Search Results (19,081)

Decision makers (DMs) are often viewed as autonomous in the majority of multicriteria group decision making (MCGDM) situations, and their psychological behaviors are seldom taken into account. Once more, we are unable to prevent both positive and negative flows of varying alternative preferences due to the nature of attributes or criteria in complicated decision-making problems. However, DMs’ perspectives are likely to affect one another in complicated MCGDM issues, and they frequently use subjective limited rationality while making decisions. The multicriteria quantum decision theory-based group decision making integrating the TODIM-PROMETHEE II strategy under linguistic Z-numbers (LZNs) is designed to overcome the aforementioned problems. In our established technique, the PROMETHEE II controls the positive and negative flows of distinct alternative preferences, the TODIM method manages the experts’ personal regrets over a criterion, and the quantum probability theory (QPT) addresses human cognition and behavior. Because LZNs can convey linguistic judgment and trustworthiness, we provide expert LZNs for their viewpoints in this work. We determine the criterion weights for each expert after first obtaining their respective expert weights. Second, to represent the limited rational behaviors of the DMs, the TODIM-PROMETHEE II approach is introduced. It is employed to determine each alternative’s dominance in both positive and negative flows. Third, a framework for quantum possibilistic aggregation is developed to investigate the effects of interference between the views of DMs. The views of DMs are seen in this procedure as synchronously occurring wave functions that affect the overall outcome by interfering with one another. The model’s efficacy is then assessed by a selection of renewable energy case studies, sensitive analysis, comparative analysis, and debate. Full article

The transportation sector is a major contributor to carbon dioxide (CO₂) emissions in Canada, making the accurate forecasting of CO₂ emissions critical as part of the global push toward carbon neutrality. This study employs interpretable machine learning techniques to predict vehicle CO₂ emissions in Canada from 1995 to 2022. Algorithms including K-Nearest Neighbors, Support Vector Regression, Gradient Boosting Machine, Decision Tree, Random Forest, and Lasso Regression were utilized. The Gradient Boosting Machine delivered the best performance, achieving the highest R-squared value (0.9973) and the lowest Root Mean Squared Error (3.3633). To enhance the model interpretability, the SHapley Additive exPlanations (SHAP) and Accumulated Local Effects methods were used to identify key contributing factors, including fuel consumption (city/highway), ethanol (E85), and diesel. These findings provide critical insights for policymakers, underscoring the need for promoting renewable energy, tightening fuel emission standards, and decoupling carbon emissions from economic growth to foster sustainable development. This study contributes to broader discussions on achieving carbon neutrality and the necessary transformations within the transportation sector. Full article

Electricity is one of the most widely used energy sources. The climate crisis, public pressure to invest in renewable and low-carbon energy sources, and the reduction in industrial electricity consumption caused by the COVID-19 pandemic have a significant impact on the energy sector. In addition, military action in Europe is affecting energy generation capacity and availability, which raises the question of economic calculus, particularly regarding the cost of generation and supply. These factors affect the cost structure of those responsible for supplying energy and, in extreme cases, can lead to energy exclusion. The article aimed to identify differences in the presentation and interpretation of operating cost data from the individual and consolidated financial statements of Polish energy groups, which is of key importance for investors, analysts and decision-makers in the energy sector. The analysis uses data for 2018–2022 from the income statement. The research hypothesis is that the complexity of Polish energy groups in the Polish energy sector leads to ambiguity in the interpretation of cost data included in stand-alone and consolidated financial statements. Full article

To mitigate climate change problems, a low-carbon renewable energy policy is needed. Evaluating the impact of these problems on global value chains is essential to ensure an effective transition to sustainable economic development. This study analyzes the impact of emission reduction policies on Global Value Chains (GVC) using the Global Trade Analysis Project-Energy (GTAP-E) model by addressing three fundamental research questions. First, how does the implementation of B40 renewable energy policy combined with carbon tax affect Indonesia’s energy sector output and carbon emissions? Second, to what extent does this policy influence Indonesia’s participation in GVC, particularly in the crude palm oil (CPO) industry? Third, what are the implications for economic growth and social welfare? Our analysis focuses on the CPO sector, considering Indonesia’s position as the world’s largest producer and its potential for sustainable biofuel production through clean technological processes. The results of this study show that the policy effectively reduces carbon emissions through decreased fossil fuel production while promoting renewable energy adoption. It significantly increases Indonesia’s forward GVC participation in the CPO sector, enhancing value addition and international competitiveness. Furthermore, the policy generates positive impacts on economic growth and social welfare. This study emphasizes the importance of international policy coordination and the crucial role of technological innovation in achieving sustainable economic development for a low-carbon economy and strengthening Indonesia’s position in the global value chain. Full article

