A microgrid multi-source coordinated control method and device

Abstract

The present invention is applicable to the technical field of new energy, and provides a microgrid multi-source coordinated control method and device, the microgrid multi-source coordinated control method comprising: obtaining multiple historical power generation corresponding to each of multiple historical control cycles and the median of historical power generation corresponding to each of multiple historical control cycles; calculating the median of power generation in the current control cycle according to the multiple historical power generation and the median of the multiple historical power generation; obtaining the real-time load of the microgrid and the power storage capacity of the energy storage system; calculating the supply and demand balance index according to the median of power generation, the real-time load and the power storage capacity; matching the control strategy of the current control cycle according to the supply and demand balance index. By dynamically adjusting the control strategy, various energy resources can be utilized to the maximum extent, energy utilization efficiency can be improved, and the reliability and quality of power supply can be ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of new energy, and in particular relates to a microgrid multi-source coordinated control method and device. Background Art

[0002] Microgrid is a small power system that integrates renewable energy, energy storage equipment, energy management system and other components. It can operate in grid-connected mode or in island operation (off-grid) mode. Multi-source coordinated control is a key technology to maintain the stable operation of microgrids. Its purpose is to coordinate and control various distributed energy sources, energy storage equipment and loads under different operation modes to improve energy efficiency, ensure the reliability and quality of power supply, and achieve economical and environmentally friendly operation.

[0003] However, microgrid systems are usually composed of multiple distributed energy sources, energy storage devices and loads. Traditional control methods may find it difficult to effectively manage the complexity of the system, resulting in certain limitations in the control system. Summary of the invention

[0004] In view of this, an embodiment of the present invention provides a microgrid multi-source coordinated control method and device to solve the technical problem that traditional control methods may be difficult to effectively manage the complexity of the system, resulting in certain limitations in the control system.

[0005] A first aspect of an embodiment of the present invention provides a microgrid multi-source coordinated control method, the microgrid multi-source coordinated control method comprising:

[0006] Acquire multiple historical power generation amounts corresponding to multiple historical regulation cycles and the median of historical power generation amounts corresponding to multiple historical regulation cycles; the historical regulation cycle refers to a regulation cycle adjacent to the current regulation cycle; the median of historical power generation amounts refers to the median of multiple historical power generation amounts;

[0007] Calculating the median power generation of the current regulation cycle according to the multiple historical power generation and the medians of the multiple historical power generation;

[0008] Obtain the real-time load of the microgrid and the power storage capacity of the energy storage system;

[0009] Calculating a supply-demand balance index according to the median power generation, the real-time load and the power storage;

[0010] According to the supply-demand balance index, the regulation strategy of the current regulation cycle is matched.

[0011] Furthermore, the step of calculating the supply-demand balance index according to the median power generation, the real-time load and the power storage comprises:

[0012] Obtain the current real-time power generation and the upper capacity limit of the energy storage system;

[0013] Substituting the real-time power generation, the capacity upper limit, the median power generation, the real-time load and the power storage into a preset model to obtain the supply-demand balance index;

[0014] The preset model is:

[0015] in, represents the supply-demand balance index, represents the median power generation, represents the real-time power generation at the current time t, represents the real-time load at the current time t. represents the amount of electricity stored at the current time t, represents the upper capacity limit of the energy storage system, , and Represents the weight factor.

[0016] Furthermore, the step of matching the regulation strategy of the current regulation cycle according to the supply-demand balance index includes:

[0017] If the supply-demand balance index is greater than a threshold, power is supplied to the load through multiple distributed energy resources and energy storage systems;

[0018] If the supply-demand balance index is not greater than a threshold, power is supplied to the load and the energy storage system respectively according to the power generation of the multiple distributed energy sources.

[0019] Furthermore, if the supply-demand balance index is not greater than a threshold, the steps of supplying power to the load and the energy storage system respectively according to the power generation of the plurality of distributed energy sources include:

[0020] According to the order of the power generation, the first power generation and the second power generation are added to obtain a first value;

[0021] If the first value is not greater than the real-time load, the first value is added to the third power generation to obtain a second value;

[0022] If the second value is greater than the real-time load, supplying power to the load through the target distributed energy corresponding to the first power generation, the second power generation and the third power generation;

[0023] Power is supplied to the energy storage system through non-targeted distributed energy resources.

