KR102625403B1 - Integrated local renewable energy management system - Google Patents

Abstract

One embodiment of the present invention is a renewable energy control infrastructure that is connected to a grid system that collects renewable energy power generation information from renewable energy power sources within each renewable energy power generation zone in the region and collects grid data containing the renewable energy power generation information. ; And an application unit that communicates with the renewable energy control infrastructure to receive the system data, determines power system stability in the area based on the system data, and generates output control information according to the power system stability. And, the system system collects the renewable energy generation information of the renewable energy power generation source through a plurality of information collection terminals, and the renewable energy control infrastructure controls each renewable energy generation zone in the region according to the output control information. It provides a regional renewable energy integrated control system that controls renewable energy generation.

Description

Local renewable energy integrated management system {INTEGRATED LOCAL RENEWABLE ENERGY MANAGEMENT SYSTEM}

The present invention relates to a regional renewable energy integrated control system, and more specifically, to determine the impact of renewable energy generation on the local power system and to control the renewable energy production of each renewable energy generation zone in the region according to the judgment results. It is about a regional renewable energy integrated control system.

At the 2011 Durban General Assembly, it was agreed to form a new climate regime after 2020 in which both developed and developing countries participate as a follow-up to the Kyoto Protocol. In addition, following the signing of the Paris Agreement in December 2015, a new climate system that will apply to all countries in 2020 was introduced, and in line with this new climate system, new energy industries centered on renewable energy are being promoted.

Renewable energy refers to renewable energy including sunlight, water, precipitation, biological organisms, etc., and power generation using this includes solar energy, wind energy, and hydroelectric energy.

This type of renewable energy has the advantage of being clean, free of depletion, and pollution-free renewable energy. However, it has the disadvantage of being less powerful and affected by weather conditions compared to base power generation from oil, coal, and nuclear power.

Specifically, since renewable energy depends on natural conditions (solar radiation, temperature, wind, etc.), it has characteristics that make it difficult to predict the output for power production, uncertainty, and high volatility in output amount.

For example, in the case of solar power generation, the amount of power generation is intermittent because it is greatly affected by weather conditions such as the amount of sunlight, and since it is difficult to accurately predict weather conditions, the uncertainty of the amount of power generation is also high.

Figure 1 is a diagram to explain the need for management of reserve power due to the intermittency of renewable energy generation.

As shown in Figure 1, renewable energy generated in each power generation zone (1) is supplied to the power grid (3). And since energy generated from base power generation means (2) such as oil, coal, and nuclear power is also supplied to the power grid (3), renewable energy and base power generation energy are combined in the power grid (3).

For example, when renewable energy is energy obtained through solar power generation, as shown in the graph of FIG. 1, the amount of base power generation required during the day decreases, and the power reserve required increases after sunset compared to the daytime.

On the other hand, when the amount of renewable energy generation during the day is reduced due to weather conditions, more base power generation is needed to equal the reduced amount of renewable energy power generation. For the above-mentioned reasons, if the forecast error for the power production of renewable energy increases, the planned power generation amount and the actual amount are divided. Since there is a difference between the total amounts, it is necessary to increase the reserve power to cope with the prediction error. This has the problem of increasing power generation costs.

Accordingly, an integrated renewable energy control system is needed that can predict and control the generation amount of renewable energy, respond to the volatility of renewable energy and generation acceptance issues, and stably operate (monitoring, predicting, controlling, etc.) the power system in each region.

The technical task to be achieved by the present invention is to determine the impact of renewable energy generation on the local power system and predict the output of each renewable energy generation zone in the region according to the judgment result, evaluate the stability/acceptance limit, and control the output of renewable energy through the process. The goal is to provide a regional renewable energy integrated control system that can control production.

Another technical task to be achieved by the present invention is to provide an in-memory application database unit optimized for control of the local power system.

Another technical task to be achieved by the present invention is to provide an application infrastructure that provides an environment for predicting the output of renewable energy, assessing stability/acceptability limits, and performing output control in connection with local renewable energy power generation sources and grid systems.

Another technical task to be achieved by the present invention is to distribute and parallel process warehousing system data, weather data, and a plurality of information generated in the process of evaluating the stability/acceptance limits of the power system, and to analyze the warehousing big data in real time. The goal is to provide an analysis infrastructure for analysis.

The technical problem to be achieved by the present invention is not limited to the technical problem mentioned above, and other technical problems not mentioned can be clearly understood by those skilled in the art from the description below. There will be.

In order to achieve the above technical problem, an embodiment of the present invention is connected to a grid system that collects renewable energy power generation information from renewable energy power generation sources within each renewable energy power generation zone in the region, and grid data containing the renewable energy power generation information. renewable energy management infrastructure that collects; And an application unit that communicates with the renewable energy control infrastructure to receive the system data, determines power system stability in the area based on the system data, and generates output control information according to the power system stability. And, the system system collects the renewable energy generation information of the renewable energy power generation source through a plurality of information collection terminals, and the renewable energy control infrastructure controls each renewable energy generation zone in the region according to the output control information. It provides a regional renewable energy integrated control system that controls renewable energy generation.

The system may include a Supervisory Control And Data Acquisition (SCADA) module that collects the renewable energy generation information by communicating in real time with each of the plurality of information collection terminals.

The system system includes an EMS (Energy Management System) that collects base power generation data, power facility information, and power facility characteristic information within the region, and the system data is data collected by the EMS when collecting the renewable energy power generation information. Further comprising, the power facility information may be information on power facilities connected to the power system of the region, and the power facility characteristic information may be information representing the characteristics of each power facility connected to the power system of the region.

