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Energies, Volume 14, Issue 22 (November-2 2021) – 376 articles

Cover Story (view full-size image): Aerosol particle transport indoors, especially in educational spaces, has become a significant concern due to the COVID-19 pandemic. Classrooms with a central HVAC system respond more quickly to an internal source of contamination than those with pure air recirculation systems such as fan coil units. Furthermore, increasing the ventilation rate without improved filtration is an inefficient use of energy. View this paper
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14 pages, 23646 KiB  
Article
Influence of Clearance on the Rocker Arm Pin on the Steerability and Stability of the Vehicle Motion
by Krzysztof Parczewski and Henryk Wnęk
Energies 2021, 14(22), 7827; https://doi.org/10.3390/en14227827 - 22 Nov 2021
Cited by 5 | Viewed by 2261
Abstract
The article presents an analysis of the impact of a malfunction resulting from excessive clearance on the rocker arm pin of the front suspension on the vehicle’s steerability. The first part of the article presents an analysis of the influence of the clearance [...] Read more.
The article presents an analysis of the impact of a malfunction resulting from excessive clearance on the rocker arm pin of the front suspension on the vehicle’s steerability. The first part of the article presents an analysis of the influence of the clearance on the rocker arm pin on the geometry of the suspension and steering system. The occurrence of forces acting on the rocker arm pin in various phases of the vehicle motion was analyzed. To assess the vehicle’s steering, the vehicle’s response time to sudden steering wheel movement was used. The vehicle’s response time to sudden movement of the steering wheel was used to assess the vehicle’s steerability. The second part presents the results of bench tests and traction tests of a vehicle equipped with a specially made measuring rocker arm with the possibility of simulating a clearance. The tests were carried out on a class B passenger car in selected road tests. The results of measurements obtained for the roadworthy vehicle and the vehicle with the rocker arm with clearance were compared. The influence of the clearance on the rocker arm pin on the change of vehicle steerability in steady and dynamically changing conditions was analyzed. The test results show the effect of clearance on vehicle steering and on the vehicle steerability. The study tried to determine to what extent the clearance on the rocker arm affects the vehicle’s steerability and thus the safety in road traffic. Full article
(This article belongs to the Special Issue Vehicle and Traffic Safety)
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<p>Assessment of vehicle steerability depending on the vehicle response time [<a href="#B16-energies-14-07827" class="html-bibr">16</a>,<a href="#B17-energies-14-07827" class="html-bibr">17</a>].</p>
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<p>Forces acting on the rocker arm pin (<b>a</b>), rocker arm pin (<b>b</b>): <span class="html-italic">F</span>—force acting on the bodywork, <span class="html-italic">F<sub>s</sub></span>—side force, <span class="html-italic">F<sub>z</sub></span>—vertical force.</p>
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<p>Forces acting on the rocker arm pin during the turning maneuver: <span class="html-italic">F<sub>x</sub></span>—longitudinal force, <span class="html-italic">F<sub>y</sub></span>—lateral force, <span class="html-italic">e<sub>y</sub></span>—lateral displacement of the center of the tire footprint, <span class="html-italic">s</span>—displacement of the center of the tire footprint in the longitudinal direction, <span class="html-italic">δ</span>—the steering angle of the wheel.</p>
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<p>Change of the steering angle caused by clearance on the rocker arm pin: <span class="html-italic">∆δ</span>—changing the steering angle of the wheel, <span class="html-italic">γ</span>—steering arm inclination angle.</p>
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<p>Forces acting on the rocker arm pin during various cases of vehicle motion (for a positive swing radius): (<b>a</b>) acceleration, (<b>b</b>) braking, (<b>c</b>) driving along a road curve: <span class="html-italic">F<sub>s</sub></span>—side force, <span class="html-italic">F<sub>y</sub></span>—lateral force, <span class="html-italic">F<sub>y</sub></span>—longitudinal force, <span class="html-italic">F<sub>s</sub></span>—centrifugal force.</p>
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<p>View of the measuring arm.</p>
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<p>Measurement of the required lateral force to eliminate the rocker arm clearance.</p>
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<p>Characteristics of resetting the rocker arm clearance.</p>
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<p>Change of the trajectory caused by resetting the rocker arm clearance while driving on a circular track (driving at a speed of ~30 km/h within a radius of ~22 m).</p>
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<p>Change of the trajectory caused by resetting the rocker arm pin clearance (driving at ~40 km/h).</p>
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<p>The angle of rotation of the steering wheel during the lane change maneuver (driving at ~40 km/h).</p>
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<p>Change of the trajectory caused by resetting the rocker arm clearance during braking (blue line—braking start).</p>
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<p>The angles of rotation of the steering wheel during the braking maneuver (initial speed ~70 km/h).</p>
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<p>Vehicle steerability depending on yaw speed and vehicle response time [<a href="#B16-energies-14-07827" class="html-bibr">16</a>,<a href="#B17-energies-14-07827" class="html-bibr">17</a>] and own research.</p>
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23 pages, 1367 KiB  
Article
Economic and Environmental Aspects of Agriculture in the EU Countries
by Joanna Domagała
Energies 2021, 14(22), 7826; https://doi.org/10.3390/en14227826 - 22 Nov 2021
Cited by 10 | Viewed by 3614
Abstract
The analysis of the economic efficiency of agriculture has been the subject of numerous studies. An economically efficient agricultural sector is not always environmentally efficient. Agriculture is a large emitter of greenhouse gases. The Intergovernmental Panel on Climate Change states that food production [...] Read more.
The analysis of the economic efficiency of agriculture has been the subject of numerous studies. An economically efficient agricultural sector is not always environmentally efficient. Agriculture is a large emitter of greenhouse gases. The Intergovernmental Panel on Climate Change states that food production and agriculture are responsible for 21–37% of total global CO2 emissions. Due to the comprehensive assessment of the agricultural efficiency, it is worthwhile to apply to its measurement an integrated approach based on economic, energy and environmental aspects. These aspects were the main reasons for undertaking this research. The purpose of the study was to determine the economic, energy and environmental efficiency of agriculture in the EU Member States in 2019. The environmental analyses relate to the period 1990–2019. A total of 26 member states of the European Union (excluding Malta and Luxembourg) were selected for research. The sources of materials were Eurostat and the European Environmental Agency. This study was based on the Data Envelopment Analysis method, and used the DEA model focused on minimizing inputs. The research also adopts energy productivity and greenhouse gas emission efficiency indicators. The DEA model features the following variables: one effect (value of agricultural production) and four inputs (land, labour, use of fertilizers and use of energy). It was found that seven out of the 26 studied EU countries have efficient agriculture. The efficient agriculture group included The Netherlands, Denmark, Greece, Cyprus, the United Kingdom, Italy and Ireland. Based on the DEA method, benchmarks have been defined for countries with inefficient agriculture. On the basis of these benchmarks for inefficient agricultural sectors, it was possible to determine how they could improve efficiency to achieve the same results with fewer inputs. This issue is particularly important in the context of sustainable agricultural development. In the next stage of the research, the analysis of economic and energy efficiency was combined with the analysis of GHG emission efficiency in agriculture. Four groups of countries have been distinguished: eco-efficiency leaders, eco-efficiency followers, environmental slackers, eco-efficiency laggards. The leaders of the classification were The Netherlands, Italy, Greece, Cyprus and Portugal. Full article
(This article belongs to the Special Issue Advances in Energy and Environmental Economics)
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<p>Change in EU-28 greenhouse gas emissions, 1990–2019 (1990 = 100). Source: European Environment Agency.</p>
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<p>Sources of greenhouse gas emissions in the EU-28, 2019. Source: European Environment Agency and Eurostat.</p>
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<p>The economic and energy efficiency of EU agriculture based on the DEA method (2019). Source: author’s own calculations based on Eurostat.</p>
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<p>Economic, energy and environmental efficiency of agriculture in EU (2019). Source: author’s own calculations.</p>
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<p>Eco-efficiency of agriculture in EU (2019). Source: own study.</p>
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19 pages, 3155 KiB  
Article
Thermal Comfort and Energy Analysis of a Hybrid Cooling System by Coupling Natural Ventilation with Radiant and Indirect Evaporative Cooling
by Pradeep Shakya, Gimson Ng, Xiaoli Zhou, Yew Wah Wong, Swapnil Dubey and Shunzhi Qian
Energies 2021, 14(22), 7825; https://doi.org/10.3390/en14227825 - 22 Nov 2021
Cited by 9 | Viewed by 3354
Abstract
A hybrid cooling system which combines natural ventilation with a radiant cooling system for a hot and humid climate was studied. Indirect evaporative cooling was used to produce chilled water at temperatures slightly higher than the dew point. With this hybrid system, the [...] Read more.
A hybrid cooling system which combines natural ventilation with a radiant cooling system for a hot and humid climate was studied. Indirect evaporative cooling was used to produce chilled water at temperatures slightly higher than the dew point. With this hybrid system, the condensation issue on the panel surface of a chilled ceiling was overcome. A computational fluid dynamics (CFD) model was employed to determine the cooling load and the parameters required for thermal comfort analysis for this hybrid system in an office-sized, well-insulated test room. Upon closer investigation, it was found that the thermal comfort by the hybrid system was acceptable only in limited outdoor conditions. Therefore, the hybrid system with a secondary fresh air supply system was suggested. Furthermore, the energy consumptions of conventional all-air, radiant cooling, and hybrid systems including the secondary air supply system were compared under similar thermal comfort conditions. The predicted results indicated that the hybrid system saves up to 77% and 61% of primary energy when compared with all-air and radiant cooling systems, respectively, while maintaining similar thermal comfort. Full article
(This article belongs to the Topic Sustainable Energy Technology)
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<p>(<b>a</b>) Configuration of proposed hybrid cooling system: (1) air–water counterflow heat exchanger; (2) air–water counterflow padding tower; (3) water pump; (4) fan; (5) chilled ceiling; (6) window opening; (7) internal heat load; (8) solar flux. (<b>b</b>) Psychrometric process to produce chilled water in IEC.</p>
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<p>(<b>a</b>) Computational domain and dimensions for office model; (<b>b</b>) exterior surface mesh; (<b>c</b>) interior surface mesh; and (<b>d</b>) volume mesh.</p>
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<p>Temperature contours (1.6 m from the wall) for the four different scenarios: (<b>a</b>) natural ventilation with radiant cooling, (<b>b</b>) hybrid system with CCP surface temperature of 26 °C, (<b>c</b>) hybrid system with CCP surface temperature of 27 °C, and (<b>d</b>) hybrid system with CCP surface temperature of 28 °C.</p>
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<p>Standard effective temperatures of the four cases.</p>
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<p>Effect of air speed on <span class="html-italic">PMV</span> and <span class="html-italic">PPD</span>.</p>
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<p>Psychrometric chart for air handling process.</p>
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<p>Psychrometric chart for dehumidification in DDS.</p>
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<p>Comparison of primary energy consumption.</p>
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<p>Design conditions for simulation of natural ventilation illustrating various domains: (<b>a</b>) Computational domain, (<b>b</b>) Boundary conditions: side view, and (<b>c</b>) Boundary conditions: top view.</p>
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<p>Velocity contours on the horizontal (x–y) plane: z = 1.1 m for (<b>a</b>) south-east wind, (<b>b</b>) north-east wind.</p>
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<p>Velocity contours on the vertical plane through middle of window opening for (<b>a</b>) south-east wind and (<b>b</b>) north-east wind.</p>
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<p>Cross-ventilation model [<a href="#B51-energies-14-07825" class="html-bibr">51</a>].</p>
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<p>Comparison of simulated and experimental results for air velocity through the opening.</p>
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<p>Comparison of simulated and experimental results for air temperature and cooling capacity.</p>
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21 pages, 1113 KiB  
Article
Stability Metric Based on Sensitivity Analysis Applied to Electrical Repowering System
by João R. B. Paiva, Alana S. Magalhães, Pedro H. F. Moraes, Júnio S. Bulhões and Wesley P. Calixto
Energies 2021, 14(22), 7824; https://doi.org/10.3390/en14227824 - 22 Nov 2021
Cited by 3 | Viewed by 2116
Abstract
Stability metrics are used to quantify a system’s ability to maintain equilibrium under disturbances. We did not identify the proposition of a stability metric using sensitivity analysis within the literature. This work proposes a system stability metric and its application to an electrical [...] Read more.
Stability metrics are used to quantify a system’s ability to maintain equilibrium under disturbances. We did not identify the proposition of a stability metric using sensitivity analysis within the literature. This work proposes a system stability metric and its application to an electrical repowering system. The methodology for applying the proposed metric comprises: (i) system parameters sensitivity analysis and spider diagram construction, (ii) determining the array containing the line segments inclination angles of each spider diagram curve, and (iii) stability calculation using the array mean and maximum inclination value of a line segment. After simulating the model built for the electrical repowering system and applying the methodology, we obtain results regarding the sensitivity indices and stability values of system inputs relative to their outputs, considering the original system and with reduced parameters. Using the stability study, it was possible to determine different stability categories for the system parameters, which indicates the need for different analysis levels. Full article
(This article belongs to the Section F: Electrical Engineering)
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<p>Local sensitivity analysis for a system with multiple inputs and one output. One-at-a-time measurements are performed for each input system parameter.</p>
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<p>Parameter suppression process in a system with four inputs and multiple outputs.</p>
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<p>Keeping outputs <math display="inline"><semantics> <mover accent="true"> <msub> <mi>y</mi> <mn>1</mn> </msub> <mo>→</mo> </mover> </semantics></math>, <math display="inline"><semantics> <mover accent="true"> <msub> <mi>y</mi> <mn>2</mn> </msub> <mo>→</mo> </mover> </semantics></math> and <math display="inline"><semantics> <mover accent="true"> <msub> <mi>y</mi> <mn>3</mn> </msub> <mo>→</mo> </mover> </semantics></math> considering the reduction from four to three input parameters.</p>
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<p>Spider diagram for a hypothetical system with three input parameters.</p>
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<p>Delimitation of right triangle with angle <math display="inline"><semantics> <mi>α</mi> </semantics></math>, considering a specific line segment and the horizontal plane.</p>
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<p>Cases of greater and less stability. (<b>a</b>) Greater stability: <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <msup> <mn>0</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>. (<b>b</b>) Less stability: <math display="inline"><semantics> <mrow> <mi>α</mi> <mo>=</mo> <msup> <mn>90</mn> <mo>∘</mo> </msup> </mrow> </semantics></math>.</p>
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<p>Activity flowchart to obtain the <math display="inline"><semantics> <msub> <mi>x</mi> <mi>i</mi> </msub> </semantics></math> parameter stability relative to the system output.</p>
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<p>Interconnected Power System (IPS) used for case study. Adapted from [<a href="#B69-energies-14-07824" class="html-bibr">69</a>].</p>
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<p>Representation of inputs and outputs considered in the electrical repowering system study.</p>
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<p>Electrical repowering system with reduced quantity from four to three input parameters. (<b>a</b>) <math display="inline"><semantics> <msub> <mi>V</mi> <mi>f</mi> </msub> </semantics></math> suppression. (<b>b</b>) <math display="inline"><semantics> <msub> <mi>ω</mi> <mrow> <mi>G</mi> <mi>I</mi> </mrow> </msub> </semantics></math> suppression.</p>
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<p>Number of occurrences of each stability category in the selected electrical repowering system scenarios.</p>
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<p>Single-line diagram of a power system with <span class="html-italic">b</span>-buses.</p>
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25 pages, 1826 KiB  
Article
Energy-Efficient and Disjoint Multipath Using Face Routing in Wireless Sensor Networks
by Hyunchong Cho, Seungmin Oh, Yongje Shin and Euisin Lee
Energies 2021, 14(22), 7823; https://doi.org/10.3390/en14227823 - 22 Nov 2021
Cited by 1 | Viewed by 1685
Abstract
In WSNs, multipath is well-known as a method to improve the reliability of packet delivery by making multiple routes from a source node to a destination node. To improve reliability and load-balancing, it is important to ensure that disjoint characteristics of multipath do [...] Read more.