[0024] Furthermore, the step of calculating the median power generation of the current regulation cycle according to the multiple historical power generation and the multiple medians of the historical power generation includes:

[0025] Get the pre-trained LSTM model;

[0026] The multiple historical power generation amounts and the multiple medians of the historical power generation amounts are input into different LSTM layers in the LSTM model to obtain the median power generation amount of the current regulation cycle.

[0027] Furthermore, the step of inputting the multiple historical power generation amounts and the multiple medians of the historical power generation amounts into different LSTM layers in the LSTM model to obtain the median power generation amount of the current regulation cycle includes:

[0028] Inputting the plurality of historical power generation amounts into a first LSTM layer to obtain first output data; the first LSTM layer includes a plurality of LSTM units;

[0029] Inputting the medians of the multiple historical power generation amounts into a second LSTM layer to obtain second output data; the second LSTM layer includes multiple LSTM units;

[0030] The first output data and the second output data are input into a third LSTM layer to obtain a median of power generation in a current regulation cycle; the third LSTM layer includes a plurality of LSTM units.

[0031] Furthermore, before the step of obtaining the pre-trained LSTM model, the method further includes:

[0032] Step A1: obtaining a plurality of sample power generation amounts corresponding to a plurality of sample control cycles, a median of the sample power generation amounts corresponding to a plurality of sample control cycles, and a training label;

[0033] Step A2: input multiple sample power generation and multiple sample power generation medians into the initial LSTM model to obtain training results;

[0034] Step A3: calculating the error between the training result and the training label, and adjusting the initial LSTM model according to the error between the training result and the training label;

[0035] Step A4: Based on different sample power generation, sample power generation median and training labels, repeat steps A2 to A3 until a preset number of training times is reached to obtain the pre-trained LSTM model.

[0036] A second aspect of an embodiment of the present invention provides a microgrid multi-source coordinated control device, comprising:

[0037] A first acquisition unit is used to acquire a plurality of historical power generation amounts corresponding to each of a plurality of historical control cycles and a median of historical power generation amounts corresponding to each of a plurality of historical control cycles; the historical control cycle refers to a control cycle adjacent to a current control cycle; the median of historical power generation amounts refers to a median of a plurality of historical power generation amounts;

[0038] A first calculation unit, configured to calculate a median power generation in a current regulation cycle according to the plurality of historical power generation and the medians of the plurality of historical power generation;

[0039] A second acquisition unit is used to acquire the real-time load of the microgrid and the power storage capacity of the energy storage system;

[0040] a second calculation unit, configured to calculate a supply-demand balance index according to the median power generation amount, the real-time load and the power storage amount;

[0041] A matching unit is used to match the control strategy of the current control cycle according to the supply and demand balance index.

[0042] A third aspect of an embodiment of the present invention provides a terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method described in the first aspect when executing the computer program.

[0043] A fourth aspect of an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in the first aspect are implemented.

[0044] Compared with the prior art, the embodiment of the present invention has the beneficial effect of: using multiple historical control cycles and power generation data, as well as real-time load and power storage of the energy storage system, the control strategy of the current control cycle is determined by calculating and matching the supply and demand balance index. Specifically, the method first obtains multiple historical power generation corresponding to each of the multiple historical control cycles and the median of the historical power generation corresponding to each of the multiple historical control cycles. The historical control cycle here refers to the control cycle adjacent to the current control cycle, and the median of the historical power generation refers to the median of multiple historical power generation. Then, according to these historical data, the median of the power generation of the current control cycle is calculated. At the same time, the real-time load of the microgrid and the power storage of the energy storage system are obtained. Then, the supply and demand balance index is calculated by combining the median of the power generation, the real-time load and the power storage to reflect the current supply and demand situation. Finally, according to the obtained supply and demand balance index, the control strategy suitable for the current control cycle is matched, so as to achieve stable operation of the microgrid system and optimize energy utilization. Since the power generation data has a certain regularity, the median of the power generation of the current cycle is predicted based on the control cycle. However, the regularity of the load demand is weak and there is a large mutation, so the real-time load is used for calculation. The above technical solution comprehensively considers historical data and real-time information, can more accurately predict and respond to fluctuations in energy supply and demand, and improves the response speed and stability of the microgrid system. At the same time, by dynamically adjusting the control strategy, various energy resources can be utilized to the maximum extent, energy utilization efficiency can be improved, and the reliability and quality of power supply can be ensured. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0046] Figure 1 A schematic flow chart of a microgrid multi-source coordinated control method provided by the present invention is shown;