It further includes a distributed parallel processing unit that provides weather data of the region to the renewable energy control infrastructure, wherein the application unit includes a weather prediction module that generates weather prediction information of the renewable energy generation area based on the weather data; a renewable energy output prediction module that generates output prediction information of the renewable energy power generation zone based on the weather prediction information and the system data; Based on the power equipment characteristic information and power equipment information, the exact size and phase angle of the bus voltage are calculated based on the dynamic and static information of the power equipment, and based on the calculated values, the overload of the line and transformer and the bus voltage are calculated. Other system analysis modules that generate state estimation result information that detects constraint violations and reactive power constraint violations of generators and synchronous generators; A stability evaluation module that generates stability evaluation information of the local power system based on at least two of the output prediction information, state estimation result information, power facility characteristic information, and power facility information; An acceptance limit evaluation module that generates acceptance limit evaluation information based on the voltage standard violation degree of the local power system, facility and transmission line overload, transient stability, renewable energy LVRT (Low Voltage Ride Through), and fault current size; Comprising a renewable energy output control module that generates the output control information based on the stability evaluation information and the acceptance limit evaluation information, the weather prediction information, the output prediction information, the state estimation result information, the stability evaluation information, The acceptance limit evaluation information and the output control information may be returned to the renewable energy control infrastructure.

The renewable energy power generation source is a wind power generation source, and the renewable energy output prediction module collects wind speed and wind power generation data of the renewable energy power source for a certain period of time, and at least some of the wind speed and wind power generation data of the certain period of time include wind speed and wind power generation data. Estimating the first power generation by setting up an ARIMAX model based on wind power generation data, and estimating the second power generation by setting up a polynomial regression model based on at least some of the wind speed and wind power generation data during the certain period of time, , Estimating the third power generation based on wind speed data at a point near the renewable energy power generation source, using the first power generation, the second power generation, the third power generation, and past wind speed and wind power generation data of the renewable energy power source. Output prediction information based on analog ensemble can be generated.

The renewable energy output prediction module collects wind speed prediction data at a point near the renewable energy power source and spatial data near the renewable energy power source, and predicts the wind speed at the renewable energy power source location based on the Kriging technique. And, the wind speed can be corrected according to the altitude of the renewable energy power generation source based on the Deacon equation, and the third power generation amount can be estimated based on the corrected wind speed.

The renewable energy management infrastructure includes an infrastructure management unit, and the infrastructure management unit includes an in-memory database management module, an integrated process management module, an alarm/event management module, and a log management module, and the in-memory database management module Controls the execution, control, status management of the in-memory database unit, and processes of modules belonging to the application unit, and the integrated process management module provides process management information, preset priorities, and current status of each component in the renewable energy control infrastructure. Based on the status, the process of each component in the renewable energy control infrastructure is controlled and alarms and events generated during the control process are stored and handled, and the alarm/event management module stores alarm and event information generated in the grid system. and handles, transmits the alarm and event information to the integrated control unit and the distributed parallel processing unit, and the log management module generates a log file by referring to the process log information stored in the in-memory database unit and log level. Accordingly, log information is recorded in the log file, and the log information in the log file can be deleted according to a set period.

The renewable energy management infrastructure is connected to the infrastructure management unit and stores the process management information, meta information of the in-memory database, the power facility modeling information, the power facility characteristic information, and module information of the SCADA module. It may further include infrastructure management information memory.

The distributed parallel processing unit may receive weather data of the region from an external weather database or weather server and provide it to the renewable energy control infrastructure.

The renewable energy control infrastructure includes a real-time database, and the real-time database can store the system data and information returned from the application unit.

The distributed parallel processing unit includes a data collection unit that collects data and information stored in the real-time database; a data loading unit that distributes the data or information collected in the data collection unit and loads it into a non-relational database or distributed file system; a data processing and exploration unit that queries the data or information loaded in the data loading unit, converts it into a predetermined format, and warehouses the converted data; And it may include a data analysis application unit that performs secondary analysis of the stability of the local power system.

The data collection unit includes a first distributed queue module, a system data collection/loading module, a second distributed queue module, and a weather data collection/loading module, and the first distributed queue module is connected to the real-time database and serves as the real-time database. Receives data stored in and pushes it to the system data collection/loading module, and the second distributed queue module is connected to at least one of a distribution automation system, a metering data management system, a weather database, or a weather server to receive data and perform the weather It can be pushed to the data collection/loading module.

The data processing search unit includes an SQL processing engine, an aggregate information generation module, an aggregate information creation history management module, and a data warehousing module, and the SQL processing engine queries data loaded in the non-relational database or the distributed file system. Loaded into the data warehousing module, the aggregated information generation module generates aggregated information of data loaded into the non-relational database or distributed file system and loaded into the data warehousing module, and the aggregated information generation history management module is configured to: Creation history information of aggregate information, major aggregate and statistical meta information can be created and loaded into the data warehousing module.

The data analysis application unit learns based on data stored in the data warehousing module, and receives at least part of the data loaded in the non-relational database or the distributed file system as input and uses an artificial intelligence to estimate the amount of renewable energy generation in the region. May include neural network models.

It further includes an integrated control unit that receives the data warehoused in the data loading unit, visualizes it, and provides it to the user, wherein the integrated control unit generates a control message according to the user's input, and the control message has priority over the output control information. Thus, it is possible to control the amount of renewable energy generation in each renewable energy generation zone within the region.

The renewable energy power generation source is connected to an inverter, the output control information is transmitted to the information collection terminal, and the information collection terminal can control the power generation amount of the renewable energy power source by controlling the inverter.

The information collection terminal is a remote terminal unit, and the interval at which the information collection terminal collects the renewable energy generation information may be 1 second or less.

According to an embodiment of the present invention, output control information is generated by predicting the output amount of renewable energy power generation sources in the region based on grid data collected through the SCADA module of the grid system, local power use environment data, and weather data, and , the power generation amount of each renewable power generation zone in the region or the renewable energy power generation source belonging to each renewable power generation zone is controlled using output control information, so the load on the power system due to the intermittency of renewable energy can be reduced.

In addition, according to an embodiment of the present invention, it is possible to predict the output of a renewable energy power generation source, so it is possible to establish a preliminary power generation plan based on the predicted value and reduce power system operating costs through automatic control.

In addition, according to an embodiment of the present invention, a vast amount of system data and information generated according to the operation of the application unit are stored/managed/analyzed by the distributed parallel processing unit, thereby improving the overall data processing ability of the regional renewable energy integrated control system. It can be.

The effects of the present invention are not limited to the effects described above, and should be understood to include all effects that can be inferred from the configuration of the invention described in the description or claims of the present invention.