In WSNs, multipath is well-known as a method to improve the reliability of packet delivery by making multiple routes from a source node to a destination node. To improve reliability and load-balancing, it is important to ensure that disjoint characteristics of multipath do not use same nodes during path generation. However, when multipath studies encounter a hole area from which is hard to transmit data packets, they have a problem with breaking the disjoint features of multipath. Although existing studies propose various strategies to bypass hole areas, they have side effects that significantly accelerate energy consumption and packet transmission delay. Therefore, to retain the disjoint feature of multipath, we propose a new scheme that can reduce delay and energy consumption for a node near a hole area using two approaches—global joint avoidance and local avoidance. This scheme uses global joint avoidance to generate a new path centered on a hole area and effectively bypasses the hole area. This scheme also uses local joint avoidance that does not select the same nodes during new path generation using a marking process. In simulations, the proposed scheme has an average 30% improvement in terms of average energy consumption and delay time compared to other studies. Full article
(This article belongs to the Special Issue Green Network Technologies and Renewable Energy Systems)
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<p>The frequent communication problem when face routing is used near the hole area.</p>
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<p>Greedy forwarding failure (<b>left</b>) and face routing (<b>right</b>).</p>
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<p>The overlapping problem near the hole area during multipath generation.</p>
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<p>The isolated problem near the hole area during the multipath generation.</p>
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<p>The inefficient problem near the hole area during multipath generation.</p>
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<p>Local joint avoidance during multipath generation.</p>
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<p>Marking process in an isosceles triangle area near a hole area.</p>
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<p>Average energy consumption according to hole size.</p>
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<p>Average energy consumption according to end-to-end distance.</p>
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<p>Average energy consumption according to the radio range of each node.</p>
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<p>Average delay time according to hole size.</p>
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<p>Average delay time according to end-to-end distance.</p>
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<p>The average delay time according to the radio range of a node.</p>
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17 pages, 11482 KiB  
Article
Electrical Double Layer Mechanism Analysis of PEM Water Electrolysis for Frequency Limitation of Pulsed Currents
by Jae-Hoon Kim, Chang-Yeol Oh, Ki-Ryong Kim, Jong-Pil Lee and Tae-Jin Kim
Energies 2021, 14(22), 7822; https://doi.org/10.3390/en14227822 - 22 Nov 2021
Cited by 6 | Viewed by 3320
Abstract
This paper proposes a method for improving hydrogen generation using pulse current in a proton exchange membrane-type electrolyzer (PEMEL). Traditional methods of electrolysis using direct current are known as the simplest approach to produce hydrogen. However, it is highly dependent on environmental variables, [...] Read more.
This paper proposes a method for improving hydrogen generation using pulse current in a proton exchange membrane-type electrolyzer (PEMEL). Traditional methods of electrolysis using direct current are known as the simplest approach to produce hydrogen. However, it is highly dependent on environmental variables, such as the temperature and catalyst used, to enhance the rate of electrolysis. Therefore, we propose electrolysis using a pulse current that can apply several dependent variables rather than environmental variables. The proposed method overcomes the difficulties in selecting the frequency of the pulse current by deriving factors affecting hydrogen generation while changing the concentration generated by the cell interface during the pulsed water-electrolysis process. The correlation between the electrolyzer load and the frequency characteristics was analyzed, and the limit value of the applicable frequency of the pulse current was derived through electrical modeling. In addition, the operating characteristics of PEMEL could be predicted, and the PEMEL using the proposed pulse current was verified through experiments. Full article
(This article belongs to the Special Issue Advances in Hydrogen Energy Production and Storage)
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<p>Pulse operation by voltage pulse.</p>
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<p>I–V characteristic curve of electrolyzer according to pulse-on time variable.</p>
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<p>I–V characteristic curve of electrolyzer according to pulse-amplitude variable.</p>
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<p>Equivalent circuit of water electrolysis load.</p>
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<p>Frequency dependence of electrical polarization.</p>
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<p>Concentration gradients of internal chemical species in the water electrolyzer.</p>
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<p>Frequency vs. H<sub>2</sub> production characteristic curve of electrolyzer according to pulse-frequency variable.</p>
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<p>I–V characteristic curve of water electrolyzer: (<b>a</b>) the whole experiment, (<b>b</b>) a specific operating point.</p>
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<p>Initial instantaneous charging current when intermittent pulse potential is applied.</p>
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<p>Steady-state current when intermittent pulse potential is applied.</p>
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<p>Flowchart of electrical modeling.</p>
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<p>Frequency vs. H<sub>2</sub> characteristic curves of electrolyzer with pulse-frequency variable limits applied.</p>
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<p>A PEM electrolysis system.</p>
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<p>DC and pulsed operation simulation results: (<b>a</b>) DC, (<b>b</b>) Pulse operation.</p>
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<p>Stack voltage and current pulse patterns applied to the experiment.</p>
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16 pages, 412 KiB  
Article
Prosumers’ Needs Satisfied Due to Cooperation with Offerors in the Context of Attitudes toward Such Cooperation
by Agnieszka Izabela Baruk
Energies 2021, 14(22), 7821; https://doi.org/10.3390/en14227821 - 22 Nov 2021
Cited by 2 | Viewed by 1834
Abstract
The purpose of this article is to determine final purchasers’ needs satisfied due to cooperation with offerors and the dependencies between these needs and previous behaviors and attitudes toward this cooperation. The results of the world literature analysis indicate a cognitive and research [...] Read more.
The purpose of this article is to determine final purchasers’ needs satisfied due to cooperation with offerors and the dependencies between these needs and previous behaviors and attitudes toward this cooperation. The results of the world literature analysis indicate a cognitive and research gap regarding the aspects mentioned. In order to reduce the gap, empirical studies were conducted, in which an online questionnaire was used to gather primary data. The research was implemented in the second half of 2020 among 1150 respondents representing Polish adult final purchasers. The data were subjected to quantitative analysis using statistical analysis and statistical testing, including exploratory factor analysis, cluster analysis, Pearson chi-square independence test, V-Cramer contingency coefficient analysis, and Kruskal–Wallis test. The results of the statistical analysis made it possible to verify six research hypotheses. Dependencies were found between needs satisfied due to cooperation with offerors and the following aspects: (1) purchasers’ previous participation in cooperation with offerors, (2) purchasers’ willingness to cooperate with offerors, and (3) the assessment of contemporary purchasers’ readiness to cooperate with offerors. Willingness to cooperate with offerors differentiated all eleven needs satisfied due to cooperation with offerors analyzed in this study. Two other variables differentiated only a few of the needs analyzed. The results obtained from the research have a cognitive and applicability value. They contribute to theory of marketing and market behavior. They can also facilitate establishing and strengthening cooperation between offerors and final purchasers as important partners cooperating in the process of creating a marketing offer. This effect is very important in the case of shaping the cooperation between final purchasers and offerors of different products including energy ones. The originality of the approach proposed is evidenced by the fact it is the first time final purchasers’ needs that can be satisfied due to cooperation with offerors have been analyzed in the context of attitudes and behavior reflecting purchasers’ (1) previous participation in this cooperation, (2) willingness to cooperate with offerors, and (3) the assessment of contemporary final purchasers’ readiness to cooperate with offerors. Full article
(This article belongs to the Special Issue Sustainable Production and Environmentally Responsible Consumption)
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<p>Dendrogram using the Ward link showing the structure of needs, which according to respondents, are satisfied due to cooperation with offerors. Where: symbols as in <a href="#energies-14-07821-t001" class="html-table">Table 1</a>.</p>
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21 pages, 4849 KiB  
Article
A Novel Short-Term Residential Electric Load Forecasting Method Based on Adaptive Load Aggregation and Deep Learning Algorithms
by Tingting Hou, Rengcun Fang, Jinrui Tang, Ganheng Ge, Dongjun Yang, Jianchao Liu and Wei Zhang
Energies 2021, 14(22), 7820; https://doi.org/10.3390/en14227820 - 22 Nov 2021
Cited by 21 | Viewed by 2608
Abstract
Short-term residential load forecasting is the precondition of the day-ahead and intra-day scheduling strategy of the household microgrid. Existing short-term electric load forecasting methods are mainly used to obtain regional power load for system-level power dispatch. Due to the high volatility, strong randomness, [...] Read more.
Short-term residential load forecasting is the precondition of the day-ahead and intra-day scheduling strategy of the household microgrid. Existing short-term electric load forecasting methods are mainly used to obtain regional power load for system-level power dispatch. Due to the high volatility, strong randomness, and weak regularity of the residential load of a single household, the mean absolute percentage error (MAPE) of the traditional methods forecasting results would be too big to be used for home energy management. With the increase in the total number of households, the aggregated load becomes more and more stable, and the cyclical pattern of the aggregated load becomes more and more distinct. In the meantime, the maximum daily load does not increase linearly with the increase in households in a small area. Therefore, in our proposed short-term residential load forecasting method, an optimal number of households would be selected adaptively, and the total aggregated residential load of the selected households is used for load prediction. In addition, ordering points to identify the clustering structure (OPTICS) algorithm are also selected to cluster households with similar power consumption patterns adaptively. It can be used to enhance the periodic regularity of the aggregated load in alternative. The aggregated residential load and encoded external factors are then used to predict the load in the next half an hour. The long short-term memory (LSTM) deep learning algorithm is used in the prediction because of its inherited ability to maintain historical data regularity in the forecasting process. The experimental data have verified the effectiveness and accuracy of our proposed method. Full article
(This article belongs to the Special Issue Artificial Intelligence for Buildings)
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<p>The maximum daily loads of the customer numbered as 10006414 from February 2012 to March 2014.</p>
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<p>The maximum daily loads of the selected ten customers in March 2013.</p>
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<p>The distribution probability of mean daily loading rates of eighty selected customers: (<b>a</b>) 1 March; (<b>b</b>) 5 March; (<b>c</b>) 10 March.</p>
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<p>The quantitative indexes of total electric loads of the ten selected residents: (<b>a</b>) maximum daily load; (<b>b</b>) mean daily load; (<b>c</b>) daily load rate; (<b>d</b>) minimum daily load rate; (<b>e</b>) volatility index.</p>
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<p>The quantitative indexes of total electric loads of the ten selected residents: (<b>a</b>) maximum daily load; (<b>b</b>) mean daily load; (<b>c</b>) daily load rate; (<b>d</b>) minimum daily load rate; (<b>e</b>) volatility index.</p>
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<p>The detailed residential load prediction process of our proposed method.</p>
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<p>The LSTM-based short-term residential load prediction process.</p>
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<p>Histogram of MAPE values of forecasting results on 31 March for the selected 200 households.</p>
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<p>Clustering results of daily load curves of selected residents (<b>a</b>) Customer id:10006704; (<b>b</b>) Customer id: 10006414; (<b>c</b>) Customer id: 10006486; (<b>d</b>) Customer id: 10006674.</p>
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<p>The detailed forecasting results at 48 points on 31 March (<b>a</b>) 150 households; (<b>b</b>) 200 households.</p>
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<p>The detailed forecasting results at 336 points from 25 March to 31 March.</p>
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20 pages, 26447 KiB  
Article
Influence of Photovoltaic Development on Decarbonization of Power Generation—Example of Poland
by Grzegorz Lew, Beata Sadowska, Katarzyna Chudy-Laskowska, Grzegorz Zimon and Magdalena Wójcik-Jurkiewicz
Energies 2021, 14(22), 7819; https://doi.org/10.3390/en14227819 - 22 Nov 2021
Cited by 24 | Viewed by 3166
Abstract
Climate change is becoming a global problem. In many countries, actions are taken with the main aim of reducing CO2 emissions. The main action, especially in developed countries, is decarbonization. The European Union has become one of the organizations that plays a [...] Read more.