[0047] Figure 2 A schematic diagram of a microgrid multi-source coordinated control device provided by an embodiment of the present invention is shown;

[0048] Figure 3 A schematic diagram of a terminal device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0049] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0050] In view of this, an embodiment of the present invention provides a microgrid multi-source coordinated control method and device to solve the technical problem of improving the stability of power supply.

[0051] First, the present invention provides a multi-source coordinated control method for a microgrid. Figure 1 , Figure 1 FIG. 1 is a schematic flow chart of a microgrid multi-source coordinated control method provided by the present invention. Figure 1 As shown, the microgrid multi-source coordinated control method may include the following steps:

[0052] Step 101: obtaining a plurality of historical power generation amounts corresponding to a plurality of historical control cycles and a median of historical power generation amounts corresponding to a plurality of historical control cycles; the historical control cycle refers to a control cycle adjacent to a current control cycle; the median of historical power generation amounts refers to a median of a plurality of historical power generation amounts;

[0053] The control cycle is a preset time parameter, and a control process needs to be executed once in each control cycle. The length of the control cycle can be preset based on actual control requirements or control accuracy, and is not limited here.

[0054] Among them, the number of multiple historical power generation is greater than the median number of historical power generation.

[0055] Step 102: Calculate the median power generation of the current regulation cycle according to the multiple historical power generation and the medians of the multiple historical power generation;

[0056] The traditional power generation forecasting method only predicts through multiple historical power generation. In order to improve the prediction accuracy, this application obtains the median of historical power generation of multiple historical regulation cycles and combines multiple historical power generation for comprehensive prediction, which improves the data dimension and thus improves the prediction accuracy. The specific power generation forecasting logic is as follows:

[0057] Specifically, step 102 specifically includes step 1021 to step 1022:

[0058] Step 1021: Obtain a pre-trained LSTM model;

[0059] Step 1022: Input the multiple historical power generation and the multiple medians of the historical power generation into different LSTM layers in the LSTM model to obtain the median power generation of the current regulation cycle.

[0060] By using a pre-trained long short-term memory (LSTM) model, the time series characteristics of power generation data can be effectively captured. The LSTM model can learn and remember long-term dependencies in historical data, thereby making more accurate predictions of the median power generation. By inputting historical power generation data and median data into different LSTM layers, this technical solution can process and analyze data in real time and quickly obtain the median power generation of the current regulation cycle. This instant computing power is very important for power grid operation and management that requires real-time adjustment of power generation strategies. In traditional power generation forecasting, only the time series data of historical power generation is often used, while this technical solution also considers the median of historical power generation, which is a more comprehensive use of historical data. By combining more relevant data features, the LSTM model can provide more comprehensive and accurate predictions. Since the historical median is taken into account when predicting the median power generation of the current regulation cycle, this method is more resistant to the impact of outliers (such as sudden changes in power generation caused by extreme weather) than the average. The median is insensitive to outliers and can provide more robust prediction results, thereby enhancing the stability and reliability of the power grid. In summary, the above technical solution uses the pre-trained LSTM model to comprehensively consider historical power generation and its median data, which can provide real-time, accurate and robust median power forecasts, providing an effective technical support for grid regulation.

[0061] Specifically, step 1022 specifically includes steps B1 to B3:

[0062] Step B1: inputting the plurality of historical power generation amounts into a first LSTM layer to obtain first output data; the first LSTM layer includes a plurality of LSTM units;

[0063] Step B2: inputting the medians of the multiple historical power generation into the second LSTM layer to obtain second output data; the second LSTM layer includes multiple LSTM units;

[0064] Step B3: input the first output data and the second output data into the third LSTM layer to obtain the median power generation of the current regulation cycle; the third LSTM layer includes multiple LSTM units.