Figure 1 is a diagram to explain the process in which a load is generated on the power grid due to the intermittency of renewable energy generation.
Figure 2 is a block diagram schematically showing a regional renewable energy integrated control system according to an embodiment of the present invention.
Figure 3 is a diagram for explaining a renewable power generation information collection unit and a system linked thereto according to an embodiment of the present invention.
Figure 4 is a block diagram for explaining the renewable energy pipe infrastructure and application unit according to an embodiment of the present invention.
Figure 5 is a diagram for explaining the process in which the renewable energy control infrastructure is linked with the integrated control unit and the distributed parallel processing unit according to an embodiment of the present invention.
Figure 6 is an example diagram illustrating a process in which a renewable energy output prediction module generates output prediction information of a power generation zone in a region according to an embodiment of the present invention.

Hereinafter, the present invention will be described with reference to the attached drawings. However, the present invention may be implemented in various different forms and, therefore, is not limited to the embodiments described herein. In order to clearly explain the present invention in the drawings, parts that are not related to the description are omitted, and similar parts are given similar reference numerals throughout the specification.

Throughout the specification, when a part is said to be "connected (connected, contacted, combined)" with another part, this means not only "directly connected" but also "indirectly connected" with another member in between. "Includes cases where it is. Additionally, when a part is said to “include” a certain component, this does not mean that other components are excluded, but that other components can be added, unless specifically stated to the contrary.

The terms used herein are only used to describe specific embodiments and are not intended to limit the invention. Singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, terms such as “comprise” or “have” are intended to indicate the presence of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification, but are not intended to indicate the presence of one or more other features. It should be understood that this does not exclude in advance the possibility of the existence or addition of elements, numbers, steps, operations, components, parts, or combinations thereof.

Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings.

Figure 2 is a block diagram schematically showing a regional renewable energy integrated control system according to an embodiment of the present invention.

As shown in Figure 2, the regional renewable energy integrated control system includes a renewable power generation information collection unit 100, a system system 200, a renewable energy control infrastructure 300, an application unit 400, and an integrated control unit ( 500) and a distributed parallel processing unit 600.

The renewable power generation information collection unit 100 may collect power generation information for each renewable energy power generation zone in the region. As an example, the renewable power generation information collection unit 100 may include a plurality of information collection terminals 110, 120, and 130 and may be respectively installed in a plurality of renewable energy power generation zones. Specifically, the plurality of information collection terminals 110, 120, and 130 may be field terminal devices installed to monitor, measure, and control renewable energy power generation sources within each renewable energy power generation zone.

As an example, the renewable power generation information collection unit 100 digitally converts CT and PT measurement values for meters, transmits data to the renewable power generation data linkage module, converts and relays information into the information communication method requested by the renewable power generation data linkage module, It can perform the function of collecting and transmitting basic power quality information.

As an example, the power generation information collected by each of the information collection terminals 110, 120, and 130 belonging to the renewable power generation information collection unit 100 may be converted into a predetermined protocol and transmitted to the grid system 200.

The system system 200 can monitor the status of the power system in the region based on the collected power generation information. Additionally, the grid system 200 can collect and manage power generation information from the base power generation area (P) as well as the renewable energy power generation area within the region.

And the grid system 200 can transmit the collected information to the renewable energy control infrastructure 300. Hereinafter, the information transmitted by the system system 200 to the renewable energy control infrastructure 300 will be referred to as system data.

Meanwhile, the renewable energy control infrastructure 300 provides an execution environment necessary to perform the overall function of the regional renewable energy integrated control system.

As an example, the renewable energy control infrastructure 300 may be linked with the application unit 400, and based on system data, weather prediction, renewable energy output prediction, power system stability evaluation, renewable energy output control, input/output data management, and an execution environment for performing alarm processing can be provided.

In addition, the renewable energy control infrastructure 300 includes a system system 200, an application unit 400, an integrated control unit 500, and a distributed parallel processing unit 600 belonging to a regional renewable energy integrated control system. It can be connected to the components to control the overall process of the regional renewable energy integrated control system.

Each configuration and function of this renewable energy control infrastructure 300 will be examined in detail with reference to FIG. 4.

In addition, the application unit 400 is linked to the renewable energy control infrastructure 300 and can predict or calculate various information necessary for stable operation of the power system.

As an example, the application unit 400 may receive system data from the renewable energy control infrastructure 300. And the application unit 400 can perform weather prediction, renewable energy output prediction, system safety evaluation, acceptance limit evaluation, and other system analysis based on system data, and generate renewable energy output control information based on the performance results. can do. And the application unit 400 may return information generated during each execution process to the renewable energy control infrastructure 300.

In addition, the output control information can be transmitted to each information collection terminal 110 and 120 through the grid system 200, and the power generation amount of each renewable energy power source can be controlled based on the output control information. Of course, this series of control processes may be performed automatically.

Additionally, the integrated control unit 500 may be connected to the renewable energy control infrastructure 300. The integrated control unit 500 receives information from the renewable energy control infrastructure 300 ( or from the renewable energy control infrastructure 300 via the distributed parallel processing unit 600) and processes the received information. It can be visualized and provided to users. As an example, the integrated control unit 500 may be provided to users through a web-based user interface.

In addition, the distributed parallel processing unit 600 can receive system data from the renewable energy control infrastructure 300 and can distribute or parallel process the received system data. As an example, the distributed parallel processing unit 600 can perform functions of collection, loading, processing, search, analysis, and application of system data. The specific configuration and function of the distributed parallel processing unit 600 will be examined in detail with reference to FIG. 5.

Figure 3 is a diagram for explaining the renewable power generation information collection unit 100 and the system 200 associated therewith according to an embodiment of the present invention.

As shown in FIG. 3, the renewable power generation information collection unit 100 may include a plurality of information collection terminals. In FIG. 3 , for convenience of explanation, it is assumed that the renewable power generation information collection unit 100 includes a first information collection terminal 110 and a second information collection terminal 120.

The first information collection terminal 110 may be connected to the first renewable energy power generation source (R11) in the first power generation zone. As an example, the first renewable energy power generation source (R11) may be wind power.

As an example, the first renewable energy power generation source (R11) may be sequentially connected to the transformer (R12), the circuit breaker (R13), and the first information collection terminal 110 through a distribution line.