Climate change is becoming a global problem. In many countries, actions are taken with the main aim of reducing CO2 emissions. The main action, especially in developed countries, is decarbonization. The European Union has become one of the organizations that plays a leading role in decarbonization of the economy. For this reason, renewable energy sources are being intensively developed in the EU countries. Solar energy with the use of PV installations is developing the fastest. Poland is one of the European leaders in photovoltaic development, and according to estimates for 2021–2025, it will continue to be. The aim of this study was to find out the opinions of people toward actions related to the decarbonization policy in Poland. These opinions were obtained through the prism of respondents’ attitudes toward energy produced by means of PV micro-installations. A questionnaire survey was used in this research. The survey was conducted using the CAWI (Computer-Assisted Web Interview) technique. To analyze the results of the study, a Kruskal–Wallis ANOVA test and U–Mann Whitney test were used. Responses were obtained from 633 people. The results obtained from the survey allowed us to draw conclusions, which include the following: (1) a lack of general conviction of respondents about the effectiveness of Poland’s decarbonization policy on reducing global CO2 emissions, especially among those who show a higher willingness to use PV installations, (2) the willingness to use PV installations is motivated by economic rather than environmental benefits, (3) the need for more widespread public campaigns aimed at promoting the benefits of decarbonization and renewable energy sources, and (4) the finding that the respondents’ region of residence (with a different degree of insolation) mattered for the willingness to use PV installations. Full article
(This article belongs to the Collection Feature Papers in Energy, Environment and Well-Being)
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<p>Share of renewable energy sources in gross final energy consumption. Source: Own study based on [<a href="#B15-energies-14-07819" class="html-bibr">15</a>].</p>
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<p>Structure of electricity generation sources in Poland (July 2021). Source: Own study based on data from Polish Power Grid [<a href="#B16-energies-14-07819" class="html-bibr">16</a>].</p>
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<p>Share of installed PV solar panels in 2020. Source: Own elaboration based on [<a href="#B30-energies-14-07819" class="html-bibr">30</a>].</p>
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<p>Forecasted increase in solar energy capacity. Source: Own study based on [<a href="#B30-energies-14-07819" class="html-bibr">30</a>].</p>
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<p>Change dynamics of production costs of 1 MWh. Source: Own elaboration based on [<a href="#B33-energies-14-07819" class="html-bibr">33</a>].</p>
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<p>Insolation map of Poland with study areas marked. Source: Own elaboration based on [<a href="#B50-energies-14-07819" class="html-bibr">50</a>].</p>
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<p>Will the decarbonization policy in Poland contribute to reducing global CO<sub>2</sub> emissions vs. assessment of the willingness to use PV installations.</p>
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<p>Statistics on responses to the question: Which sectors of the economy are most vulnerable to the impact of decarbonization policies?</p>
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<p>Which sectors of the economy are most affected by the decarbonization policy (mining) vs. assessment of the willingness to use PV installations?</p>
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<p>Which sectors of the economy are most affected by decarbonization policies (logistics) vs. assessment of the willingness to use PV installations?</p>
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<p>Which sectors of the economy are most affected by the decarbonization policy (medical industry) vs. assessment of the willingness to use PV installations?</p>
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<p>Statistics of responses to the question: Which sectors of the economy are most vulnerable to the impact of decarbonization policies?</p>
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<p>Statistics of responses to the question: What effects can decarbonization policies have?</p>
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<p>What effects can decarbonization policies have: increased consumer awareness (e.g., reducing energy consumption) vs. assessment of the willingness to use PV installations.</p>
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<p>What is the biggest barrier to decarbonization in transport (lack of access to finance for investment) vs. assessment of the willingness to use PV installations.</p>
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<p>What is the biggest barrier to decarbonization in transport (lack of public interest in decarbonization) vs. assessment of the willingness to use PV installations.</p>
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<p>Region vs. assessment of the willingness to use PV installations.</p>
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<p>Electricity production from RES in GWh. Data from June 2020 and 2021. Source: own elaboration based on [<a href="#B55-energies-14-07819" class="html-bibr">55</a>].</p>
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24 pages, 3812 KiB  
Article
Analysis of Geologic CO2 Migration Pathways in Farnsworth Field, NW Anadarko Basin
by Jolante van Wijk, Noah Hobbs, Peter Rose, Michael Mella, Gary Axen and Evan Gragg
Energies 2021, 14(22), 7818; https://doi.org/10.3390/en14227818 - 22 Nov 2021
Cited by 5 | Viewed by 2919
Abstract
This study reports on analyses of natural, geologic CO2 migration paths in Farnsworth Oil Field, northern Texas, where CO2 was injected into the Pennsylvanian Morrow B reservoir as part of enhanced oil recovery and carbon sequestration efforts. We interpret 2D and [...] Read more.
This study reports on analyses of natural, geologic CO2 migration paths in Farnsworth Oil Field, northern Texas, where CO2 was injected into the Pennsylvanian Morrow B reservoir as part of enhanced oil recovery and carbon sequestration efforts. We interpret 2D and 3D seismic reflection datasets of the study site, which is located on the western flank of the Anadarko basin, and compare our seismic interpretations with results from a tracer study. Petroleum system models are developed to understand the petroleum system and petroleum- and CO2-migration pathways. We find no evidence of seismically resolvable faults in Farnsworth Field, but interpret a karst structure, erosional structures, and incised valleys. These interpretations are compared with results of a Morrow B well-to-well tracer study that suggests that inter-well flow is up-dip or lateral. Southeastward fluid flow is inhibited by dip direction, thinning, and draping of the Morrow B reservoir over a deeper, eroded formation. Petroleum system models predict a deep basin-ward increase in temperature and maturation of the source rocks. In the northwestern Anadarko Basin, petroleum migration was generally up-dip with local exceptions; the Morrow B sandstone was likely charged by formations both below and overlying the reservoir rock. Based on this analysis, we conclude that CO2 escape in Farnsworth Field via geologic pathways such as tectonic faults is unlikely. Abandoned or aged wellbores remain a risk for CO2 escape from the reservoir formation and deserve further monitoring and research. Full article
(This article belongs to the Special Issue Forecasting CO2 Sequestration with Enhanced Oil Recovery)
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<p>Location of the study site (dark blue star) in Ochiltree County (yellow) in the western Anadarko Basin (blue). Modified from [<a href="#B6-energies-14-07818" class="html-bibr">6</a>]. Contours: depth to top Arbuckle Group. The Arbuckle Group is below the Morrow B reservoir, and pre-dates the basin’s flexural subsidence phase. Contour interval 1000 ft below surface. Black solid lines: major faults. MF = Meers fault zone, MU = Muenster Arch, MVF = Mountain View fault zone, NE = Nemaha uplift, WF = Willow fault zone. Dashed black lines are state boundaries: CO = Colorado, KS = Kansas, OK = Oklahoma, TX = Texas. See <a href="#energies-14-07818-f002" class="html-fig">Figure 2</a> for details and the location of Farnsworth Field.</p>
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<p>Overview map of Farnsworth Field study site within Ochiltree County, seismic lines and well data used in this study, and locations of 2D seismic lines and 3D seismic survey. The inset shows the location (grey) of the map. The Killingsworth well has been used for the well-tie with DC-NEP-10. Well 13-10A is a CO<sub>2</sub> injection well in Farnsworth Field.</p>
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<p>Simplified stratigraphic column of Farnsworth Field area, with details of CO<sub>2</sub> reservoir (Morrow B) and cap rock at well 13–10A (location of this well is shown in <a href="#energies-14-07818-f002" class="html-fig">Figure 2</a>), and major tectonic events (in red). Grain size: F is fine, M is medium, C is coarse, VC is very coarse.</p>
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<p>Interpretation of seismic lines DC-NEP-10 (short east–west line) and DC-NEP-33 (north and south), and well-tie with the Killingsworth well (light blue). Locations of lines and Killingsworth well shown in <a href="#energies-14-07818-f002" class="html-fig">Figure 2</a>. The Atokan/Morrowan formations are mostly transparent, and their boundaries cannot be resolved in these data. The Missourian Kansas City Group and Late Devonian-Early Mississippian Woodford shale are interpreted in the 3D seismic data (<a href="#energies-14-07818-f005" class="html-fig">Figure 5</a>). No seismically resolvable faults are observed on the 2D seismic lines in the Atokan or Morrowan formations.</p>
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<p>Interpreted horizons at location of well 13-10A (<b>a</b>); Top Kansas City Formation (<b>b</b>); and Base Hunton Formation (<b>c</b>). Farnsworth Field is outlined in red; also shown are locations of wells 13-10A, 13-14, and 32-8. Based on well ties, the “Morrow B reflector” is located within the Morrow B.</p>
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<p>The Morrow B surface displaying the three characterization wells 13-10A, 13-14, and 32-8; (<b>a</b>) the Variance attribute overlain on the Morrow B surface; and (<b>b</b>) the Ant Tracking attribute overlain on the Ant Tracking volume. Features discussed in text are labeled as I, II, and III. In (<b>a</b>), the concentric rings in the eastern side of the survey have not been identified in other attributes and there is no evidence that they are geologic features.</p>
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<p>(<b>a</b>) Two seismic lines through the feature (labeled I and II in <a href="#energies-14-07818-f006" class="html-fig">Figure 6</a>) in the western part of Farnsworth Field; locations of lines indicated in (<b>b</b>); (<b>b</b>) portion of Farnsworth Field (outlined in red) and locations of seismic lines; (<b>c</b>) karst collapse infill structure in the eastern part of Farnsworth Field; location of east line indicated in (<b>b</b>). Vertical lines in (<b>a</b>) mark the dashed line in (<b>b</b>).</p>
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<p>(<b>a</b>) Location of three channel-like features in the western Farnsworth Field; (<b>b</b>) details of seismic line intersecting channel 1; (<b>c</b>) details of seismic line intersecting channel 2; (<b>d</b>) details of seismic line intersecting feature 3.</p>
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<p>(<b>a</b>) Returns to well 11-2 of tracers 1,6-nds, 1,3,6-nts, and 1,5-nds that were injected into wells 13-13, 13-10A, and 13-5, respectively, on 2 May 2014; (<b>b</b>) returns to well 13-17 of the tracer 1,5-nds that was injected into well 13-5 during the 2014 tracing campaign.</p>
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<p>(<b>a</b>) Tracer 2,7-nds concentrations measured in well 13–19. 100 kg of this tracer was injected into water-injection well 14-1 on 13 October 2015; (<b>b</b>) 2,7-nds concentrations measured in well 13-14; (<b>c</b>) 2,7-nds concentrations measured in well 13-12. A paucity of data points on this plot reflects the fact that this well was sampled infrequently; (<b>d</b>) 2,7-nds concentrations measured in well 8-2. The paucity of data points on this plot reflects the fact that this well was sampled relatively infrequently; (<b>e</b>) 2,7-nds concentrations measured in well 20-8.</p>
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<p>Returns of the tracers 2,6-nds and 2-ns, which were injected into well 13-3.</p>
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<p>Farnsworth Field map of Morrow B isochore from well logs (well locations shown in White et al., 2017, <a href="#energies-14-07818-f003" class="html-fig">Figure 3</a>); tracer injection wells (triangles) and detection wells (stars) from tracer studies conducted in 2014, 2015, and 2017 indicated in grey, red, and blue, respectively. Stars mark wells where tracers were detected: injections in 13-13, 13-10A, and 13-5 were detected in 11-2; injections in 13-5 were detected in 13-17; injections in 13-13 were detected in 11-2; injections in 14-1 were detected in 13-12, 13-14, 13-19, 8-2, and 20-8; injections in 13-3 were detected in 8-2.</p>
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<p>Burial and temperature history for well 13-10A. Before onset of the Laramide uplift, the source rocks from which hydrocarbons in Farnsworth Field are sourced (<a href="#energies-14-07818-t001" class="html-table">Table 1</a>; Woodford, Morrowan, and Atokan) reached the oil/gas windows.</p>
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<p>Details of seismic line DC-NEP-33 (location in <a href="#energies-14-07818-f002" class="html-fig">Figure 2</a>) with a Morrowan sandstone layer (yellow) that is encased in shale (light red). The projected location of the Killingsworth well is marked. Geometry of the sand body is based on well logs and average reservoir dimensions (see text for discussion). Colors correspond to the age of deposition, except for the Morrow sandstone, which is of Morrowan age.</p>
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<p>Vitrinite reflectance and liquid (green) and gas (red) migration pathways predicted by Schlumberger Petromod<sup>®</sup> software. The Morrowan formation is divided into an Upper and Lower Morrow shale. The black box is enlarged in the inset; the reservoir sandstone formation (yellow) is charged by the Upper and Lower Morrowan shales, the Woodford, and the Thirteen Finger Limestone.</p>
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13 pages, 2685 KiB  
Article
A Study on the Possibility of Measuring Sludge Sedimentation Using Contrast Detection Characteristics of CdS Photoresistors
by Seong-Min Hong, Hyun-Ook Kim and Choong-Gon Kim
Energies 2021, 14(22), 7817; https://doi.org/10.3390/en14227817 - 22 Nov 2021
Viewed by 1883
Abstract
Although operators periodically measure the sludge volume index (SVI) to stabilize the bioreactor and solid–liquid separation during the wastewater treatment process, there is a problem of inconsistency attributed to the subjective judgment of the operator. This study aims to investigate the possibility of [...] Read more.
Although operators periodically measure the sludge volume index (SVI) to stabilize the bioreactor and solid–liquid separation during the wastewater treatment process, there is a problem of inconsistency attributed to the subjective judgment of the operator. This study aims to investigate the possibility of securing objective data by employing CdS (cadmium–sulfur) photoresistors for SVI measurements. The sedimentation velocity of settling sludge was measured using LED (Light Emitting Diode) lights at the same level as the installed CdS photoresistors. As a result of the experiment, the settling velocity of sludge in the CdS photoresistors’ installation position H1 to H8 (non-flocculent settling), H9 to H12 (discrete flocculent settling) and H13 to H18 (zone settling and compressive settling), was 0.594 mm/s, 0.180 mm/s and 0.056 mm/s, respectively. Through this study, it was confirmed that measuring sludge sedimentation using the CdS photoresistors is possible. If the measurement of solid matter in sludge using several sludge sedimentation measurements is enabled in the future, it will be possible to develop calculation algorithms to measure the SVI. Full article
(This article belongs to the Special Issue Sustainable Management of Waste for Renewable Energy Resources)
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<p>(<b>a</b>) Flow chart of the sludge settling test device. (<b>b</b>) Photo of the sludge settling test device set.</p>
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<p>(<b>a</b>) Flow chart of the sludge settling test device. (<b>b</b>) Photo of the sludge settling test device set.</p>
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<p>LED characteristic. (<b>a</b>): Relative luminous intensity, (<b>b</b>): Spectral distribution.</p>
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<p>Initial for installation of CdS photoresistors height.</p>
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<p>Blank test for the sludge settling measurement sensor (●: without cylinder, ◊: with cylinder).</p>
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<p>Visual test on sludge sedimentation trend.</p>
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<p>Measurement of the bioreactor sludge by the sludge sedimentation measuring sensor.</p>
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<p>Variation of <b>H1</b>–<b>H8</b> CdS photoresistors in sludge sedimentation detecting.</p>
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<p>Variation of <b>H1</b>–<b>H8</b> CdS photoresistors in sludge sedimentation detecting.</p>
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<p>Variation of <b>H9</b>–<b>H12</b> CdS photoresistors in sludge sedimentation detecting.</p>
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<p>Variation of <b>H13</b>–<b>H20</b> CdS photoresistors in sludge sedimentation detecting.</p>
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<p>Variation of <b>H13</b>–<b>H20</b> CdS photoresistors in sludge sedimentation detecting.</p>
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16 pages, 4798 KiB  
Article
Design and Analysis of a Permanent Magnet Vernier Machine with Non-Uniform Tooth Distribution
by Fei Zhao, Mengzhu Cao, Encheng Tao and Liyi Li
Energies 2021, 14(22), 7816; https://doi.org/10.3390/en14227816 - 22 Nov 2021
Cited by 1 | Viewed by 2830
Abstract
To improve the torque performance of the permanent magnet vernier machine in the direct-drive system for Unmanned Aerial Vehicle (UAV), this paper proposes the topology of non-uniform tooth distribution. This distribution, considering the additional flux harmonics, aims to contribute to torque improvement, whereas [...] Read more.