[0065] It is worth noting that the first LSTM layer and the second LSTM layer process at different time scales (between regulation cycles and within regulation cycles). Then, the processing results corresponding to different time scales are input into the third LSTM layer to increase the data dimension and thus improve the processing accuracy.

[0066] Multiple historical power generation data are input into the first layer of LSTM, which contains multiple LSTM units to capture the long-term and short-term dependencies of time series data. This step aims to extract the features of historical power generation data. The median of historical power generation is input into the second layer of LSTM, which also contains multiple LSTM units. The role of this layer is to model the trend and fluctuation of historical power generation in order to better predict the future median. The output data of the first and second layers are merged and input into the third layer of LSTM. The third layer of LSTM also contains multiple LSTM units, whose task is to integrate the features and trends of historical power generation data to generate the prediction results of the median power generation in the current regulation cycle. In this way, the historical power generation data and its statistical characteristics can be fully utilized to more accurately predict the median power generation in the current regulation cycle, providing an important reference for the regulation and operation of the power system.

[0067] As an optional embodiment of the present application, before step 1021, steps A1 to A4 are also included:

[0068] Step A1: obtaining a plurality of sample power generation amounts corresponding to a plurality of sample control cycles, a median of the sample power generation amounts corresponding to a plurality of sample control cycles, and a training label;

[0069] Step A2: input multiple sample power generation and multiple sample power generation medians into the initial LSTM model to obtain training results;

[0070] Step A3: calculating the error between the training result and the training label, and adjusting the initial LSTM model according to the error between the training result and the training label;

[0071] Step A4: Based on different sample power generation, sample power generation median and training labels, repeat steps A2 to A3 until a preset number of training times is reached to obtain the pre-trained LSTM model.

[0072] Collect the power generation data of multiple samples, extract the power generation under the corresponding multiple regulation cycles and the median of the sample power generation for each sample, and use these data as input features and training labels. Then, input these sample power generation data and medians into the initial LSTM model for training to obtain preliminary training results. Subsequently, calculate the error between the training result and the training label, and adjust the initial LSTM model accordingly to improve its performance. The entire training process is repeated until the preset number of training times is reached. Finally, a pre-trained and perfect LSTM model is obtained, which can effectively predict the changing trend of sample power generation under different regulation cycles. The advantage of this technical solution is that it makes full use of the data information of multiple samples, and continuously optimizes the model performance by gradually adjusting the model parameters, thereby improving the prediction accuracy and generalization ability of the LSTM model.

[0073] Step 103: Obtain the real-time load of the microgrid and the power storage capacity of the energy storage system;

[0074] The power storage capacity of an energy storage system refers to the current real-time power storage capacity in the storage system.

[0075] Step 104: Calculating a supply-demand balance index according to the median power generation, the real-time load and the power storage capacity;

[0076] Specifically, step 104 specifically includes: obtaining the real-time power generation at the current moment and the upper limit of the capacity of the energy storage system;

[0077] Substituting the real-time power generation, the capacity upper limit, the median power generation, the real-time load and the power storage into a preset model to obtain the supply-demand balance index;

[0078] The preset model is:

[0079]

[0080] in, represents the supply-demand balance index, represents the median power generation, represents the real-time power generation at the current time t, represents the real-time load at the current time t, represents the amount of electricity stored at the current time t, represents the upper capacity limit of the energy storage system, , and Represents the weight factor.

[0081] It is worth noting that the calculation of the supply and demand balance index , which is used to reflect the real-time supply and demand status of the power system. The larger the supply and demand balance index, the greater the load demand. The smaller the supply and demand balance index, the smaller the load demand.

[0082] The above formula evaluates the adequacy of power generation by comparing the difference between actual power generation and median power generation. If the actual power generation is close to or reaches the lower limit, the value of this part is high, reflecting the potential tension of the power supply system. The above formula compares the power storage with the upper limit of the storage capacity to reflect the utilization of power storage. If the power storage is close to or reaches the upper limit of the storage capacity, the value of this part is high, indicating that the utilization rate of the energy storage system is high. The above formula compares the real-time load with the actual power generation to evaluate the match between supply and demand in the power system. If the gap between load and power generation is small, the value of this part is high, indicating that the balance between supply and demand is better.