The transformer can boost the electrical energy produced by the first renewable energy power generation source (R11) to a distribution level voltage.

Circuit breakers can be installed in distribution lines and can detect abnormal currents due to overcurrent short circuits and ground faults. Additionally, the circuit breaker can block the flow of current when an abnormal current occurs. For example, the breaker may be a vacuum circuit breaker (VCB).

And, the first information collection terminal 110 may be connected to a measuring point or breaker (R13) of a distribution line through which renewable energy is transmitted. And the first information collection terminal 110 can measure the power information of the measurement point or circuit breaker. As an example, the first information collection terminal may be connected to the measurement point through a PT or CT cable for measurement (meter).

And, the first information collection terminal 110 may transmit the measured power information to the grid system 200. At this time, the first information collection terminal 110 may convert power information according to a predetermined protocol. As an example, the predetermined protocol may be one of Modbus, DNP, and K-DNP.

Meanwhile, the first information collection terminal 110 may be connected to the first renewable energy power generation source (R11) with the first control device (R14) interposed therebetween. As an example, the first information collection terminal 110 may receive output control information from the grid system 200. And, the first information collection terminal 110 may control the output of the first renewable energy power generation source (R11) using the first control device (R14) based on the received output control information.

Specifically, the first information collection terminal 110 may receive monitoring and measurement control information received from a renewable power generation data linkage module connected to the grid system 200 through a modem. And the first information collection terminal 110 may transmit the request to a lower destination (ex. first control device (R14)) according to a preset protocol (ex. Modbus) address. At this time, the lower destination may be an inverter (not shown) connected to the first renewable energy power generation source (R11).

In short, the first information collection terminal 110 operates the first renewable energy power source (R11) so that the power generation amount of the first renewable energy power source (R11) increases or decreases based on the output control information received from the grid system 200. You can control it.

Meanwhile, the second information collection terminal 120 may be connected to the second renewable energy power generation source (R21) in the second power generation zone. As an example, the second renewable energy power generation source (R21) may be solar power generation. Hereinafter, a description of the configuration of the second information collection terminal 120 that overlaps with the first information collection terminal 110 will be omitted.

As an example, the second renewable energy power generation source (R21) may be sequentially connected to the inverter (R22), transformer (R23), circuit breaker (R24), and second information collection terminal 120 through a distribution line.

The inverter R22 can convert direct current energy stored in the current collector of the second renewable energy power generation source R21, that is, the solar collector, into alternating current energy.

And, the second information collection terminal 120 may be connected to a measuring point or breaker (R24) of a distribution line through which renewable energy is transmitted. And the second information collection terminal 120 can measure the power information of the measurement point or breaker (R24).

Meanwhile, the second information collection terminal 120 may be directly connected to the inverter (R22). And, the second information collection terminal 120 can receive output control information transmitted through the grid system 200. And, the second information collection terminal 120 can control the power generation amount of the second renewable energy power generation source (R21) by controlling the inverter (R22) based on the received output control information.

In the above, it was explained that the first information collection terminal 110 and the second information collection terminal 120 control the power generation amount of the renewable energy power generation source using the first control device (R14) and the inverter (R22), respectively. Of course, a configuration in which the information collection terminals 110 and 120 control the amount of power generation by controlling other components within each power generation zone is also included in the technical idea of the present invention.

Meanwhile, each information collection terminal (110, 120) belonging to the renewable power generation information collection unit 100 may be a remote terminal unit (RTU). Additionally, the information collection terminal can measure the power information of the measurement point at intervals of up to 1 second. This is because monitoring and analysis of instantaneous system impacts are necessary due to the nature of renewable energy power generation sources with very fast and large fluctuations in output.

That is, each information collection terminal 110, 120 measures power information at intervals of up to 1 second, thereby enabling accurate time synchronization of the renewable power generation status.

In addition, the power generation information collected by the renewable power generation information collection unit 100, that is, the power information, may be transmitted to the grid system 200 through a renewable power generation data linkage module.

The renewable power generation data linkage module T1 may collect power generation information transmitted from the renewable power generation information collection unit 100 and transmit it to the grid system 200. Additionally, the renewable power generation data linkage module (T1) may transmit the control signal received from the grid system 200 to each of the information collection terminals 110 and 120 belonging to the renewable power generation information collection unit 100.

Meanwhile, the system system 200 can monitor the status of the power system in the area based on the collected power generation information.

To this end, the grid system 200 may include a Supervisory Control And Data Acquisition (SCADA) module 210 for controlling power generation sources within each renewable power generation zone and collecting information. The SCADA module 210 can collect power generation information generated in each power generation zone in the region in real time.

Additionally, the grid system 200 may include an EMS (Energy Management System) 220 that collects base power generation data from base power generation sources in the region and power usage environment data on consumption within the region. At this time, the base power source refers to a power source other than a local renewable energy power source. However, of course, the EMS 220 can also collect power generation data from all power generation sources in the region. Additionally, the EMS 220 may functionally include the SCADA module 210.

Figure 4 is a block diagram for explaining the renewable energy control infrastructure 300 and application unit 400 according to an embodiment of the present invention.

As shown in FIG. 4, the renewable energy control infrastructure 300 includes a grid system connection unit 310, an in-memory database unit 320, an infrastructure management unit 330, an infrastructure management information memory 340, and a real-time It may include a connection unit 350.

The grid system linkage unit 310 may include a grid data reception module 311 and a control message transmission module 312.

The grid data receiving module 311 may receive facility information and real-time power generation information necessary for the operation of the application unit 400 from the grid system 200.

As an example, the grid data receiving module 311 may receive real-time power generation information of each power generation zone in the region from the SCADA module 210. Additionally, the system data receiving module 311 may receive facility information of each power generation zone in the region from the EMS system 220.

Additionally, the system data reception module 311 can receive weather data from the distributed parallel processing unit 600. As an example, weather data may be data collected by the distributed parallel processing unit 600 from an external server. As an example, the weather data may include at least one of budget forecast data, Korea Meteorological Administration observation data, power generation complex data, and solar radiation measurement data. At this time, of course, weather data can be collected by other components belonging to the renewable energy control system, such as the system system 200, in addition to the distributed parallel processing unit 600.