To improve the torque performance of the permanent magnet vernier machine in the direct-drive system for Unmanned Aerial Vehicle (UAV), this paper proposes the topology of non-uniform tooth distribution. This distribution, considering the additional flux harmonics, aims to contribute to torque improvement, whereas the cogging torque also increases at the same time. A phasors method is proposed to solve the issue caused by the non-uniform structure, adjusting the mechanic angle of each tooth reasonably to restrict the cogging torque. In addition, the non-uniform design is illustrated in detail, which includes the method of grouping the teeth, considering the factors of series pole ratio and winding layout. By using the three-dimensional finite element method, torque is significantly increased without additional torque ripple, which satisfies the desired design target. Full article
(This article belongs to the Special Issue All-Electric Propulsion Technology for Electrified Aviation)
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<p>Configuration of the proposed AFPMVM: (<b>a</b>) regular topology (<b>b</b>) proposed topology.</p>
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<p>Top view of half proposed AFPMVM.</p>
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<p>Expanded view of one tooth unit in non-uniform distribution.</p>
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<p>Analytical airgap permeance in one unit of two different tooth distribution topologies.</p>
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<p>Equivalent 2D machine model (expanded at middle radius).</p>
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<p>Star of slots and resultant phasors of target machines: (<b>a</b>) regular machine with <span class="html-italic">τ<sub>t</sub></span> = 20°; (<b>b</b>) proposed machine with <span class="html-italic">τ<sub>t</sub></span> = 18.1°; (<b>c</b>) resultant phasors of back-EMF.</p>
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<p>Cogging torque verification of proposed method by FEM: (<b>a</b>) each group (<b>b</b>) sum comparison.</p>
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<p>Cogging torque phasors diagram.</p>
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<p>Cogging torque phasor diagram for equal angle: (<b>a</b>) <span class="html-italic">N<sub>non</sub></span> orders (<b>b</b>) 2 <span class="html-italic">N<sub>non</sub></span> orders (<b>c</b>) 3 <span class="html-italic">N<sub>non</sub></span> orders.</p>
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<p>Cogging torque with different tooth pitch by FEM.</p>
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<p>Design approach of non-uniform tooth distribution.</p>
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<p>The phasor of cogging torque for <span class="html-italic">n<sub>g</sub></span> group tooth.</p>
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<p>Flux density distribution of the 3D-FEM in on-load condition.</p>
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<p>Comparison of airgap flux density by FEM: (<b>a</b>) flux density waveform; (<b>b</b>) spectra of FFT.</p>
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<p>Comparison of performance at 50 rpm by FEM: (<b>a</b>) back-EMF; (<b>b</b>) electromagnetic torque with rated 0.4 A<sub>rms</sub> current.</p>
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<p>Cogging torque contrast by FEM. (<b>a</b>) Cogging torque. (<b>b</b>) Spectra of FFT.</p>
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18 pages, 1192 KiB  
Article
Prioritization of Contracting Methods for Water and Wastewater Projects Using the Fuzzy Analytic Hierarchy Process Method
by Hadi Sarvari, Daniel W. M. Chan, Behrouz Ashrafi, Timothy O. Olawumi and Nerija Banaitiene
Energies 2021, 14(22), 7815; https://doi.org/10.3390/en14227815 - 22 Nov 2021
Cited by 4 | Viewed by 2393
Abstract
This study uses the fuzzy analytical hierarchy process (FAHP) method to prioritize contracting methods to determine the most suitable contract option for water and wastewater projects (WWP). Content analysis, a two-round Delphi survey technique, and a series of validation and reliability tests helped [...] Read more.
This study uses the fuzzy analytical hierarchy process (FAHP) method to prioritize contracting methods to determine the most suitable contract option for water and wastewater projects (WWP). Content analysis, a two-round Delphi survey technique, and a series of validation and reliability tests helped establish the 18 key criteria for FAHP analysis. Consequently, data collected from experts through a pairwise comparison questionnaire form the basis for the inputs for the FAHP analysis. Consequently, the final weightings were derived for each of the key criteria and available contracting methods. The results indicate that the bilateral, cooperative, and trilateral contracting methods are the most suitable for WWP in Iran, with the highest weighting. The study provides useful guidance for the top management of project firms in selecting the optimal contracting method for their projects and offers significant contributions from theoretical and practical perspectives. Full article
(This article belongs to the Special Issue Construction Project Management 2021)
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<p>Overall research design of the study.</p>
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<p>Decision tree used in the current study.</p>
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<p>The final weighting of contracting options.</p>
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10 pages, 1846 KiB  
Article
First-Principles Study of Pt-Based Bifunctional Oxygen Evolution & Reduction Electrocatalyst: Interplay of Strain and Ligand Effects
by Seung-hoon Kim, Yoonmook Kang and Hyung Chul Ham
Energies 2021, 14(22), 7814; https://doi.org/10.3390/en14227814 - 22 Nov 2021
Cited by 6 | Viewed by 3019
Abstract
We examined the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) of Pt-based Pt3M/Pt nanoalloy catalysts (where M represents a 3d transition metal) for bifunctional electrocatalysts using spin-polarized density functional theory calculations. First, the stability of the Pt3M/Pt [...] Read more.
We examined the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) of Pt-based Pt3M/Pt nanoalloy catalysts (where M represents a 3d transition metal) for bifunctional electrocatalysts using spin-polarized density functional theory calculations. First, the stability of the Pt3M/Pt catalyst was investigated by calculating the bulk formation energy and surface separation energy. Using the calculated adsorption energies for the OER/ORR intermediates in the modeled catalysts, we predicted the OER/ORR overpotentials and potential limiting steps for each catalyst. The origins of the enhanced catalytic reactivity in Pt3M/Pt catalysts caused by strain and ligand effects are explained separately. In addition, compared to Pt(111), the OER and ORR activities in a Pt3Ni/Ptskin catalyst with a Pt skin layer were increased by 13.7% and 18.4%, respectively, due to the strain and ligand effects. It was confirmed that compressive strain and ligand effects are key factors in improving the catalytic performance of OER/ORR bifunctional catalysts. Full article
(This article belongs to the Special Issue Inorganic Nanocrystal Solar Cells)
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<p>DFT slab models. Gray, blue, and red spheres represent Pt, M, and O atoms, respectively. An asterisk (*) denotes the adsorption state.</p>
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<p>OER/ORR Gibbs free energy diagram of Pt(111) catalyst at equilibrium potential (U = 1.23 V) under acidic conditions (pH = 0 and T = 298 K) An asterisk (*) denotes the adsorption state.</p>
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<p>Relation between OER/ORR overpotential and adsorption energy of reaction intermediates O (<b>a</b>) and OH (<b>b</b>). A smaller negative value on the <span class="html-italic">x</span>-axis (to the right) indicates weaker adsorption.</p>
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<p>Changes in adsorption energy of OER/ORR intermediates due to the strain effect.</p>
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<p>(<b>a</b>) PDOS of the surface Pt atoms, and (<b>b</b>) OER/ORR Gibbs free energy diagram at equilibrium potential for Pt(111), Pt<sub>3</sub>Ni/Pt, and Pt<sub>3</sub>Ni/Pt<sub>skin</sub> catalysts. An asterisk (*) denotes the adsorption state.</p>
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27 pages, 11313 KiB  
Article
Long-Term Expansion Planning of the Transmission Network in India under Multi-Dimensional Uncertainty
by Spyros Giannelos, Anjali Jain, Stefan Borozan, Paola Falugi, Alexandre Moreira, Rohit Bhakar, Jyotirmay Mathur and Goran Strbac
Energies 2021, 14(22), 7813; https://doi.org/10.3390/en14227813 - 22 Nov 2021
Cited by 19 | Viewed by 3203
Abstract
Considerable investment in India’s electricity system may be required in the coming decades in order to help accommodate the expected increase of renewables capacity as part of the country’s commitment to decarbonize its energy sector. In addition, electricity demand is geared to significantly [...] Read more.
Considerable investment in India’s electricity system may be required in the coming decades in order to help accommodate the expected increase of renewables capacity as part of the country’s commitment to decarbonize its energy sector. In addition, electricity demand is geared to significantly increase due to the ongoing electrification of the transport sector, the growing population, and the improving economy. However, the multi-dimensional uncertainty surrounding these aspects gives rise to the prospect of stranded investments and underutilized network assets, rendering investment decision making challenging for network planners. In this work, a stochastic optimization model is applied to the transmission network in India to identify the optimal expansion strategy in the period from 2020 until 2060, considering conventional network reinforcements as well as energy storage investments. An advanced Nested Benders decomposition algorithm was used to overcome the complexity of the multistage stochastic optimization problem. The model additionally considers the uncertainty around the future investment cost of energy storage. The case study shows that deployment of energy storage is expected on a wide scale across India as it provides a range of benefits, including strategic investment flexibility and increased output from renewables, thereby reducing total expected system costs; this economic benefit of planning with energy storage under uncertainty is quantified as Option Value and is found to be in excess of GBP 12.9 bn. The key message of this work is that under potential high integration of wind and solar in India, there is significant economic benefit associated with the wide-scale deployment of storage in the system. Full article
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<p>Diagram of the decomposition algorithm.</p>
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<p>Diagram of the electricity grid of India, which consists of 5 regions and 30 states (shown as blue circles along with their abbreviations).</p>
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<p>Diagram of the electricity grid of India, with the 62 transmission lines appearing where six of them are HVDC (shown in blue).</p>
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<p>Scenario tree structure, consisting of 11 scenario-tree nodes, illustrating the uncertainty around three quantities in the following order; namely around battery storage investment cost (in £k/ kW), around the installed generation capacity of solar PV across India (GW) and around the installed generation capacity of wind units across India (GW). Note that epoch1 (1 January 2020–31 December 2029) covers node 1, and epoch2 (1 January 2030–31 December 2039) covers nodes 2–3, while epoch3 (1 January 2040–31 December 2049) covers nodes 4–7 and epoch4 (1 January 2050–31 December 2059) covers nodes 8–11. Very high values for wind and solar were applied to the period 2050–2060 (last epoch) to also account for future increases beyond the problem horizon. The values over the straight lines connecting nodes indicate probabilities of transition (e.g., it is 60% likely to go from node 3 to node 6), while the probability from nodes of the third epoch (nodes 4–7) to those of the last epoch (nodes 8–11) is 100% (i.e., deterministic transition).</p>
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<p>Peak demand (GW) across India for each of the four epochs (2020–2029, 2030–2039, 2040–2049, 2050–2059).</p>
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<p>Optimal investment strategy for the case with only conventional investments. The notation (i-j) represents the upgrade of the capacity of the transmission line connected buses (i.e., India states) i and j. Note that the scenario tree depicts investment decisions, i.e., the capacity upgrades will become operational one epoch afterwards (this is why there are no investment decisions taken in the last epoch as there is no epoch5).</p>
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<p>Optimal investment strategy for the case with conventional and energy storage investments. The notation (z) represents energy storage investment in bus (i.e., India state) z.</p>
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<p>Aggregate investments in the transmission system of India as of 2050 (scenario-tree node 8) with conventional reinforcements only. Dashed lines represent existing transmission lines and full lines represent transmission lines that are reinforced.</p>
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<p>Aggregate investments in the transmission system of India as of 2050 (scenario-tree node 8) with the possibility to invest in conventional reinforcements and in energy storage. Dashed lines represent existing transmission lines, full lines represent transmission lines that are reinforced, and squares represent energy storage investment in the corresponding bus.</p>
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<p>Generation mix in the year 2050 according to scenario 1 (i.e., scenario-tree node 8), with the availability of storage, in four typical days. Figure (<b>a</b>) reports a typical day within the period January–March, (<b>b</b>) a typical day within April–June, (<b>c</b>) a typical day within July–September, and (<b>d</b>) a typical day within October–December.</p>
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<p>Generation mix in the year 2050 according to scenario 4 (specifically, scenario-tree node 11), with the availability of storage, in four typical days. Figure (<b>a</b>) reports a typical day within the period January–March, (<b>b</b>) a typical day within April–June, (<b>c</b>) a typical day within July–September, and (<b>d</b>) a typical day within October–December.</p>
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<p>Generation mix in the year 2020 (specifically, scenario-tree node 1), with the availability of storage, in four typical days. Figure (<b>a</b>) reports a typical day within the period January–March, (<b>b</b>) a typical day within April–June, (<b>c</b>) a typical day within July–September, and (<b>d</b>) a typical day within October–December.</p>
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<p>Generation mix in the year 2050 (specifically, scenario-tree node 8), without the availability of storage, in four typical days. Figure (<b>a</b>) reports a typical day within the period January–March, (<b>b</b>) a typical day within April–June, (<b>c</b>) a typical day within July–September, and (<b>d</b>) a typical day within October–December.</p>
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<p>Generation mix in the year 2050 (specifically, scenario-tree node 11), without the availability of storage, in four typical days. Figure (<b>a</b>) reports a typical day within the period January–March, (<b>b</b>) a typical day within April–June, (<b>c</b>) a typical day within July–September, and (<b>d</b>) a typical day within October–December.</p>
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<p>Generation mix in region ER according to scenario node 8, with the availability of storage, in four typical days. Figure (<b>a</b>) reports a typical day within the period January–March, (<b>b</b>) a typical day within April–June, (<b>c</b>) a typical day within July–September, and (<b>d</b>) a typical day within October–December.</p>
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<p>Generation mix in region NER according to scenario node 8 with the availability of storage, in four typical days. Figure (<b>a</b>) reports a typical day within the period January–March, (<b>b</b>) a typical day within April–June, (<b>c</b>) a typical day within July–September, and (<b>d</b>) a typical day within October–December.</p>
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<p>Generation mix in region NR according to scenario node 8 with the availability of storage, in four typical days. Figure (<b>a</b>) reports a typical day within the period January–March, (<b>b</b>) a typical day within April–June, (<b>c</b>) a typical day within July–September, and (<b>d</b>) a typical day within October–December.</p>
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<p>Generation mix in region SR according to scenario node 8 with the availability of storage, in four typical days. Figure (<b>a</b>) reports a typical day within the period January–March, (<b>b</b>) a typical day within April–June, (<b>c</b>) a typical day within July–September, and (<b>d</b>) a typical day within October–December.</p>
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<p>Generation mix in region WR according to scenario node 8 with the availability of storage, in four typical days. Figure (<b>a</b>) reports a typical day within the period January–March, (<b>b</b>) a typical day within April–June, (<b>c</b>) a typical day within July–September, and (<b>d</b>) a typical day within October–December.</p>
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<p>Optimal accumulated line investment cost per scenario for the stochastic studies with and without storage.</p>
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<p>Optimal operation cost in the last epoch per scenario for the stochastic studies with and without storage.</p>
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<p>Difference between the optimal accumulated line investment costs for the stochastic studies with and without storage, for every scenario-tree node.</p>
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<p>Difference between the optimal operation costs for the stochastic studies with and without storage, per scenario-tree node.</p>
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<p>Optimal investment cost in line reinforcement for the deterministic and stochastic formulations for each epoch and scenario.</p>
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14 pages, 3893 KiB  
Article
Archimedes Screw Design: An Analytical Model for Rapid Estimation of Archimedes Screw Geometry
by Arash YoosefDoost and William David Lubitz
Energies 2021, 14(22), 7812; https://doi.org/10.3390/en14227812 - 22 Nov 2021
Cited by 11 | Viewed by 10203
Abstract
In designing Archimedes screws, determination of the geometry is among the fundamental questions that may affect many aspects of the Archimedes screw powerplant. Most plants are run-of-river and highly depend on local flow duration curves that vary from river to river. An ability [...] Read more.