As reliance on sustainable energy grows, the demand for efficient, high-performance energy storage systems becomes increasingly critical, especially in uninterruptible power supplies (UPS), where reliability and fast transitions are essential. Supercapacitors, with their high power density and rapid charging capabilities, are emerging as strong alternatives to lithium-ion batteries in UPS systems. This paper presents a novel real-time estimation technique for monitoring supercapacitor parameters within a UPS, focusing on the dynamic behavior of these parameters and their evolution over the system’s lifecycle. The proposed estimator demonstrates exceptional accuracy, achieving less than 1% error within 120 ms of startup and nearly zero error thereafter. The estimator’s performance remains robust even as supercapacitor parameters change due to aging effects over the lifespan. The UPS system features a modular design, enabling scalability to accommodate higher power requirements or longer backup durations and adaptability to various supercapacitor types. Experimental results highlight the system’s robustness in both charging and backup modes, emphasizing the potential of supercapacitors as key components in future UPS systems. Full article

Over the last few decades, several marine renewable energy (MRE) technologies, such as wave energy converters (WECs) and current energy converters (CECs), have been developed. As opposed to traditional materials such as metal alloys, the structure of these technologies is made up of polymer and polymer composite materials. Most structures have been made using thermoset polymer composites; however, since thermoset polymer composites are not recyclable and lack sustainability, and with recent innovations in recyclable resins, bio-based resins, and the development of additive manufacturing technologies, thermoplastic polymers are increasingly being used. Nevertheless, the methodologies for identifying end-of-life options and recovering these polymer composites, as well as the recycling and reuse processes for MRE structures, are not well-studied. Specifically, since these MRE structures are subjected to salinity, moisture, varying temperature, biofouling, and corrosion effects depending on their usage, the recyclability after seawater aging and degradation needs to be explored. Hence, this review provides an in-depth review of polymer composites used in marine applications, the hygrothermal aging studies conducted so far to understand the degradation of these materials, and the reuse and recycling methodologies for end-of-life MRE structures, with a particular emphasis on sustainability. Full article

The increasing deployment of decentralized power generation based on intermittent renewable resources to reach environmental targets creates new challenges for power systems stability. Several technologies and approaches have been proposed in recent years including the use of superconducting magnetic energy storage. This study focuses on the review of existing superconducting magnetic energy storage systems for power quality control purposes. Such systems can supply and absorb the rated power level within seconds, promoting fast power quality regulation. Systems for power quality services such as frequency regulation, power oscillation damping, power fluctuation suppression, and active power filtering are identified and described. First, the physical characterization of superconducting magnets concerning geometries, materials, associated inductances, and nominal magnetic energy storage capacities is conducted. Then, the functional description of several current conversion circuits and systems used as interfaces for superconducting magnets is performed. The existing methodologies and systems to perform the control of current converters for different power control services and applications are also identified and described. Finally, the results regarding the number of different systems identified for each power quality control service are presented, and their applicability is discussed based on the adopted control approach. Challenges concerning the development of new systems to improve the power quality on grids with high penetration of decentralized energy resources from intermittent renewables are also identified. Full article

Since rising worldwide energy consumption is anticipated with increasing rapid industrialization and urbanization, green energy sources have become the ineluctable choice among energy engineers, power engineers, and researchers for carbon-free and sustainable electric power generation. By integrating several energy sources, a hybrid renewable and sustainable power supply system (HRSPSS) has been created to solve the global warming problem. HRSPSS aims to develop contemporary electricity grids that benefit society, the environment, and the economy. However, there is a need for thorough assessment of these complex HRSPSSs for making the most use of renewable energy potential and carefully crafting suitable solutions. This paper provides a thorough investigation of the most effective methods for sizing, optimizing, controlling, and managing energy, as well as how to combine different renewable energy sources to create a hybrid sustainable power supply system. Information on several software simulation tools and optimization methods that have been used to support HRSPSS development, research, and planning is presented in this study. Additionally, this study covers energy management and control strategies that have been used to ensure efficient and optimal operation of HRSPSS. Furthermore, this article presents an extensive comparison among various strategies utilized in each area (sizing, optimizing, controlling, and managing energy) to provide conclusive remarks on the suitable strategies for respective applications. The outcome of this study will help various stakeholders in the energy sector to make appropriate decisions during the design, development, and implementation phases of a hybrid sustainable power supply system. Full article