In addition, the control message transmission module 312 may transmit output control information generated through linkage between the renewable energy control infrastructure 300 and the application unit 400 to the grid system 200. As an example, output control information may be transmitted to each information collection terminal (110, 120) of each power generation zone in the region via the SCADA module 210.

The in-memory database unit 320 may include a real-time database 321 and an application database 322.

The real-time database 321 can store facility information, real-time power generation information, weather data, etc. received by the grid data receiving module 311 from the grid system 200. Additionally, the real-time database 321 may provide stored facility information, real-time power generation information, weather data, etc. to the application unit 400.

In addition, the application unit 400 includes a weather information prediction module 410, a renewable energy output prediction module 420, a stability evaluation module 430, an acceptance limit evaluation module 440, a renewable energy output control module 450, and others. It may include a system analysis module 460.

The weather information prediction module 410 may generate weather prediction information for a renewable energy power generation area in the region based on weather data. As an example, weather prediction information may be predicted values of solar radiation, wind speed, temperature, etc.

Additionally, the renewable energy output prediction module 420 can generate output prediction information for each renewable energy power generation zone in the region based on weather forecast information and system data. At this time, the output prediction information may be the amount of power generation expected to be generated in each renewable energy power generation zone.

Additionally, the stability evaluation module 430 may generate stability evaluation information of the power system based on at least two of output prediction information, state estimation result information, power facility characteristic information, and power facility information.

At this time, the power facility characteristic information is information that manages the characteristics of each power facility and may include information such as facility name, capacity, facility type, dynamic information, power generation amount, frequency, and power factor. Additionally, the power facility information may be information on power facilities connected to the power system. For example, power equipment connected to the power system may be a generator, transformer, or switch. In addition, the state estimation result information is based on the power facility characteristic information and power facility information. The exact size and phase angle of the bus voltage are calculated based on the dynamic and static information of the power facility, and the line and transformer are connected based on the calculated values. This may be information that detects overload, violation of bus voltage constraints, and violation of reactive power constraints of the generator and synchronous generator. Such power facility characteristic information, power facility information, and state estimation result information may be generated by other system analysis modules 460. Meanwhile, power facility characteristic information and power facility information may be information received from the grid system.

In addition, the stability evaluation information may be information that evaluates transient stability, voltage stability, etc. during a normal state or a transient state before and after a disturbance by reflecting the dynamic characteristics of the power facility based on the static state of the power system.

Next, the acceptance limit evaluation module 440 is a module for analyzing the acceptance limit to respond to the output volatility of renewable energy, and can periodically evaluate the acceptance limit for processed system data including output prediction information.

As an example, the acceptance limit evaluation module 440 can generate acceptance limit evaluation information based on voltage standard violation, facility and transmission line overload, transient stability, renewable energy LVRT (Low Voltage Ride Through), and fault current magnitude. there is.

Here, the degree of violation of the voltage standard may be determined based on the results of an analysis of voltage changes in the local power system due to an assumed failure or the results of an analysis of violations of the voltage maintenance standard and voltage adjustment target. Here, a hypothetical failure refers to a virtual single or multiple power equipment failure that may occur in the power system.

In addition, the overload degree of facilities and transmission lines can be determined based on the results of analysis of overload of transformers and transmission lines in the system due to assumed failures or the results of analysis of tidal flow changes due to changes in renewable energy output.

Additionally, the transient stability may be determined based on the results of phase angle instability analysis after the assumed failure. At this time, screening through linearization may be performed prior to determining transient stability.

In addition, the renewable energy LVRT can be determined based on the results of analysis of the violation of the LVRT standard of the renewable energy transient voltage waveform at the time of expected failure.

Additionally, the fault current size may be a fault current size calculated based on the power contribution of renewable energy.

Next, the renewable energy output control module 450 may generate output control information based on the stability evaluation information and the acceptance limit evaluation information. As an example, the output control information may be power generation control information for each renewable energy power generation zone in the region.

In addition, the application unit 400 may return each piece of information generated in the process of generating the output control information along with the output control information to the renewable energy control infrastructure 300. As an example, the application unit 400 transmits power facility characteristic information, power facility information, output control information, output prediction information, weather prediction information, state estimation result information, stability evaluation information, and acceptance limit evaluation information to the renewable energy control infrastructure ( 300).

Specifically, information returned from the application unit 400 may be returned to the application database 322 within the in-memory database unit 320. Additionally, the returned information may also be recorded in the real-time database 321.

That is, the real-time database 321 can store not only system data obtained from the system system 200 and weather data obtained from the distributed parallel processing unit 600, but also each information returned from the application unit 400.

Additionally, information stored in the real-time database 321 may be provided to the integrated control unit 500 or the distributed parallel processing unit 600. Additionally, power generation sources belonging to each renewable power generation zone within the region may be controlled based on the returned information.

Meanwhile, the infrastructure management unit 330 may include an in-memory database management module 331, an integrated process management module 332, an alarm/event management module 333, and a log management module 334.

The in-memory database management module 331 can perform execution, control, and status management of the in-memory database unit 320. Additionally, the in-memory database management module 331 can execute and manage management processes (node management, integrated management process, etc.) for controlling applications operating based on the in-memory database unit 320.

The integrated process management module 332 refers to the information (process management information, priority, current status, etc.) stored in the in-memory database unit 320 to execute, control, and schedule the processes of each component in the renewable energy control infrastructure. Management, status management, process alarms, and event handling can be performed.

The alarm/event management module 333 stores and handles alarm and event information generated in the grid system 200 and can transmit the alarm and event information to the integrated control unit 500 and the distributed parallel processing unit 600.

The log management module 334 creates a log file by referring to the process log information stored in the in-memory database unit 320, records log information in the log file according to the log level, and records the log file in accordance with a set cycle. Log information can be deleted.

In addition, the infrastructure management information memory 340 includes process management information required to drive each module in the infrastructure management unit 330, in-memory database meta information, power facility modeling information, power facility characteristic information, and the SCADA module 210. Information can be saved. That is, when driving an internal module, the infrastructure management unit 330 can access the infrastructure management information memory 340 to load and use data required for driving.