In designing Archimedes screws, determination of the geometry is among the fundamental questions that may affect many aspects of the Archimedes screw powerplant. Most plants are run-of-river and highly depend on local flow duration curves that vary from river to river. An ability to rapidly produce realistic estimations for the initial design of a site-specific Archimedes screw plant helps to facilitate and accelerate the optimization of the powerplant design. An analytical method in the form of a single equation was developed to rapidly and easily estimate the Archimedes screw geometry for a specific site. This analytical equation was developed based on the accepted, proved or reported common designs characteristics of Archimedes screws. It was then evaluated by comparison of equation predictions to existing Archimedes screw hydropower plant installations. The evaluation results indicate a high correlation and reasonable relative difference. Use of the equation eliminates or simplifies several design steps and loops and accelerates the development of initial design estimations of Archimedes screw generators dramatically. Moreover, it helps to dramatically reduce one of the most significant burdens of small projects: the nonscalable initial investigation costs and enables rapid estimation of the feasibility of Archimedes screw powerplants at many potential sites. Full article
(This article belongs to the Special Issue Energy Conversion System – Small Hydropower Plants)
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<p>Required parameters to define the geometry of Archimedes screws [<a href="#B18-energies-14-07812" class="html-bibr">18</a>,<a href="#B28-energies-14-07812" class="html-bibr">28</a>].</p>
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<p>Required parameters to define the effective area.</p>
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<p>Comparison of Equation (14) results for <math display="inline"><semantics> <mrow> <mo>δ</mo> <mo>=</mo> <mn>0.5</mn> </mrow> </semantics></math> and different <math display="inline"><semantics> <mo>σ</mo> </semantics></math> values.</p>
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<p>Equation (16) results for the whole range of the dimensionless inlet depth of the screw (Ξ) values in comparison with the currently installed AST designs of <a href="#energies-14-07812-t002" class="html-table">Table 2</a>.</p>
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<p>Comparison of Equation (16) results with Dragomirescu [<a href="#B17-energies-14-07812" class="html-bibr">17</a>] and the other Archimedes screw installations (<a href="#energies-14-07812-t002" class="html-table">Table 2</a>).</p>
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<p>A fast and easy analytical method for designing Archimedes screws.</p>
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16 pages, 5740 KiB  
Article
An Electromagnetic Design of a Fully Superconducting Generator for Wind Application
by Yingzhen Liu, Francesco Grilli, Jiwei Cao, Liyi Li, Chengming Zhang, Mingyi Wang, Fengyu Xu, Jingbo Lin and Mathias Noe
Energies 2021, 14(22), 7811; https://doi.org/10.3390/en14227811 - 22 Nov 2021
Cited by 9 | Viewed by 2791
Abstract
A fully superconducting wind generator employs superconductors in stator and rotor to enable high torque density and low weight, that is, enable an ultra-light electric machine for wind application. However, the level of the AC loss of the stator armature coils is a [...] Read more.
A fully superconducting wind generator employs superconductors in stator and rotor to enable high torque density and low weight, that is, enable an ultra-light electric machine for wind application. However, the level of the AC loss of the stator armature coils is a critical issue, which lacks investigations in the design of the fully superconducting generators. In this paper, an in-house model was developed to analyze the potential of a fully superconducting generator by integrating the electromagnetic design with the AC loss estimation. The electromagnetic model was made through analytical equations, which take into consideration the geometry, the magnetic properties of iron, and the nonlinear E–J constitutive law of superconductors. Since the permeability of iron materials and the critical current of the superconductors depend on the magnetic field, an iteration process was proposed to find their operating points for every electromagnetic design. The AC loss estimation was carried out through finite element software based on the T–A formulation of Maxwell’s equations instead of analytical equations, due to the complexity of magnetic fields, currents and rotation. The results demonstrate that the design approach is viable and efficient, and is therefore useful for the preliminary design of the generator. In addition, it is found that smaller tape width, larger distance between the superconducting coils in the same slot, smaller coil number in one slot and lower working temperature can reduce the AC loss of the stator coils, but the reduction of the AC loss needs careful design to achieve an optimum solution. Full article
(This article belongs to the Special Issue Electrical Machine Design 2021)
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<p>The structure of the generator.</p>
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<p>The general procedure of the design model.</p>
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<p>Illustration of the generator’s geometry.</p>
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<p><span class="html-italic">B</span><span class="html-italic">–H</span> curve of M235-35A from Stiefelmayer-Lasertechnik GmbH at 50 Hz.</p>
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<p>Proposed iteration process of operating-point determination.</p>
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<p>User interface of the design model of fully superconducting generators.</p>
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<p>The active material weight, superconductor length, and AC loss of the stator coils as a function of air-gap diameter and pole pair number: (<b>a</b>) active material weight, (<b>b</b>) superconductor length, (<b>c</b>) stator coil AC loss without end windings, and (<b>d</b>) stator coil AC loss including end windings.</p>
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<p>Design results of the 10 MW fully superconducting wind generators: (<b>a</b>) scatter points of AC loss of stator coils and superconductor length, (<b>b</b>) scatter points of active material weight and superconductor length.</p>
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<p>The instantaneous power dissipation (W/m<sup>3</sup>) reach the maximum in one period and magnetic field (red arrows) with tape width of 4 mm, 2 mm, and 1 mm, from left to right.</p>
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<p>AC loss of stator coils as a function of distance between coils in one slot.</p>
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<p>The instantaneous power dissipation (W/m<sup>3</sup>) reach the maximum in one period and magnetic field (red arrows).</p>
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<p>The instantaneous power dissipation (W/m<sup>3</sup>) reach the maximum in one period and magnetic field (red arrows) with 2 coils and 4 coils in one slot from left to right.</p>
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<p>The AC loss of the stator coils and the equivalent loss at 300 K as a function of temperature: (<b>a</b>) The AC loss of the stator coils at cryogenic temperature, (<b>b</b>) The equivalent AC loss of stator coils at 300 K.</p>
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<p>The instantaneous power dissipation (W/m<sup>3</sup>) reach the maximum in one period at different working temperature.</p>
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31 pages, 4412 KiB  
Article
Machine Learning Techniques in the Energy Consumption of Buildings: A Systematic Literature Review Using Text Mining and Bibliometric Analysis
by Ahmed Abdelaziz, Vitor Santos and Miguel Sales Dias
Energies 2021, 14(22), 7810; https://doi.org/10.3390/en14227810 - 22 Nov 2021
Cited by 17 | Viewed by 4162
Abstract
The high level of energy consumption of buildings is significantly influencing occupant behavior changes towards improved energy efficiency. This paper introduces a systematic literature review with two objectives: to understand the more relevant factors affecting energy consumption of buildings and to find the [...] Read more.
The high level of energy consumption of buildings is significantly influencing occupant behavior changes towards improved energy efficiency. This paper introduces a systematic literature review with two objectives: to understand the more relevant factors affecting energy consumption of buildings and to find the best intelligent computing (IC) methods capable of classifying and predicting energy consumption of different types of buildings. Adopting the PRISMA method, the paper analyzed 822 manuscripts from 2013 to 2020 and focused on 106, based on title and abstract screening and on manuscripts with experiments. A text mining process and a bibliometric map tool (VOS viewer) were adopted to find the most used terms and their relationships, in the energy and IC domains. Our approach shows that the terms “consumption,” “residential,” and “electricity” are the more relevant terms in the energy domain, in terms of the ratio of important terms (TITs), whereas “cluster” is the more commonly used term in the IC domain. The paper also shows that there are strong relations between “Residential Energy Consumption” and “Electricity Consumption,” “Heating” and “Climate. Finally, we checked and analyzed 41 manuscripts in detail, summarized their major contributions, and identified several research gaps that provide hints for further research. Full article
(This article belongs to the Special Issue Green Network Technologies and Renewable Energy Systems)
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<p>Methodology steps.</p>
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<p>Search query.</p>
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<p>PRISMA flow chart.</p>
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<p>Word cloud for intelligent techniques applied to energy.</p>
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<p>Word offset plot for the top 5 words ranked by frequency.</p>
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<p>General steps for obtaining highly relevant terms in our corpus. The numbers represent the computed TITs of the terms. Note: if (TITs) &gt; 0.05, the term is relevant.</p>
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<p>The relationships between the common terms using the bibliometric map.</p>
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<p>Major factors of energy consumption in residential and public buildings.</p>
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<p>Classification techniques that used energy consumption in residential and public buildings.</p>
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<p>Prediction techniques that used energy consumption in residential and public buildings.</p>
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<p>Prediction and classification techniques that used energy consumption in residential and public buildings.</p>
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<p>Evaluation measure of intelligent computing models.</p>
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<p>The most relevant factors that influence the energy consumption of buildings, from our survey.</p>
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<p>Top classification techniques identified in our survey.</p>
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<p>Top prediction techniques identified in our survey.</p>
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15 pages, 3212 KiB  
Article
Synthesis of Mesoporous γ-Alumina Support for Water Composite Sorbents for Low Temperature Sorption Heat Storage
by Manca Ocvirk, Alenka Ristić and Nataša Zabukovec Logar
Energies 2021, 14(22), 7809; https://doi.org/10.3390/en14227809 - 22 Nov 2021
Cited by 10 | Viewed by 2287
Abstract
The efficiency of thermochemical heat storage is crucially determined by the performance of the sorbent used, which includes a high sorption capacity and a low regeneration temperature. The thermochemical salt hydrate– γ-alumina composite sorbents are promising materials for this application but lack systematic [...] Read more.
The efficiency of thermochemical heat storage is crucially determined by the performance of the sorbent used, which includes a high sorption capacity and a low regeneration temperature. The thermochemical salt hydrate– γ-alumina composite sorbents are promising materials for this application but lack systematic study of the influence of γ-alumina structural properties on the final storage performance. In this study, mesoporous γ-Al2O3 supports were prepared by solvothermal and hydrothermal synthesis containing a block copolymer (F-127) surfactant to design thermochemical CaCl2 and LiCl composite water sorbents. Altering the solvent in the synthesis has a significant effect on the structural properties of the γ-Al2O3 mesostructure, which was monitored by powder XRD, nitrogen physisorption, and SEM. Solvothermal synthesis led to a formation of mesoporous γ-Al2O3 with higher specific surface area (213 m2/g) and pore volume (0.542 g/cm3) than hydrothermal synthesis (147 m2/g; 0.414 g/cm3). The highest maximal water sorption capacity (2.87 g/g) and heat storage density (5.17 GJ/m3) was determined for W-46-LiCl containing 15 wt% LiCl for space heating, while the best storage performance in the sense of fast kinetics of sorption, without sorption hysteresis, low desorption temperature, very good cycling stability, and energy storage density of 1.26 GJ/m3 was achieved by W-46-CaCl2. Full article
(This article belongs to the Special Issue New Trends in Thermal Energy Storage: Materials and Technologies)
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<p>Powder XRD patterns of (<b>a</b>) γ-Al<sub>2</sub>O<sub>3</sub> products obtained after thermal treatment at 800 °C and (<b>b</b>) CaCl<sub>2</sub> and LiCl composites with W-46 and ES-47 γ-Al<sub>2</sub>O<sub>3</sub> supports.</p>
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<p>SEM pictures of hydrothermally prepared mesoporous γ-Al<sub>2</sub>O<sub>3</sub> supports: (<b>a</b>) E-37, (<b>b</b>) W-46, and (<b>c</b>) ES-47.</p>
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<p>Surface charge of γ-alumina supports W-46 and ES-47.</p>
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<p>Nitrogen sorption isotherms of (<b>a</b>) γ-alumina supports with corresponding PSDs, (<b>b</b>) W-46 and its composites with corresponding PSDs, (<b>c</b>) ES-47 and its composites with corresponding PSDs.</p>
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<p>TG/DTG curves of the hydrothermally prepared support (<b>a</b>) W-46 and its composites and (<b>b</b>) ES-47 and its composites.</p>
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<p>(<b>a</b>) Water uptake curves and (<b>b</b>) water sorption kinetics curves of the composites with W-46 and ES-47 supports at 35 °C.</p>
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<p>The integral heat of sorption of the composites for space heating storage cycle: sorption temperature of 35 °C, evaporation temperature of 5 °C, desorption temperature of 90 °C, and condensation temperature of 30 °C.</p>
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<p>Cycling stability of 25 cycles of sorption and desorption for W-46-CaCl<sub>2</sub> and W-46-LiCl between 35 °C and 100 °C at 12.5 mbar.</p>
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20 pages, 7309 KiB  
Article
Concept Design of a High-Voltage Electrostatic Sanitizer to Prevent Spread of COVID-19 Coronavirus
by Vahid Behjat, Afshin Rezaei-Zare, Issouf Fofana and Ali Naderian
Energies 2021, 14(22), 7808; https://doi.org/10.3390/en14227808 - 22 Nov 2021
Cited by 7 | Viewed by 3150
Abstract
In addition to public health measures, including social distancing, masking, cleaning, surface disinfection, etc., ventilation and air filtration can be a key component of a multi-pronged risk mitigation strategy against COVID-19 transmission indoors. Electrostatic precipitators (ESP) have already proved their high performance in [...] Read more.