Lithium batteries represent a pivotal technology in the advancement of renewable energy, and their enhanced performance and safety are vital to the attainment of sustainable development goals. To solve the issue of the high missed detection rate of minimal defects on end face of lithium battery shells, a novel YOLO-based Minimal Defect Detection algorithm, named YOLO-MDD, is proposed. Firstly, aimed at the problem of insufficient data, a dataset of defects on the end face of lithium battery shells is constructed and annotated. Secondly, a YOLO-MDD network which includes a feature extraction module and a four-scale detection head for detecting defects of various scales is improved. Here, deformable convolution and an attention module are ingeniously embedded into the backbone of YOLO to capture more detailed and accurate information on object defects, and the four-scale head is used to handle the significant differences in the size and shape of defects on lithium battery shells. Finally, a hybrid loss including localization loss with normalized Wasserstein distance (NWD), classification loss, and confidence loss is designed to optimize our model to further enhance its sensitivity to minimal defects. The experimental results show that the proposed YOLO-MDD has a mean average precision of 80% for the defect detection of the lithium battery shells, especially with a minimal defect rust spots mean average precision of 74.1% and a recall rate of 71.5%, which is superior compared with other mainstream detection algorithms and provides the technical support necessary to achieve the goals of energy and environmental sustainability. Full article

In order to reach climate protection goals at national or international levels, new forms of combined heating and cooling networks with ultra-low network temperatures (5GDHC) are viable alternatives to conventional heating networks. This paper presents a simulation library for 5GDHC networks as sustainable shared energy systems, developed in the object-oriented simulation framework OpenModelica. It comprises sub-models for residential buildings acting as prosumers in the network, with additional roof-mounted thermal systems, dynamic thermo-hydraulic representations of distribution pipes and storage, time-series-based sources for heating and cooling, and weather conditions adjustable to user-specified locations. A detailed insight into an in-house development of a sub-model for horizontal ground heat collectors is given. This sub-model is directly coupled with thermo-hydraulic network simulations. The simulation results of energy balances and energetic efficiencies for an example district are described. Findings from this study show that decentralised roof-mounted solar thermal systems coupled to the network can contribute 21% to the total source heat provided in the network while annual thermal gains from the distribution pipes add up to more than 18% within the described settings. The presented simulation library can support conceptual and advanced planning phases for renewable heating and cooling supply structures based on environmental sources. Full article

In contemporary power electronics, multilevel converters stand at the forefront of high-power, high-voltage applications, offering superior performance in terms of efficiency, reduced harmonics, and improved voltage waveform quality compared to traditional two-level converters. Their capability to synthesize waveforms with multiple voltage levels has garnered significant attention across various industrial sectors, including renewable energy systems, electric vehicles, and high-voltage power transmissions. This paper provides a comprehensive overview of multilevel converter technology, encompassing their classification, main topologies, recent advancements, and emerging trends. By exploring the evolution of multilevel converter technology and identifying future research directions, researchers and engineers can gain valuable insights into the design, optimization, and application of these advanced power electronic systems. Full article

Active customers play a critical role in the successful implementation of support schemes, paving the way for the emergence of an energy community. This analysis explores the cooperation among active customers and the implications for developing energy communities. Furthermore, the motivations for consumers becoming active customers in the context of Latvia are illuminated, while also exploring the broader context of navigating the complex regulatory landscape to promote self-consumption. In contrast to prior studies, which often focus on individual or homogenous group participation, this analysis uniquely examines collaborative frameworks that incorporate varied customer categories and profiles. This approach not only underscores the role of tailored regulatory structures in fostering self-consumption, but also presents practical policy insights for incentivizing community-based energy models. The findings reveal that individual participation of active customers in support schemes only achieves the minimal self-consumption threshold in 47% of cases. In contrast, membership in an energy community significantly increases this rate, reaching 84%. These encouraging results underscore the importance of promoting energy community membership among active customers, which subsequently demonstrates substantial potential when promoted across diverse load profile categories. Additionally, the integration of photovoltaic and wind turbine technologies consistently improves self-consumption values. Full article