In addition, the real-time connection unit 350 may include a real-time transmission module 351, a real-time control module 352, and a real-time reception module 353, and the renewable energy control infrastructure 300 and the integrated control unit 500 and the distributed parallel processing unit 600.

Figure 5 is a diagram for explaining the process in which the renewable energy control infrastructure 300 is linked with the integrated control unit 500 and the distributed parallel processing unit 600 according to an embodiment of the present invention.

As shown in FIG. 5, the real-time transmission module 351 can transmit information stored in the in-memory database unit 320 to the distributed parallel processing unit 600.

The distributed parallel processing unit 600 can provide a distributed parallel processing environment for distributing and quickly processing data acquired in large quantities from the grid system 200 linked to the renewable energy control infrastructure 300.

This is because the amount of system data acquired in relation to renewable energy generation information and data generated as a result of the operation of the application unit 400 is enormous. These data have high utility as basic data for analysis and prediction of system risk due to the increase in renewable energy, but when information is collected from multiple regions, the amount of data is so large that it is not easy to store and analyze.

In other words, the distributed parallel processing unit 600 according to an embodiment of the present invention is capable of storing and analyzing large amounts of data, and can monitor regional grid stability and reliability for renewable energy through tools such as the visualization analysis module 641. It functions to produce accurate calculations.

Specifically, the distributed parallel processing unit 600 may include a data collection unit 610, a data loading unit 620, a data processing search unit 630, and a data analysis application unit 640.

The data collection unit 610 may collect data from the renewable energy control infrastructure 300 or an external network or server.

To this end, the data collection unit 610 may include a first distributed queue module 611, a system data collection/loading module 612, a second distributed queue module 613, and a weather data collection/loading module 614. there is.

The first distributed queue module 611 may receive data stored in the real-time database 321 in the in-memory database unit 320 from the real-time transmission module 351. As an example, the first distributed queue module 611 may be system data or a plurality of information data generated by the application unit 400. And the first distributed queue module 611 can push-process the received data.

And, the system data collection/loading module 612 receives data by pulling the data loaded in the first distributed queue module 611, and stores the received data in the non-relational database 621 or It can be loaded into the distributed file system 622. As an example, the non-relational database 621 may be No-SQL. As an example, the distributed file system 622 may be the Hadoop Distributed File System (HDFS).

Meanwhile, the second distributed queue module 613 may be connected to an external network, system, or server.

As an example, the second distributed queue module 613 is connected to the Distribution Automation System (DAS) (I1) and receives information about the status information, current, voltage, or failure of the distribution facility from a distribution line automation terminal device. can receive.

As another example, the second distributed queue module 613 may be connected to a Meter Data Management System (MDMS) (I2) to receive metering data.

As another example, the second distributed queue module 613 may be connected to the weather database I3 or the weather server I3 to receive local weather data.

Additionally, the second distributed queue module 613 may transmit information to the weather data collection/loading module 614. And the system data collection/loading module 612 receives data by pulling the data loaded in the second distributed queue module 613, and stores the received data in the non-relational database 621 or distributed data in the data loading unit 620. It can be loaded into the file system 622.

Meanwhile, the loaded weather data may be transmitted to the real-time reception module 353 via the first distributed queue module or the second distributed queue module. Additionally, the weather data received by the real-time reception module 353 can be transferred to the real-time database 321 and used as a basis for generating weather prediction information.

The memory cache 623 may function as a cache memory in the process of storing data received by the first distributed queue module 611 in the non-relational database 621 or the distributed file system 622.

The data processing search unit 630 may include an SQL processing engine 631, a data warehousing module 632, an aggregate information generation module 633, and an aggregate information creation history management module 634.

The SQL processing engine 631 can query, manage, or process data loaded in connection with a non-relational database 621 or a distributed file system 622.

Additionally, the aggregate information creation module 633 may generate aggregate information based on data loaded in the non-relational database 621 or the distributed file system 622 and load it into the data warehousing module 632.

Additionally, when generating aggregate information, the aggregate information creation history management module 634 may generate history information, creation history information, or key aggregate/statistical meta information and load and process them in the data warehousing module 632.

And the data warehousing module 632 can be connected to the SQL processing engine 631. As an example, the data warehousing module 632 may be a database in which an SQL processing engine converts and manages data loaded from the non-relational database 621 or the distributed file system 622 into a predetermined format. Additionally, the data warehousing module 632 may transmit data converted into a predetermined format to the integrated control unit 500 at the request of the integrated control unit 500.

In addition, the data analysis application unit 640 can perform a secondary analysis of the stability of the local power system for renewable energy using the visualization analysis module 641. As an example, the visualization analysis module may visualize data stored in the data warehousing module 632 by analyzing power data. In addition, the data analysis application unit 640 learns based on data stored in the data warehousing module 632, and receives at least some system data as input to predict the amount of renewable energy generation in the region. An artificial neural network model (not shown) Poetry) may be included.

Meanwhile, the integrated control unit 500 can receive data from the distributed parallel processing unit 600, that is, the data warehousing module 632, visualize the received data, and provide it to the user. At this time, the integrated control unit 500 may receive data directly from the renewable energy control infrastructure 300 without going through the distributed parallel processing unit 600.

As an example, the integrated control unit 500 includes a real-time monitoring module 510, an infrastructure resource monitoring module 520, a distributed parallel resource monitoring module 530, a power facility information management module 540, and a renewable energy monitoring/control process. It may include a management module 550, an infrastructure process management module 560, and a statistics and aggregate information management module 570.

The real-time monitoring module 510 can provide various information necessary for power system management.

As an example, the real-time monitoring module 510 provides real-time renewable power generation comprehensive status information, real-time weather information comprehensive status information, and real-time linkage status information for each line to the user in real time based on the data received from the distributed parallel processing unit 600. You can.

In addition, the real-time monitoring module 510 monitors the status of the SCADA module 210, EMS system 220, distribution automation system (I1), metering data management system (I2), or weather database (I3) and monitors the threshold value ( By setting the collection cycle, speed, I/O, etc.), you can provide an alarm function when the relevant threshold is exceeded.