In addition to public health measures, including social distancing, masking, cleaning, surface disinfection, etc., ventilation and air filtration can be a key component of a multi-pronged risk mitigation strategy against COVID-19 transmission indoors. Electrostatic precipitators (ESP) have already proved their high performance in fluid filtration, particularly in industrial applications, to control exhaust gas emissions and remove fine and superfine particles from the flowing gas, using high-voltage electrostatic fields and forces. In this contribution, a high-voltage electrostatic sanitizer (ESS), based on the electrostatic precipitation concept, is proposed as a supportive measure to reduce indoor air infection and prevent the spread of COVID-19 coronavirus. The finite element method (FEM) is used to model and simulate the proposed ESS, taking into account three main mechanisms involving in electrostatic sanitization, namely electrostatic field, airflow, and aerosol charging and tracing, which are mutually coupled to each other and occur simultaneously during the sanitization process. To consider the capability of the designed ESS in capturing superfine particles, functional parameters of the developed ESS, such as air velocity, electric potential, and space charge density, inside the ESS are investigated using the developed FEM model. Simulation results demonstrate the ability of the designed ESS in capturing aerosols containing coronavirus, precipitating suspended viral particles, and trapping them in oppositely charged electrode plates. Full article
(This article belongs to the Special Issue State-of-the-Art Energy Related Technologies in Canada 2020-2021)
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<p>A 2D schematic of the electrostatic precipitator (ESP). The device consists of an air inlet, air outlet, and body housing the discharging electrode and collecting plates.</p>
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<p>Evaporation of a human exhaled droplet in the liquid phase to a non-evaporative aerosol containing viruses.</p>
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<p>Overview of the electric field strength versus applied electric voltage at the discharging electrode.</p>
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<p>Electrical charge production. (<b>a</b>) Ionization of an air atom. (<b>b</b>) Colliding accelerated free electrons to another air atom and bumping another electron from the atom. (<b>c</b>) Ascending production of electrons and positive ions.</p>
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<p>Formation of negative air ions.</p>
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<p>The ESS operation in collecting the particles from the air.</p>
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<p>Particle charging by the field mechanism, and its effect on the electric field lines; (<b>a</b>) unsaturated particle; (<b>b</b>) saturated particle.</p>
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<p>Schematic of a two-stage ESS.</p>
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<p>A simple schematic of ESS with agglomeration system.</p>
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<p>Aerosols electrical agglomeration; (<b>a</b>) agglomeration of small particles together; (<b>b</b>) agglomeration of small particles with the large particle.</p>
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<p>The computational domain of the modeled ESS (the electrodes are not to scale).</p>
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<p>The computational domain boundary conditions.</p>
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<p>Velocity magnitude of the airflow inside the electrostatic sanitizer (ESS).</p>
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<p>Electric potential contours in the ESS.</p>
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<p>Space charge density contours in the ESS.</p>
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<p>Aerosol trajectories through the ESS channel for aerosols with uniform diameters of, respectively, 0.1 µm, 0.3 µm, 0.5 µm, 1 µm, 3 µm, and 5 µm at V = −30 kV.</p>
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27 pages, 6370 KiB  
Article
Turbine Design and Optimization for a Supercritical CO2 Cycle Using a Multifaceted Approach Based on Deep Neural Network
by Muhammad Saeed, Abdallah S. Berrouk, Burhani M. Burhani, Ahmed M. Alatyar and Yasser F. Al Wahedi
Energies 2021, 14(22), 7807; https://doi.org/10.3390/en14227807 - 22 Nov 2021
Cited by 13 | Viewed by 3643
Abstract
Turbine as a key power unit is vital to the novel supercritical carbon dioxide cycle (sCO2-BC). At the same time, the turbine design and optimization process for the sCO2-BC is complicated, and its relevant investigations are still absent in [...] Read more.
Turbine as a key power unit is vital to the novel supercritical carbon dioxide cycle (sCO2-BC). At the same time, the turbine design and optimization process for the sCO2-BC is complicated, and its relevant investigations are still absent in the literature due to the behavior of supercritical fluid in the vicinity of the critical point. In this regard, the current study entails a multifaceted approach for designing and optimizing a radial turbine system for an 8 MW sCO2 power cycle. Initially, a base design of the turbine is calculated utilizing an in-house radial turbine design and analysis code (RTDC), where sharp variations in the properties of CO2 are implemented by coupling the code with NIST’s Refprop. Later, 600 variants of the base geometry of the turbine are constructed by changing the selected turbine design geometric parameters, i.e., shroud ratio (rs4r3), hub ratio (rs4r3), speed ratio (νs) and inlet flow angle (α3) and are investigated numerically through 3D-RANS simulations. The generated CFD data is then used to train a deep neural network (DNN). Finally, the trained DNN model is employed as a fitting function in the multi-objective genetic algorithm (MOGA) to explore the optimized design parameters for the turbine’s rotor geometry. Moreover, the off-design performance of the optimized turbine geometry is computed and reported in the current study. Results suggest that the employed multifaceted approach reduces computational time and resources significantly and is required to completely understand the effects of various turbine design parameters on its performance and sizing. It is found that sCO2-turbine performance parameters are most sensitive to the design parameter speed ratio (νs), followed by inlet flow angle (α3), and are least receptive to shroud ratio (rs4r3). The proposed turbine design methodology based on the machine learning algorithm is effective and substantially reduces the computational cost of the design and optimization phase and can be beneficial to achieve realistic and efficient design to the turbine for sCO2-BC. Full article
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<p>A flow chart of the methodology followed in the current study.</p>
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<p>(<b>a</b>) Dimensions of the turbine, (<b>b</b>) velocity diagram at inlet, (<b>c</b>) velocity diagram at rotor exist, and (<b>d</b>) h-s diagram.</p>
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<p>Radial turbine design flow diagram.</p>
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<p>Nomenclature of a typical airfoil geometry.</p>
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<p>Transformation of the profile to be used for NGV.</p>
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<p>Cmputational geometry and mesh.</p>
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<p>(<b>a</b>) Back propagation algorithm of DNN, (<b>b</b>) Graphic representation of DNN.</p>
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<p>Layout of the Levenberg–Marquardt (LM) optimizing function.</p>
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<p>Flow diagram of MOGA.</p>
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<p>Sensitivity analysis of turbine’s performance parameters to the design parameters.</p>
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<p>Error analysis of the ML algorithm.</p>
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<p>Fitting data from the regressed model and original data.</p>
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<p>Effect of the design parameter on the turbine performance parameters.</p>
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<p>(<b>a</b>) Response surface of turbine’s efficiency to inlet flow angle and speed ratio. (<b>b</b>) Response surface of turbine’s rotor size to inlet flow angle and speed ratio (<b>c</b>) Response surface of turbine’s efficiency to shroud ratio and hub ratio (<b>d</b>) Response surface of turbine’s rotor size to shroud ratio and hub ratio.</p>
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<p>Pareto front computed for rotor’s size and rotor’s efficiency using multi-objective genetic algorithm.</p>
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<p>(<b>a</b>) Pressure contours on the hub and blades surfaces, (<b>b</b>) pressure profile along the nozzle guide vane at 50% span, and (<b>c</b>) pressure profiles at various points.</p>
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<p>(<b>a</b>) Pressure contours on the hub and blades surfaces, (<b>b</b>) pressure profile along the nozzle guide vane at 50% span, and (<b>c</b>) pressure profiles at various points.</p>
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<p>Off-design performance of the optimized turbine geometry.</p>
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31 pages, 1932 KiB  
Review
Maximum Power Point Tracking Techniques for Photovoltaic Panel: A Review and Experimental Applications
by Mohamed Derbeli, Cristian Napole, Oscar Barambones, Jesus Sanchez, Isidro Calvo and Pablo Fernández-Bustamante
Energies 2021, 14(22), 7806; https://doi.org/10.3390/en14227806 - 22 Nov 2021
Cited by 31 | Viewed by 4711
Abstract
This article contains a review of essential control techniques for maximum power point tracking (MPPT) to be applied in photovoltaic (PV) panel systems. These devices are distinguished by their capability to transform solar energy into electricity without emissions. Nevertheless, the efficiency can be [...] Read more.
This article contains a review of essential control techniques for maximum power point tracking (MPPT) to be applied in photovoltaic (PV) panel systems. These devices are distinguished by their capability to transform solar energy into electricity without emissions. Nevertheless, the efficiency can be enhanced provided that a suitable MPPT algorithm is well designed to obtain the maximum performance. From the analyzed MPPT algorithms, four different types were chosen for an experimental evaluation over a commercial PV system linked to a boost converter. As the reference that corresponds to the maximum power is depended on the irradiation and temperature, an artificial neural network (ANN) was used as a reference generator where a high accuracy was achieved based on real data. This was used as a tool for the implementation of sliding mode controller (SMC), fuzzy logic controller (FLC) and model predictive control (MPC). The outcomes allowed different conclusions where each controller has different advantages and disadvantages depending on the various factors related to hardware and software. Full article
(This article belongs to the Special Issue Design and Implementation of Control Schemes for Wave Energy Systems)
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<p>Overview of the analyzed methods in this article.</p>
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<p>Typical curves for a PV system where: (<b>a</b>) is a conventional power-voltage and power-current graph with the MPP highlighted; (<b>b</b>) shows how the power-voltage curves change with different temperature at constant irradiation; (<b>c</b>) displays the change due to partial shadowing in power-voltage curves; (<b>d</b>) exhibits the variation of the power-voltage curves with constant temperature and variable irradiation.</p>
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<p>Principle of the hill climbing algorithms for MPPT.</p>
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<p>Flowchart of P&amp;O algorithm.</p>
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<p>Flowchart of INC algorithm.</p>
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<p>Flowchart of INR algorithm.</p>
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<p>Flowchart of Drift-free algorithm.</p>
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<p>FLC Structure.</p>
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<p>Implementation architecture of the MPPT controller.</p>
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<p>Predicted outputs results.</p>
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<p>Performance analysis of the predicted LRN model.</p>
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<p><math display="inline"><semantics> <mrow> <mi>I</mi> <mi>r</mi> <mi>r</mi> <mi>a</mi> <mi>d</mi> <mi>i</mi> <mi>a</mi> <mi>t</mi> <mi>i</mi> <mi>o</mi> <mi>n</mi> <mo>−</mo> <mi>T</mi> <mi>e</mi> <mi>m</mi> <mi>p</mi> <mi>e</mi> <mi>r</mi> <mi>a</mi> <mi>t</mi> <mi>u</mi> <mi>r</mi> <mi>e</mi> <mo>−</mo> <mi>C</mi> <mi>u</mi> <mi>r</mi> <mi>r</mi> <mi>e</mi> <mi>n</mi> <mi>t</mi> </mrow> </semantics></math> characteristic surface of the MPP.</p>
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<p>PV panel characteristic curves: (<b>a</b>) voltage-current; (<b>b</b>) voltage–power.</p>
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<p>MPPT based on P&amp;O: (<b>a</b>) Irradiation (W/m<sup>2</sup>); (<b>b</b>) Temperature (<math display="inline"><semantics> <msup> <mrow/> <mo>∘</mo> </msup> </semantics></math>C); (<b>c</b>) Load resistance (<math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>I</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> </mrow> </semantics></math>); (<b>d</b>) Duty cycle; (<b>e</b>) PV current.</p>
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<p>MPPT based on P&amp;O: (<b>a</b>) PV voltage; (<b>b</b>) PV power; (<b>c</b>) Boost converter output current; (<b>d</b>) Boost converter output voltage; (<b>e</b>) Boost converter output power.</p>
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<p>MPPT based on RNN and SMC: (<b>a</b>) Irradiation (W/m<sup>2</sup>); (<b>b</b>) Temperature (<math display="inline"><semantics> <msup> <mrow/> <mo>∘</mo> </msup> </semantics></math>C); (<b>c</b>) PV current; (<b>d</b>) PV voltage; (<b>e</b>) PV power.</p>
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<p>MPPT based on RNN and SMC: (<b>a</b>) Load Resistance (<math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>I</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> </mrow> </semantics></math>); (<b>b</b>) PV current; (<b>c</b>) PV voltage; (<b>d</b>) PV power.</p>
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<p>MPPT based on RNN and SMC: (<b>a</b>) Duty cycle; (<b>b</b>) Error; (<b>c</b>) Boost converter output current (<math display="inline"><semantics> <msub> <mi>I</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> </semantics></math>); (<b>d</b>) Boost converter output voltage (<math display="inline"><semantics> <msub> <mi>V</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> </semantics></math>).</p>
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<p>MPPT based on RNN and FLC: (<b>a</b>) Irradiation (W/m<sup>2</sup>); (<b>b</b>) Temperature (<math display="inline"><semantics> <msup> <mrow/> <mo>∘</mo> </msup> </semantics></math>C); (<b>c</b>) PV current; (<b>d</b>) PV voltage; (<b>e</b>) PV power.</p>
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<p>MPPT based on RNN and FLC: (<b>a</b>) Load Resistance (<math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>I</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> </mrow> </semantics></math>); (<b>b</b>) PV current; (<b>c</b>) PV voltage; (<b>d</b>) PV power.</p>
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<p>MPPT based on RNN and FLC: (<b>a</b>) Duty cycle; (<b>b</b>) Error; (<b>c</b>) Boost converter output current (<math display="inline"><semantics> <msub> <mi>I</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> </semantics></math>); (<b>d</b>) Boost converter output voltage (<math display="inline"><semantics> <msub> <mi>V</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> </semantics></math>).</p>
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<p>MPPT based on RNN and MPC: (<b>a</b>) Irradiation (W/m<sup>2</sup>); (<b>b</b>) Temperature (<math display="inline"><semantics> <msup> <mrow/> <mo>∘</mo> </msup> </semantics></math>C); (<b>c</b>) PV current; (<b>d</b>) PV voltage; (<b>e</b>) PV power.</p>
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<p>MPPT based on RNN and MPC: (<b>a</b>) Load Resistance (<math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>I</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> </mrow> </semantics></math>); (<b>b</b>) PV current; (<b>c</b>) PV voltage; (<b>d</b>) PV power.</p>
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<p>MPPT based on RNN and MPC: (<b>a</b>) Duty cycle; (<b>b</b>) Error; (<b>c</b>) Boost converter output current (<math display="inline"><semantics> <msub> <mi>I</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> </semantics></math>); (<b>d</b>) Boost converter output voltage (<math display="inline"><semantics> <msub> <mi>V</mi> <mrow> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> </semantics></math>).</p>
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27 pages, 7551 KiB  
Review
Losses in Efficiency Maps of Electric Vehicles: An Overview
by Emad Roshandel, Amin Mahmoudi, Solmaz Kahourzade, Amirmehdi Yazdani and GM Shafiullah
Energies 2021, 14(22), 7805; https://doi.org/10.3390/en14227805 - 22 Nov 2021
Cited by 20 | Viewed by 7801
Abstract
In some applications such as electric vehicles, electric motors should operate in a wide torque and speed ranges. An efficiency map is the contour plot of the maximum efficiency of an electric machine in torque-speed plane. It is used to provide an overview [...] Read more.