[0083] Step 105: Matching the control strategy of the current control cycle according to the supply-demand balance index.

[0084] Specifically, step 105 specifically includes step 1051 to step 1052:

[0085] Step 1051: If the supply-demand balance index is greater than a threshold, powering the load through multiple distributed energy resources and energy storage systems;

[0086] Step 1052: If the supply-demand balance index is not greater than the threshold, power is supplied to the load and the energy storage system respectively according to the power generation of the multiple distributed energy sources.

[0087] When the supply-demand balance index is greater than a given threshold, the strategy of using multiple distributed energy sources and energy storage systems to jointly supply power to the load can maximize the use of distributed energy sources, such as solar energy, wind energy and other renewable energy sources. This can not only reduce dependence on traditional fossil energy and reduce environmental pollution, but also improve energy utilization and reduce energy waste.

[0088] When the supply-demand balance index is not greater than the threshold, the strategy of supplying power to the load and the energy storage system respectively can achieve accurate power supply scheduling according to the size of the power generation of multiple distributed energy sources. Supplying power to the load can meet the user's immediate power demand, while supplying power to the energy storage system can provide peak load regulation for the power grid, ensuring the stable operation of the power grid during peak load periods or when distributed energy generation is insufficient.

[0089] This strategy can achieve efficient management of power resources, optimize the power supply structure, and improve the reliability and flexibility of the power grid. In addition, through intelligent power supply management, this technical solution can respond to changes in power grid load and adjust power generation and energy storage strategies in real time, thereby achieving the dual goals of economic operation and environmental protection while ensuring power grid security.

[0090] Specifically, step 1052 specifically includes steps C1 to C4:

[0091] Step C1: according to the order of power generation, add the first power generation and the second power generation to obtain a first value;

[0092] Step C2: if the first value is not greater than the real-time load, the first value is added to the third power generation to obtain a second value;

[0093] Step C3: if the second value is greater than the real-time load, supplying power to the load through the target distributed energy corresponding to the first power generation, the second power generation and the third power generation;

[0094] Sufficient power supply is ensured by supplying power with a power supply greater than the real-time load. The power generation is added up in order of power generation, and the target distributed energy is found by the size relationship between the real-time load and the addition result. The target distributed energy can not only supply sufficient power resources, but also avoid excessive power supply, which leads to power reverse flow.

[0095] Step C4: Supply power to the energy storage system through non-target distributed energy resources.

[0096] Non-target distributed energy refers to all distributed energy sources except target distributed energy sources.

[0097] This technical solution dynamically adjusts the order of power generation to achieve a balance between supply and demand. First, the power generation of multiple distributed energy sources is arranged in order of size. Then, the first power generation is added to the second power generation to obtain a first value. If the first value is not greater than the real-time load, the first value is added to the third power generation to obtain a second value. If the second value is greater than the real-time load, the target distributed energy corresponding to the first power generation, the second power generation, and the third power generation is used to supply power to the load to meet the real-time load demand; at the same time, the non-target distributed energy is used to supply power to the energy storage system to achieve energy storage and balanced utilization. Through this technical solution, it is possible to effectively respond to fluctuations in supply and demand, improve energy utilization efficiency, and achieve flexibility and sustainability in energy supply.

[0098] In this embodiment, multiple historical control cycles and power generation data, as well as real-time load and power storage capacity of the energy storage system, are used to determine the control strategy of the current control cycle by calculating and matching the supply and demand balance index. Specifically, the method first obtains multiple historical power generation corresponding to each of the multiple historical control cycles and the median of the historical power generation corresponding to each of the multiple historical control cycles. The historical control cycle here refers to the control cycle adjacent to the current control cycle, and the median of the historical power generation refers to the median of multiple historical power generation. Then, based on these historical data, the median of the power generation of the current control cycle is calculated. At the same time, the real-time load of the microgrid and the power storage capacity of the energy storage system are obtained. Then, the supply and demand balance index is calculated by combining the median of the power generation, the real-time load and the power storage capacity to reflect the current supply and demand situation. Finally, according to the obtained supply and demand balance index, the control strategy suitable for the current control cycle is matched, so as to achieve stable operation of the microgrid system and optimize energy utilization. Since the power generation data has a certain regularity, the median of the power generation of the current cycle is predicted based on the control cycle. However, the regularity of the load demand is weak and there is a large mutation, so the real-time load is used for calculation. The above technical solution comprehensively considers historical data and real-time information, can more accurately predict and respond to fluctuations in energy supply and demand, and improves the response speed and stability of the microgrid system. At the same time, by dynamically adjusting the control strategy, various energy resources can be utilized to the maximum extent, energy utilization efficiency can be improved, and the reliability and quality of power supply can be ensured.