In addition, the real-time monitoring module 510 can provide a function to monitor Mvar information, controllable capacity information, facility capacity, and weather information appropriate for the type of generator of each renewable energy power generation source in the region.

In addition, the real-time monitoring module 510 can provide a function to monitor voltage, supply capacity, current load, output, etc. for each DL unit generator.

In addition, the real-time monitoring module 510 can provide a function to monitor information on renewable energy power generation sources, current output measurements, output forecast values, weather forecast information, etc.

In addition, the real-time monitoring module 510 may provide real-time event information of renewable energy power generation sources and provide an alarm function when a set threshold value is exceeded or fell below.

In addition, the infrastructure resource monitoring module 520 can provide a function to monitor CPU usage rate, memory usage rate, disk usage rate, RTDB status information, etc. of the configuration within the renewable energy control infrastructure 300.

In addition, the distributed parallel resource monitoring module 530 monitors real-time DISK IO of each component in the distributed parallel processing unit 600. Provides functions to monitor cluster CPU utilization, network IO, and distributed file system (622) IO.

Additionally, the power facility information management module 540 can manage power facility characteristic information, modeling (layer/link) information, and information acquired by the SCADA module 210.

Additionally, the renewable energy monitoring/control process management module 550 can monitor the status of each renewable energy power generation source belonging to each renewable power generation zone in the region. As an example, the renewable energy monitoring/control process management module 550 can monitor real-time power generation information of each renewable energy power generation source collected by the SCADA module 210. As an example, the renewable energy monitoring/control process management module 550 can obtain real-time power generation information of each renewable energy power generation source from grid data.

Additionally, the renewable energy monitoring/control process management module 550 can monitor alarm and event information. At this time, the monitored information can be visualized and provided to the user.

Additionally, the infrastructure process management module 560 provides functions for querying, registering, modifying, deleting, and executing schedules for each component within the renewable energy control infrastructure 300.

Additionally, the statistics and aggregate information management module 570 provides statistical management functions for data collection status, alarm data, event data, and system data.

Meanwhile, the renewable energy detection/control process management module 550 may transmit a control message to the real-time control module 352 in the real-time connection unit 350 of the renewable energy control infrastructure 300. In addition, the real-time control module 352 can transmit a control message to the terminal device of each power generation zone in the region through the control message transmission module 312 in the grid system connection unit 310. At this time, the control message generated by the renewable energy detection/control process management module may be applied with priority over the control command delivered to each renewable energy generation zone in the region, that is, each information collection terminal. As an example, the control message may be applied prior to output control information.

Figure 6 is an example diagram to explain a process in which the renewable energy output prediction module 420 generates output prediction information of a power generation zone in a region according to an embodiment of the present invention.

In FIG. 6 , for convenience of explanation, it will be described as an example that the renewable energy power source located in the power generation area is a wind power source.

First, as shown in (a) of FIG. 6, a step of collecting wind speed and wind power generation data of a renewable energy power source for a certain period of time may be performed. (S510)

At this time, if the renewable energy power generation source is not a wind power generation source, it goes without saying that wind speed and wind power generation data can be replaced with weather data.

Additionally, a step of setting an ARIMAX model and estimating the first power generation amount may be performed based on at least some of the wind speed and wind power generation data among the data collected in step S510. (S520)

Additionally, a step of estimating the second power generation amount may be performed by setting a polynomial regression model based on at least some of the wind speed and wind power generation data among the data collected in step S510. (S530)

In addition, a step of estimating the third power generation amount may be performed based on wind speed data at a point near the renewable energy power generation source. (S540)

In addition, a step of calculating a power generation forecast value based on an analog ensemble may be performed using the first power generation amount, the second power generation amount, the third power generation amount, and past data among the data collected in step S510. (S550)

Figure 6(b) is a flowchart for explaining the process of estimating the third power generation amount in step S540.

As shown in (b) of FIG. 6, a step of collecting wind speed prediction data at a point near a renewable energy power generation source and spatial data near the renewable energy power generation source may be performed. (S541)

Additionally, a step of predicting the wind speed at the location of the renewable energy power generation source may be performed based on the Kriging technique. (S542)

At this time, the wind speed prediction may have been performed in advance by the weather information prediction module 410.

Additionally, a step of correcting wind speed according to altitude may be performed based on the Deacon equation. (S543)

Then, a step of estimating the third power generation amount based on the corrected wind speed may be performed. (S544)

The description of the present invention described above is for illustrative purposes, and those skilled in the art will understand that the present invention can be easily modified into other specific forms without changing the technical idea or essential features of the present invention. will be. Therefore, the embodiments described above should be understood in all respects as illustrative and not restrictive. For example, each component described as unitary may be implemented in a distributed manner, and similarly, components described as distributed may also be implemented in a combined form.

The scope of the present invention is indicated by the claims described below, and all changes or modified forms derived from the meaning and scope of the claims and their equivalent concepts should be construed as being included in the scope of the present invention.

100: Renewable power generation information collection unit 200: System system
300: Renewable energy control infrastructure 400: Application department
500: Integrated control unit 600: Distributed parallel processing unit

Claims (17)