In some applications such as electric vehicles, electric motors should operate in a wide torque and speed ranges. An efficiency map is the contour plot of the maximum efficiency of an electric machine in torque-speed plane. It is used to provide an overview on the performance of an electric machine when operates in different operating points. The electric machine losses in different torque and speed operating points play a prominent role in the efficiency of the machines. In this paper, an overview about the change of various loss components in torque-speed envelope of the electric machines is rendered to show the role and significance of each loss component in a wide range of torque and speeds. The research gaps and future research subjects based on the conducted review are reported. The role and possibility of the utilization of the computational intelligence-based modeling of the losses in improvement of the loss estimation is discussed. Full article
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<p>The torque-speed profiles of two driving cycles introduced for the optimization studies in different literature. The data of this plot has been collected from [<a href="#B23-energies-14-07805" class="html-bibr">23</a>]. (<b>a</b>) Highway Fuel Economy Test (HWFET), (<b>b</b>) Urban Dynamometer Driving Schedule (UDDS), (<b>c</b>) Induction motor efficiency countor and the UDDS driving cycle operating points in the torque-speed envelope.</p>
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<p>The loss and efficiency maps of a sample 50 kW IPMSM subject to operation at its maximum efficiency in each operating point. The studied IPMSM is designed for EV application. The data of this plot has been collected from [<a href="#B20-energies-14-07805" class="html-bibr">20</a>,<a href="#B24-energies-14-07805" class="html-bibr">24</a>]. (<b>a</b>) Total loss map of an IPMSM. (<b>b</b>) Efficiency map of an IPMSM.</p>
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<p>The various loss components of an electric machine used in propulsion system of EVs.</p>
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<p>The statistic of documented research focused on the impact of various types of losses on EM of electrical machines during the last three decades (1992 to 2021).</p>
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<p>Current and ohmic loss maps of a 50 kW IPMSM for operation over a wide torque speed range [<a href="#B20-energies-14-07805" class="html-bibr">20</a>,<a href="#B24-energies-14-07805" class="html-bibr">24</a>] and the contour plot of ohmic losses of a 60 kW induction machine (rotor bar and stator ohmic loss) [<a href="#B21-energies-14-07805" class="html-bibr">21</a>]. These plots have been provided based on the collected data from [<a href="#B20-energies-14-07805" class="html-bibr">20</a>,<a href="#B21-energies-14-07805" class="html-bibr">21</a>,<a href="#B24-energies-14-07805" class="html-bibr">24</a>]. (<b>a</b>) current map in the torque speed plane. (<b>b</b>) ohmic loss map in the torque speed plane. (<b>c</b>) IM rotor bar loss. (<b>d</b>) IM stator loss.</p>
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<p>Voltage and core loss maps of a 50 kW IPMSM and 45 kW SPMSM for operation over a wide torque speed range. These plots have been provided based on the collected data from [<a href="#B20-energies-14-07805" class="html-bibr">20</a>,<a href="#B24-energies-14-07805" class="html-bibr">24</a>]. (<b>a</b>) voltage map in the torque speed plane for the IPMSM. (<b>b</b>) core loss map in the torque speed plane for the IPMSM. (<b>c</b>) voltage map in the torque speed plane for the SPMSM. (<b>d</b>) core loss map in the torque speed plane for the SPMSM.</p>
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<p>The measured copper, core and drive (converter) losses per mile for three different machine/gearbox combinations in 4 drive cycles and constant speed of 65 mph operation reported in [<a href="#B89-energies-14-07805" class="html-bibr">89</a>].</p>
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<p>Non-segmented PM power loss in different operating speeds and comparison of the accuracy of the 2D and 3D FEA results for a 14.7 kW 4000 rpm 16 pole machine. The data to plot this figure was collected from [<a href="#B130-energies-14-07805" class="html-bibr">130</a>].</p>
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<p>The mechanical loss variation in a 14.9 kW axial-flux PM motor against speed in two different temperature machines. The data to plot this figure was collected from [<a href="#B141-energies-14-07805" class="html-bibr">141</a>].</p>
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<p>The graphical illustration of three widely used transmission systems in EVs [<a href="#B142-energies-14-07805" class="html-bibr">142</a>]. (<b>a</b>) single-speed transmission. (<b>b</b>) two-speed transmission. (<b>c</b>) CVT transmission.</p>
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<p>The variation of the losses and efficiency in CVT [<a href="#B154-energies-14-07805" class="html-bibr">154</a>].</p>
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<p>The conventional methods for the extraction of the motor’s efficiency experimentally based on IEEE and IEC standards. (<b>a</b>) the procedure of the calculation of the efficiency at a certain load and speed for PMS motors based on IEEE standard. (<b>b</b>) the procedure of the calculation of the efficiency at a certain load and speed for PMS and DC motors based on IEC standard. (<b>c</b>) the procedure of the calculation of the efficiency at a certain load and speed for the induction motors based on IEEE standard. (<b>d</b>) the procedure of the calculation of the efficiency at a certain load and speed for the induction motors based on IEC standard.</p>
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<p>The placement of power analyzers and dynamo meters to measure each loss component of the EV propulsion system.</p>
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19 pages, 6136 KiB  
Article
CFD Analysis of Elements of an Adsorption Chiller with Desalination Function
by Karol Sztekler, Tomasz Siwek, Wojciech Kalawa, Lukasz Lis, Lukasz Mika, Ewelina Radomska and Wojciech Nowak
Energies 2021, 14(22), 7804; https://doi.org/10.3390/en14227804 - 22 Nov 2021
Cited by 5 | Viewed by 2254
Abstract
This paper presents the results of numerical tests on the elements of an adsorption chiller that comprises a sorption chamber with a bed, a condenser, and an evaporator. The simulation is based on the data and geometry of a prototype refrigeration appliance. The [...] Read more.
This paper presents the results of numerical tests on the elements of an adsorption chiller that comprises a sorption chamber with a bed, a condenser, and an evaporator. The simulation is based on the data and geometry of a prototype refrigeration appliance. The simulation of this problem is unique and has not yet been performed, and so far, no simulation of the phenomena occurring in the systems on a real scale has been carried out. The presented results are part of the research covering the entire spectrum of designing an adsorption chiller. The full process of numerical modeling of thermal and flow phenomena taking place in the abovementioned components is presented. The computational mesh sensitivity analysis combined in the k-ε turbulence model was performed. To verify and validate the numerical results obtained, they were compared with the results of tests carried out on a laboratory stand at the AGH Center of Energy. The results of numerical calculations are in good agreement with the results of the experimental tests. The maximum deviation between the pressure obtained experimentally and by simulations is 1.8%, while for temperatures this deviation is no more than 0.5%. The results allow the identification of problems and their sources, which allows for future structural modifications to optimize the operation of the device. Full article
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<p>Scheme of the adsorption chiller with desalination test bench at the Center of Energy AGH [<a href="#B6-energies-14-07804" class="html-bibr">6</a>,<a href="#B29-energies-14-07804" class="html-bibr">29</a>]. 1—condenser; 2—distillate tank; 3—adsorbent bed; 4—brine tank; 5—evaporator; 6—deaerator; TT01—temperature in the evaporator; TT04—hot water inlet temperature; TT05—hot water outlet temperature; TT06—chilled water inlet temperature; TT07—chilled water outlet temperature; TT11—temperature in Bed 1; TT12—temperature in Bed 2; TT13—temperature in Bed 3; TT18—temperature in the condenser; PT04—pressure in the evaporator; PT07—pressure in Bed 1; PT06—pressure in Bed 2; PT05—pressure in Bed 3; PT10—pressure in the condenser; FT01—hot water flow; FT03—chilled water flow.</p>
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<p>Temperature changes over time. 1—heating water inlet to the beds; 2—heating water outlet from the beds; 3—chilled water outlet from the evaporator; 4—cooling water outlet from the condenser; 5—heat exchanger in the first bed; 6—heat exchanger in the second bed; 7—free space of the first bed; 8—free space of the second bed; 9—cooling water outlet from the beds; 10—free space of the evaporator; 11—free space of the condenser.</p>
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<p>Pressure changes over time.</p>
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<p>Destructive effect of the cumulative factor on the deposit.</p>
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<p>Visualization of the arrangement of cross-sections in the sorption chamber.</p>
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<p>Visualization of the arrangement of cross-sections in the evaporator.</p>
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<p>Visualization of the arrangement of cross-sections in the condenser.</p>
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<p>Cross-Section K1 for the sorption: (<b>a</b>) temperature distribution; (<b>b</b>) pressure distribution; (<b>c</b>) velocity distribution.</p>
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<p>Cross-Section K1 for the sorption: (<b>a</b>) temperature distribution; (<b>b</b>) pressure distribution; (<b>c</b>) velocity distribution.</p>
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<p>Pressure distribution in Section K1 for the desorption.</p>
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<p>Velocity field distribution in Section K2 for the desorption.</p>
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<p>Temperature distribution in: (<b>a</b>) Section P1; (<b>b</b>) Section P2.</p>
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<p>Velocity field distribution: (<b>a</b>) Cross-Section P1; (<b>b</b>) Cross-Section P2.</p>
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<p>Distribution of liquid water content for Cross-Section P2 on the local scale.</p>
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<p>Temperature distribution for: (<b>a</b>) Cross-Section S1; (<b>b</b>) Cross-Section S3.</p>
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<p>Distribution of the velocity field for Cross-Section S2.</p>
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<p>Comparison of the results of simulation and experimental studies—pressure over time for the sorption process.</p>
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<p>Comparison of the results of simulation and experimental studies—pressure over time for the desorption process.</p>
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<p>Comparison of the results of simulation and experimental studies—temperature over time for the sorption process.</p>
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<p>Comparison of the results of simulation and experimental studies—temperature over time for the desorption process.</p>
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26 pages, 3346 KiB  
Article
State Transitions Logical Design for Hybrid Energy Generation with Renewable Energy Sources in LNG Ship
by Michael E. Stamatakis and Maria G. Ioannides
Energies 2021, 14(22), 7803; https://doi.org/10.3390/en14227803 - 22 Nov 2021
Cited by 11 | Viewed by 2633
Abstract
In terms of energy generation and consumption, ships are autonomous and isolated power systems with energy requirements related to the type and kind of power demands and according to ship types: passenger ships, or commercial ships. Power supply on ships is traditionally based [...] Read more.
In terms of energy generation and consumption, ships are autonomous and isolated power systems with energy requirements related to the type and kind of power demands and according to ship types: passenger ships, or commercial ships. Power supply on ships is traditionally based on engines thermal generators, which use fossil fuels, diesel, or natural gas. Due to the continuous operation of thermal generators in ships, this ends up increasing polluting gas emissions for the environment, mainly CO2. A combination of Renewable Energy Sources (RES) with traditional ship thermal engines can reduce CO2 emissions, resulting in a ‘greener’ interaction between ships and the environment. Due to the varying power needs for ship operation, considering the varying nature of load demands during long distance travels and during harbor entry, the use of RES must be evaluated. This paper presents a new control method to balance LNG ship load demands and power generation from RES, based on an accurate model and solution in real conditions. The Energy Management System (EMS) is designed and implemented in a Finite State Machine structure using the logical design of state transitions. The results prove that the reduction of consumption of fossil fuels is feasible, and, if this is combined with RES, it reduces CO2 emissions. Full article
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<p>The ship energy control system with EMS, generating units and electric loads.</p>
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<p>Estimated Ship Load Demands on a 3 h basis.</p>
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<p>Typical sun radiation during 24 h.</p>
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<p>Wind Velocity during 24 h.</p>
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<p>Flow Chart of States and transitions (1 of 3).</p>
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<p>Flow Chart of States and transitions (2 of 3).</p>
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<p>Flow Chart of States and transitions (3 of 3).</p>
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<p>Typical Nano-crystalline PV panel.</p>
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<p>Vertical Axis Wind Turbine for offshore applications.</p>
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<p>Ship power generation and consumption during Scenario 1. Load demand (blue), DG1 (purple), LNG (light blue), DG2 (light green). PVs (deactivated), WECs (deactivated), Batteries (off).</p>
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<p>Ship power generation and consumption during Scenario 2. Load Demand (blue), DG1 (purple), LNG (light blue), DG2 (deactivated), PVs (orange), WECs (yellow).</p>
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<p>Ship power generation and consumption during Scenario 3. Load Demands (blue), DG1 (purple), LNG (light blue), DG2 (deactivated), PVs (deactivated), WECs (deactivated).</p>
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<p>(<b>a</b>) Ship power generation and consumption during Scenario 4. (<b>b</b>) EMS Control States. Load Demands (blue), DG1 (purple), LNG (light blue), DG2 (deactivated), PVs (brown), WECs (yellow).</p>
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16 pages, 5985 KiB  
Article
Direct Fuzzy CMAC Sliding Mode Trajectory Tracking for Biaxial Position System
by Wei-Lung Mao, Yu-Ying Chiu, Bing-Hong Lin, Wei-Cheng Sun and Jian-Fu Tang
Energies 2021, 14(22), 7802; https://doi.org/10.3390/en14227802 - 22 Nov 2021
Cited by 1 | Viewed by 1695
Abstract
High-precision trajectory control is considered as an important factor in the performance of industrial two-axis contour motion systems. This research presents an adaptive direct fuzzy cerebellar model articulation controller (CMAC) sliding mode control (DFCMACSMC) for the precise control of the industrial XY-axis motion [...] Read more.