The wastewater generated by the pharmaceutical industry poses a risk to the environment due to undesirable characteristics such as low biodegradability, high levels of contaminants, and the presence of suspended solids, in addition to the high load of organic matter due to the presence of drugs and other emerging products in the effluent. This study aims to reduce the impact of wastewater pollution by removing amoxicillin (AMO) antibiotics as an organic pollutant. In this concept, two synthesized catalysts, NiAl₂O₄ and ZnO, are sensitive oxides to light energy. The prepared materials were then characterized using X-ray diffraction, UV–vis solid reflectance diffuse, Raman spectroscopy, scanning electron microscopy, BET, and ATR-FTIR spectroscopy. The effects of principal operating parameters under sunlight, namely, the percentage of the mixture of NiAl₂O₄ and ZnO, the pH of the medium, and the initial concentration of the antibiotic were studied experimentally to determine the optimal conditions for achieving a high degradation rate. The results showed that photodegradation is higher at a pH of 6, with a weight percentage of the mixture of 50% for both catalysts in 1 g/L of the total catalyst dose. Then, the effect of the initial concentration of AMO on the photodegradation reaction showed an important influence on the photodegradation process; as the degradation rate decreases, the initial AMO concentration increases. A high degradation rate of 92% was obtained for an initial AMO concentration of 10 mg/L and a pH of 6. The kinetic study of degradation established that the first-order model and the Langmuir–Hinshelwood (LH) mechanism fit the experimental data perfectly. The study showed the success of using heterosystem photocatalysts and sustainable energy for effective pharmaceutical removal, which can be extended to treat wastewater with other organic emerging pollutants. On the other hand, modeling was introduced using Gaussian process regression (GPR) to predict the degradation rate of AMO under sunlight in the presence of heterogeneous ZnO and NiAl₂O₄ systems. The model evaluation criteria of GPR in terms of statistical coefficients and errors show very interesting results and the performance of the model used. Where statistical coefficients were close to one (R = 0.9981), statistical errors were very small (RMSE = 0.1943 and MAE = 0.0518). The results suggest that the model has a strong predictive power and can be used to optimize the process of AMO removal from wastewater. Full article

This research aims to explore the potential of renewable energy sources in urban planning, focusing on microgeneration technologies, through a structured literature review. A systematic review was conducted using the PRISMA method, encompassing the identification, selection, eligibility, and analysis of studies related to renewable energy microgeneration in urban environments. The findings emphasize key areas such as policy development, energy security, and future scenario projections, with a particular focus on solar energy generation. The review highlights the importance of robust regulatory frameworks and monitoring systems for effectively managing prosumers and ensuring equitable energy distribution. Key challenges identified include the intermittency of renewable energy sources, regulatory complexities, monitoring systems, prosumer management, energy sizing risks, and the lifecycle of microgeneration technologies. The research accentuates the need for outstanding collaboration between academia, industry, and urban planners to accelerate the adoption and implementation of renewable energy solutions. The main conclusion is that such collaboration is essential for addressing challenges, driving innovation, and contributing to the development of sustainable urban energy systems. Full article

This study presents a techno-economic and environmental analysis of hybrid renewable energy systems to identify the optimal configuration for supplying the planned 850 MW renewable energy plant in Yanbu city, Saudi Arabia. Ten grid-connected system designs combining photovoltaic (PV), wind turbine (WT), and battery storage were simulated and optimized using the HOMER Grid software (1.10.2 pro edition). A site suitability analysis was conducted to evaluate potential locations based on climatic, topographic, and infrastructure-related factors. A sensitivity analysis considered variations in solar irradiation, wind speed, temperature, load demand, and economic parameters. The results showed that the PV-only system with an 850 MW capacity achieved the lowest net present cost (NPC) of USD 201 million and levelized cost of energy (LCOE) of 0.0344 USD/kWh, making it the most economically feasible option. However, a hybrid WT–PV configuration of 212.5 MW WT and 637.5 MW PV was also proposed to support local manufacturing. All proposed systems provided over a 91% renewable energy contribution while reducing CO₂ emissions by 53% compared to grid supply only. Up to 1152 jobs are estimated to be created through renewable energy deployment in Yanbu city. Full article