[0099] like Figure 2 The present invention provides a microgrid multi-source coordinated control device 2, see Figure 2 , Figure 2 A schematic diagram of a microgrid multi-source coordinated control device provided by the present invention is shown in FIG. Figure 2 A microgrid multi-source coordinated control device is shown, comprising:

[0100] The first acquisition unit 21 is used to acquire a plurality of historical power generation amounts corresponding to each of a plurality of historical control cycles and a median of historical power generation amounts corresponding to each of a plurality of historical control cycles; the historical control cycle refers to a control cycle adjacent to a current control cycle; the median of historical power generation amounts refers to a median of a plurality of historical power generation amounts;

[0101] A first calculation unit 22, configured to calculate a median power generation in a current regulation cycle according to the plurality of historical power generation and the medians of the plurality of historical power generation;

[0102] A second acquisition unit 23 is used to acquire the real-time load of the microgrid and the power storage capacity of the energy storage system;

[0103] A second calculation unit 24 is used to calculate a supply-demand balance index according to the median power generation, the real-time load and the power storage capacity;

[0104] The matching unit 25 is used to match the control strategy of the current control cycle according to the supply and demand balance index.

[0105] The present invention provides a microgrid multi-source coordinated control device, which uses multiple historical control cycles and power generation data, as well as real-time loads and the power storage capacity of energy storage systems, to determine the control strategy of the current control cycle by calculating and matching the supply and demand balance index. Specifically, the method first obtains multiple historical power generation corresponding to multiple historical control cycles and the median of historical power generation corresponding to multiple historical control cycles. The historical control cycle here refers to the control cycle adjacent to the current control cycle, and the median of historical power generation refers to the median of multiple historical power generation. Then, according to these historical data, the median of power generation in the current control cycle is calculated. At the same time, the real-time load of the microgrid and the power storage capacity of the energy storage system are obtained. Then, the supply and demand balance index is calculated by combining the median of power generation, real-time load and power storage to reflect the current supply and demand situation. Finally, according to the obtained supply and demand balance index, the control strategy suitable for the current control cycle is matched, so as to achieve stable operation of the microgrid system and optimize energy utilization. Since the power generation data has a certain regularity, the median of power generation in the current cycle is predicted based on the control cycle. However, the regularity of load demand is weak and there is a large mutation, so the real-time load is used for calculation. The above technical solution comprehensively considers historical data and real-time information, can more accurately predict and respond to fluctuations in energy supply and demand, and improves the response speed and stability of the microgrid system. At the same time, by dynamically adjusting the control strategy, various energy resources can be utilized to the maximum extent, energy utilization efficiency can be improved, and the reliability and quality of power supply can be ensured.

[0106] Figure 3 Schematic diagram of a terminal device provided by an embodiment of the present invention. Figure 3 As shown, a terminal device 3 of this embodiment includes: a processor 30, a memory 31, and a computer program 32 stored in the memory 31 and executable on the processor 30, such as a program for multi-source coordinated control of a microgrid. When the processor 30 executes the computer program 32, the steps in each of the above-mentioned embodiments of the multi-source coordinated control method of a microgrid are implemented, such as Figure 1 Alternatively, when the processor 30 executes the computer program 32, the functions of each unit in the above-mentioned device embodiments are realized, for example, Figure 2 Function of the unit shown.