A renewable energy control infrastructure that is connected to a grid system that collects renewable energy power generation information from renewable energy power sources within each renewable energy power generation zone in the region and collects grid data containing the renewable energy power generation information; and
An application unit that communicates with the renewable energy control infrastructure to receive the system data, determines power system stability in the area based on the system data, and generates output control information according to the power system stability. ,
The system collects the renewable energy generation information of the renewable energy power generation source through a plurality of information collection terminals,
The renewable energy control infrastructure controls the amount of renewable energy generation in each renewable energy power generation zone in the region according to the output control information,
Further comprising a distributed parallel processing unit that provides weather data of the region to the renewable energy control infrastructure,
The application department,
a weather prediction module that generates weather prediction information for the renewable energy generation zone based on the weather data;
a renewable energy output prediction module that generates output prediction information of the renewable energy power generation zone based on the weather prediction information and the system data;
Based on power facility characteristic information and power facility information, the exact size and phase angle of the bus voltage are calculated based on the dynamic and static information of the power facility, and based on the calculated values, overload of lines and transformers and bus voltage constraints are determined. Other system analysis modules to detect violations;
A stability evaluation module that generates stability evaluation information of the local power system based on at least two of the output prediction information, state estimation result information, power facility characteristic information, and power facility information;
An acceptance limit evaluation module that generates acceptance limit evaluation information based on the voltage standard violation degree of the local power system, facility and transmission line overload, transient stability, renewable energy LVRT (Low Voltage Ride Through), and fault current size;
Comprising a renewable energy output control module that generates the output control information based on the stability evaluation information and the acceptance limit evaluation information,
A regional renewable energy integrated control system that returns the weather prediction information, the output prediction information, the state estimation result information, the stability evaluation information, the acceptance limit evaluation information, and the output control information to the renewable energy control infrastructure. .
According to paragraph 1,
The system system is a regional renewable energy integrated control system that includes a SCADA (Supervisory Control And Data Acquisition) module that collects the renewable energy generation information by communicating in real time with each of the plurality of information collection terminals.
According to paragraph 2,
The system system includes an EMS (Energy Management System) that collects base power generation data, power facility information, and power facility characteristic information within the region, and the system data is collected by the EMS when collecting the renewable energy power generation information. Include one more data,
The power facility information is information on power facilities connected to the power system in the area,
The power facility characteristic information is information representing the characteristics of each power facility connected to the power system in the region. A regional renewable energy integrated control system.
delete According to paragraph 1,
The renewable energy power generation source is a wind power generation source,
The renewable energy output prediction module collects wind speed and wind power generation data for a certain period of time from the renewable energy power generation source,
Setting an ARIMAX model based on at least some of the wind speed and wind power generation data for the certain period of time to estimate the first power generation,
Estimating the second power generation by setting up a polynomial regression model based on at least some of the wind speed and wind power generation data for the certain period of time,
Estimating the third power generation amount based on wind speed data at a point near the renewable energy power generation source,
Regional renewable energy integration, which generates output prediction information based on an analog ensemble using past wind speed and wind power generation data of the first power generation, the second power generation, the third power generation, and the renewable energy power source. control system.
According to clause 5,
The renewable energy output prediction module is
Collect wind speed prediction data at points near the renewable energy power generation source and spatial data near the renewable energy power generation source,
Predict the wind speed at the location of the renewable energy power generation source based on the Kriging technique,
Correcting the wind speed according to the altitude of the renewable energy power source based on the Deacon equation,
A regional renewable energy integrated control system that estimates the third power generation based on the corrected wind speed.
According to paragraph 1,
The renewable energy management infrastructure includes an infrastructure management unit and an in-memory database unit,
The infrastructure management unit includes an in-memory database management module, an integrated process management module, an alarm/event management module, and a log management module,
The in-memory database management module controls the execution, control, and status management of the in-memory database unit and the processes of modules belonging to the application unit,
The integrated process management module controls the processes of each component in the renewable energy control infrastructure based on the process management information, preset priorities, and current status of each component in the renewable energy control infrastructure, and generates alarms and alarms generated during the control process. Store and handle events,
The alarm/event management module stores and handles alarm and event information generated in the system and transmits the alarm and event information to the integrated control unit and distributed parallel processing unit,
The log management module creates a log file with reference to the process log information stored in the in-memory database unit, records log information in the log file according to the log level, and records the log in the log file at a set period. A regional renewable energy integrated control system that deletes information.
In clause 7,
The renewable energy management infrastructure is,
It is connected to the infrastructure management unit and further includes an infrastructure management information memory that stores the process management information, meta information of the in-memory database, power facility modeling information, power facility characteristic information, and module information of the SCADA module. A regional renewable energy integrated control system.
According to paragraph 1,
The distributed parallel processing unit receives weather data of the region from an external weather database or weather server and provides it to the renewable energy control infrastructure.
According to paragraph 1,
The renewable energy control infrastructure includes a real-time database,
The real-time database is a regional renewable energy integrated control system that stores the system data and information returned from the application unit.
According to clause 10,
The distributed parallel processing unit includes a data collection unit that collects data and information stored in the real-time database;
a data loading unit that distributes the data or information collected in the data collection unit and loads it into a non-relational database or distributed file system;
a data processing and exploration unit that queries the data or information loaded in the data loading unit, converts it into a predetermined format, and warehouses the converted data; and
A regional renewable energy integrated control system comprising a data analysis application unit that secondaryly analyzes the stability of the regional power system.
According to clause 11,
The data collection unit includes a first distributed queue module, a system data collection/loading module, a second distributed queue module, and a weather data collection/loading module,
The first distributed queue module is connected to the real-time database, receives data stored in the real-time database, and pushes it to the system data collection/loading module,
The second distributed queue module is connected to at least one of a distribution automation system, a metering data management system, a weather database, and a weather server, and receives data from the connected component and pushes it to the weather data collection/loading module. Energy integrated control system.
According to clause 11,
The data processing search unit includes an SQL processing engine, an aggregate information generation module, an aggregate information generation history management module, and a data warehousing module,
The SQL processing engine queries data loaded in the non-relational database or the distributed file system and loads it into the data warehousing module,
The aggregate information generation module generates aggregate information of data to be loaded in the non-relational database or distributed file system and loads it into the data warehousing module,
The aggregate information generation history management module is a regional renewable energy integrated control system that generates generation history information, main aggregate and statistical meta information of the aggregate information and loads it into the data warehousing module.
According to clause 13,
The data analysis application unit learns based on data stored in the data warehousing module, and receives at least part of the data loaded in the non-relational database or the distributed file system as input and uses an artificial intelligence to estimate the amount of renewable energy generation in the region. A regional renewable energy integrated control system that includes a neural network model.
According to clause 11,
Further comprising an integrated control unit that receives the data warehoused in the data loading unit and visualizes it to provide it to the user,
The integrated control unit generates a control message according to the user's input, and the control message takes precedence over the output control information and controls the renewable energy generation amount of each renewable energy generation zone in the region. A regional renewable energy integrated control system. .
According to claim 1,
The renewable energy power generation source is connected to an inverter,
The output control information is transmitted to the information collection terminal,
The information collection terminal is a regional renewable energy integrated control system that controls the power generation amount of the renewable energy power source by controlling the inverter.
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