High-precision trajectory control is considered as an important factor in the performance of industrial two-axis contour motion systems. This research presents an adaptive direct fuzzy cerebellar model articulation controller (CMAC) sliding mode control (DFCMACSMC) for the precise control of the industrial XY-axis motion system. The FCMAC was utilized to approximate an ideal controller, and the weights of FCMAC were on-line tuned by the derived adaptive law based on the Lyapunov criterion. With this derivation in mind, the asymptotic stability of the developed motion system could be guaranteed. The two-axis stage system was experimentally investigated using four contours, namely, circle, bowknot, heart, and star reference contours. The experimental results indicate that the proposed DFCMACSMC method achieved the improved tracking capability, and so reveal that the DFCMACSMC scheme outperformed other schemes of the model uncertainties and cross-coupling interference. Full article
(This article belongs to the Special Issue New Advances in Permanent Magnet Electrical Machines)
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<p>(<b>a</b>) Photographs of the two-axis motion stage, and (<b>b</b>) the servo drive system.</p>
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<p>The basic structure of CMAC.</p>
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<p>The mapping structure of the two-dimensional CMAC.</p>
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<p>The mapping structure of the two−dimensional FCMAC with the Gaussian function.</p>
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<p>The overall scheme of the DFCMAC sliding mode control system.</p>
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<p>The reference contours, (<b>a</b>) the circle contour, (<b>b</b>) the bowknot contour, (<b>c</b>) the heart contour, and (<b>d</b>) the star contour (unit: <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">μ</mi> <mi mathvariant="normal">m</mi> </mrow> </semantics></math>).</p>
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<p>The path trajectory of the simulations. (<b>a</b>) The X−axis tracking response, (<b>b</b>) the Y−axis tracking response, (<b>c</b>) the circle path response.</p>
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<p>The path trajectory of the simulations. (<b>a</b>) The X−axis tracking response, (<b>b</b>) the Y−axis tracking response, (<b>c</b>) the bowknot path response.</p>
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<p>The path trajectory of the simulations. (<b>a</b>) The X−axis tracking response, (<b>b</b>) the Y−axis tracking response, (<b>c</b>) the heart path response.</p>
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<p>The path trajectory of the simulations. (<b>a</b>) The X−axis tracking response, (<b>b</b>) the Y−axis tracking response, (<b>c</b>) the star path response.</p>
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<p>The path trajectory of the experiments. (<b>a</b>) The X-axis tracking response, (<b>b</b>) the Y-axis tracking response, (<b>c</b>) the circle path response.</p>
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<p>The path trajectory of the experiments. (<b>a</b>) The X−axis tracking response, (<b>b</b>) the Y−axis tracking response, (<b>c</b>) the bowknot path response.</p>
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<p>The path trajectory of the experiments. (<b>a</b>) The X−axis tracking response, (<b>b</b>) the Y−axis tracking response, (<b>c</b>) the heart path response.</p>
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<p>The path trajectory of the experiments. (<b>a</b>) The X−axis tracking response, (<b>b</b>) the Y−axis tracking response, (<b>c</b>) the star path response.</p>
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21 pages, 6001 KiB  
Article
Frequency Regulation System: A Deep Learning Identification, Type-3 Fuzzy Control and LMI Stability Analysis
by Ayman A. Aly, Bassem F. Felemban, Ardashir Mohammadzadeh, Oscar Castillo and Andrzej Bartoszewicz
Energies 2021, 14(22), 7801; https://doi.org/10.3390/en14227801 - 22 Nov 2021
Cited by 18 | Viewed by 2212
Abstract
In this paper, the problem of frequency regulation in the multi-area power systems with demand response, energy storage system (ESS) and renewable energy generators is studied. Dissimilarly to most studies in this field, the dynamics of all units in all areas are considered [...] Read more.
In this paper, the problem of frequency regulation in the multi-area power systems with demand response, energy storage system (ESS) and renewable energy generators is studied. Dissimilarly to most studies in this field, the dynamics of all units in all areas are considered to be unknown. Furthermore time-varying solar radiation, wind speed dynamics, multiple load changes, demand response (DR), and ESS are considered. A novel dynamic fractional-order model based on restricted Boltzmann machine (RBM) and deep learning contrastive divergence (CD) algorithm is presented for online identification. The controller is designed by the dynamic estimated model, error feedback controller and interval type-3 fuzzy logic compensator (IT3-FLC). The gains of error feedback controller and tuning rules of the estimated dynamic model are extracted through the fractional-order stability analysis by the linear matrix inequality (LMI) approach. The superiority of a schemed controller in contrast to the type-1 and type-2 FLCs is demonstrated in various conditions, such as time-varying wind speed, solar radiation, multiple load changes, and perturbed dynamics. Full article
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Graphical abstract

Graphical abstract
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<p>The suggested control block diagram.</p>
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<p>The general diagram of case study.</p>
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<p>The suggested control block diagram.</p>
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<p>The suggested fractional-order dynamic RBM-MLP block diagram.</p>
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<p>The suggested interval type-3 FLS block diagram.</p>
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<p>Type-3 MF.</p>
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<p>Example 1: Scenario 1: Frequency regulation performance in the presence load changes.</p>
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<p>Example 1: Scenario 2: Frequency regulation performance in the presence of multiple load changes (<math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <msub> <mi>p</mi> <mi>L</mi> </msub> </mrow> </semantics></math>).</p>
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<p>Example 1: Scenario 3: Frequency regulation in the presence of multiple load changes (<math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <msub> <mi>p</mi> <mi>L</mi> </msub> </mrow> </semantics></math>), and all parameters are changed.</p>
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<p>Example 1: Scenario 4: Frequency regulation performance in the presence of multiple load changes (<math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">Δ</mi> <msub> <mi>p</mi> <mi>L</mi> </msub> </mrow> </semantics></math>) and time-varying solar radiation and mechanical power of wind turbine.</p>
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<p>Example 2: The trajectory of load changes.</p>
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<p>Example 2: Scenario 1: The trajectory of frequency regulation for all three areas.</p>
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<p>Example 2: Scenario 2: The trajectory of frequency regulation for all three areas.</p>
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<p>Example 2: Scenario 2: The trajectory of wind speed.</p>
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<p>Example 2: Scenario 3: The trajectory of frequency regulation for all three areas.</p>
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17 pages, 3717 KiB  
Article
Performance-Based Navigation Flight Path Analysis Using Fast-Time Simulation
by Daniel A. Pamplona, Alexandre G. de Barros and Claudio J. P. Alves
Energies 2021, 14(22), 7800; https://doi.org/10.3390/en14227800 - 22 Nov 2021
Cited by 6 | Viewed by 4463
Abstract
The growing demand for air transportation has led to an increase in worldwide air traffic inefficiency due to capacity constraints. The impacts associated with this situation can be reduced through operational changes. To better handle the problem, the Single European Sky ATM Research [...] Read more.
The growing demand for air transportation has led to an increase in worldwide air traffic inefficiency due to capacity constraints. The impacts associated with this situation can be reduced through operational changes. To better handle the problem, the Single European Sky ATM Research (SESAR) and the Next Generation Air Transportation System (NextGen) program suggest Performance-Based Navigation (PBN) as a solution. The Area Navigation (RNAV) and Required Navigation Performance (RNP) approaches belong to the group of PBN procedures. These procedures allow for a more efficient use of airspace by reducing route distances, fuel consumption and perceived aircraft noise. This article quantifies the benefits of PBN systems for two indicator parameters—fuel burn and flight time—and compares PBN systems to conventional instrument navigation procedures. The case studies use five airports in Brazil. The results of this analysis show that the benefits of the PBN approach vary with aircraft type and individual route characteristics. Full article
(This article belongs to the Special Issue Air Transport Systems Optimization)
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<p>Flight phases and associated procedures. Source: The authors.</p>
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<p>Longitudinal, lateral, and vertical separation. Source: The authors.</p>
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<p>Flow chart for building TAAM scenarios. Source: The authors.</p>
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<p>Case 1 route percentage improvement by route. (<b>a</b>) SBGL-SBGR; (<b>b</b>) SBGL-SBKP; (<b>c</b>) SBGL-SBSP; (<b>d</b>) SBGR-SBGL; (<b>e</b>) SBGR-SBRJ; (<b>f</b>) SBKP-SBGL; (<b>g</b>) SBKP-SBRJ; (<b>h</b>) SBRJ-SBGR; (<b>i</b>) SBRJ-SBKP; (<b>j</b>) SBRJ-SBSP; (<b>k</b>) SBSP-SBGL; (<b>l</b>) SBSP-SBRJ.</p>
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<p>Case 1 route percentage improvement by aircraft. (<b>a</b>) A319; (<b>b</b>) A320; (<b>c</b>) A321; (<b>d</b>) B737-300; (<b>e</b>) B737-700; (<b>f</b>) B737-800; (<b>g</b>) F100; (<b>h</b>) E145; (<b>i</b>) E190; (<b>j</b>) AT72.</p>
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<p>Case 1 approach; percentage improvement by airport. (<b>a</b>) SBGL; (<b>b</b>) SBGR; (<b>c</b>) SBKP; (<b>d</b>) SBRJ; (<b>e</b>) SBSP.</p>
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<p>Case 1 approach; percentage improvement by aircraft. (<b>a</b>) A319; (<b>b</b>) A320; (<b>c</b>) A321; (<b>d</b>) B737-300; (<b>e</b>) B737-700; (<b>f</b>) B737-800; (<b>g</b>) F100; (<b>h</b>) E145; (<b>i</b>) E190; (<b>j</b>) AT72.</p>
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<p>Gain variability for fuel consumption for each route due to air traffic interactions. (<b>a</b>) Fuel consumption; (<b>b</b>) Flight time.</p>
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<p>Heat map of the traffic density in Brazilian air space and the studied area air traffic structure. Source: The authors.</p>
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<p>Average daily savings in dollars by route. (<b>a</b>) SBGL-SBGR; (<b>b</b>) SBGL-SBKP; (<b>c</b>) SBGL-SBSP; (<b>d</b>) SBGR-SBGL; (<b>e</b>) SBGR-SBRJ; (<b>f</b>) SBKP-SBGL; (<b>g</b>) SBKP-SBRJ; (<b>h</b>) SBRJ-SBGR; (<b>i</b>) SBRJ-SBKP; (<b>j</b>) SBRJ-SBSP; (<b>k</b>) SBSP-SBGL; (<b>l</b>) SBSP-SBRJ.</p>
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2 pages, 196 KiB  
Editorial
High-Capacity Cells and Batteries for Electric Vehicles
by Lluc Canals Casals, Marcel Macarulla and Alberto Gómez-Núñez
Energies 2021, 14(22), 7799; https://doi.org/10.3390/en14227799 - 22 Nov 2021
Cited by 4 | Viewed by 1635
Abstract
The automotive sector is rapidly accelerating its transformation towards electric mobility, and electric vehicle (EV) sales have been increasing year after year since the beginning of the decade [...] Full article
(This article belongs to the Special Issue High-Capacity Cells and Batteries for Electric Vehicles)
16 pages, 5244 KiB  
Article
Implementation and Control of Six-Phase Induction Motor Driven by a Three-Phase Supply
by Mohamed I. Abdelwanis, Essam M. Rashad, Ibrahim B. M. Taha and Fathalla F. Selim
Energies 2021, 14(22), 7798; https://doi.org/10.3390/en14227798 - 22 Nov 2021
Cited by 10 | Viewed by 5204
Abstract
This paper is interested in implementing and controlling a modified six-phase induction motor (MSPIM) when fed from a three-phase supply either via an inverter or with a direct grid connection loaded by a centrifugal pump. The main aims of using the MSPIM are [...] Read more.
This paper is interested in implementing and controlling a modified six-phase induction motor (MSPIM) when fed from a three-phase supply either via an inverter or with a direct grid connection loaded by a centrifugal pump. The main aims of using the MSPIM are to enhance motor reliability and reduce torque pulsation. A three-to-six phase transformer has been designed, implemented, and employed to enable the SPIM to be driven from a three-phase supply. It is preferable to use the three-to-six phase transformers integrated with three-phase inverter on using the six-phase inverter to generate lower values of harmonics and lower steady-state error of speed and reduce the starting current and because also it isolates the primary circuit from the secondary, and the cost will be lower compared to the design of a special six-phase inverter. Dynamic models of SPIM, three-to-six phase transformer, and three-phase variable speed drive are derived. Then, a scalar (V/F) closed-loop control of SPIM is employed, and the results are discussed. Fine-tuning of PID controllers is used to keep the motor speed tracking the reference value. A low pass filter is connected to reduce the ripple of voltage and current waveforms. An experimental setup has been built and implemented to check the possibility of controlling SPIM by a variable speed drive system fed from a three-to-six phase transformer. It is found that the proposed method can be effectively used to drive the SPIM from a three-phase supply. Full article
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<p>Three-to-six phase transformer connection.</p>
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<p>Phasor diagram of three and six-phase voltages.</p>
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<p>Three-phase inverter.(<b>a</b>) Primary three-phase inverter, (<b>b</b>) circuit of the three-phase inverter.</p>
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<p>The PID schematic diagram of modified six-phase induction motor control.</p>
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<p>Block diagram of the experimental setup located in the Electrical Power Laboratory in the Faculty of Engineering, Electrical Engineering Department, Kafrelshiekh University.</p>
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<p>Speed–time characteristics: (<b>a</b>) with 3-phase inverter and transformer, (<b>b</b>) with 6-phase inverter.</p>
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<p>Pump torque–time characteristics with PID.</p>
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<p>THD in voltage–time characteristics: (<b>a</b>) with 3-phase inverter and transformer(<b>b</b>) with 6-phase inverter.</p>
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<p>THD in current–time characteristics: (<b>a</b>) 3-phase inverter and transformer, (<b>b</b>) with 6-phase inverter.</p>
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<p>Stator voltage–time response: (<b>a</b>) with 3-phase inverter and transformer, (<b>b</b>) with 6-phase inverter.</p>
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<p>Stator phase current–time response: (<b>a</b>) with 3-phase inverter and transformer, (<b>b</b>) with 6-phase inverter.</p>
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<p>Torque–slip characteristics of the adapted six-phase induction motor.</p>
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<p>Measured motor voltage against frequency relationship.</p>
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<p>Measured input current against frequency relationship.</p>
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<p>Measured rotor speed against frequency relationship.</p>
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<p>Torque–speed characteristics of six-phase motor (− simulation, x experimental).</p>
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<p>Current–speed characteristics of six-phase motor (− simulation, x experimental).</p>
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