[0107] Exemplarily, the computer program 32 may be divided into one or more units, which are stored in the memory 31 and executed by the processor 30 to complete the present invention. The one or more units may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program 32 in the terminal device 3. For example, the computer program 32 may be divided into the following specific functions of each unit:

[0108] A first acquisition unit is used to acquire a plurality of historical power generation amounts corresponding to each of a plurality of historical control cycles and a median of historical power generation amounts corresponding to each of a plurality of historical control cycles; the historical control cycle refers to a control cycle adjacent to a current control cycle; the median of historical power generation amounts refers to a median of a plurality of historical power generation amounts;

[0109] A first calculation unit, configured to calculate a median power generation in a current regulation cycle according to the plurality of historical power generation and the medians of the plurality of historical power generation;

[0110] A second acquisition unit is used to acquire the real-time load of the microgrid and the power storage capacity of the energy storage system;

[0111] a second calculation unit, configured to calculate a supply-demand balance index according to the median power generation amount, the real-time load and the power storage amount;

[0112] A matching unit is used to match the control strategy of the current control cycle according to the supply and demand balance index.

[0113] The terminal device includes but is not limited to a processor 30 and a memory 31. Those skilled in the art will appreciate that Figure 3 It is only an example of a terminal device 3 and does not constitute a limitation on the terminal device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal device may also include input and output devices, network access devices, buses, etc.

[0114] The processor 30 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0115] The memory 31 may be an internal storage unit of the terminal device 3, such as a hard disk or memory of the terminal device 3. The memory 31 may also be an external storage device of the terminal device 3, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal device 3. Further, the memory 31 may also include both an internal storage unit and an external storage device of the terminal device 3. The memory 31 is used to store the computer program and other programs and data required by the roaming control device. The memory 31 may also be used to temporarily store data that has been output or is to be output.

[0116] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0117] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present invention. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0118] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0119] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0120] An embodiment of the present invention provides a computer program product. When the computer program product runs on a mobile terminal, the mobile terminal can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0121] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device that can carry the computer program code to the camera device / terminal device, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a disk or an optical disk.

[0122] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0123] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0124] In the embodiments provided by the present invention, it should be understood that the disclosed devices / network equipment and methods can be implemented in other ways. For example, the device / network equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0125] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed over multiple network units.

[0126] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0127] It should also be understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0128] As used in the present specification and the appended claims, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to monitoring, depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is monitored" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is monitored" or "in response to monitoring [described condition or event]", depending on the context.

[0129] In addition, in the description of the present specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0130] References to "one embodiment" or "some embodiments" etc. described in the present specification mean that one or more embodiments of the present invention include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0131] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A microgrid multi-source coordinated control method, characterized in that: The microgrid multi-source coordinated control method comprises: Acquire multiple historical power generation amounts corresponding to multiple historical regulation cycles and the median of historical power generation amounts corresponding to multiple historical regulation cycles; the historical regulation cycle refers to a regulation cycle adjacent to the current regulation cycle; the median of historical power generation amounts refers to the median of multiple historical power generation amounts; Calculating the median power generation of the current regulation cycle according to the multiple historical power generation and the medians of the multiple historical power generation; Obtain the real-time load of the microgrid and the power storage capacity of the energy storage system; Obtain the current real-time power generation and the upper capacity limit of the energy storage system; Substitute the real-time power generation, capacity upper limit, median power generation, real-time load and power storage into the preset model to obtain the supply and demand balance index; The preset model is: in, represents the supply-demand balance index, represents the median power generation, represents the real-time power generation at the current time t, represents the real-time load at the current time t, represents the amount of electricity stored at the current time t, represents the upper capacity limit of the energy storage system, , and represents the weight factor; According to the supply-demand balance index, the regulation strategy of the current regulation cycle is matched.

2. The microgrid multi-source coordinated control method according to claim 1, characterized in that: The step of matching the control strategy of the current control cycle according to the supply and demand balance index comprises: If the supply-demand balance index is greater than a threshold, power is supplied to the load through multiple distributed energy resources and energy storage systems; If the supply-demand balance index is not greater than a threshold, power is supplied to the load and the energy storage system respectively according to the power generation of the multiple distributed energy sources.

3. The microgrid multi-source coordinated control method according to claim 2, characterized in that: If the supply-demand balance index is not greater than a threshold, the steps of supplying power to the load and the energy storage system respectively according to the power generation of the plurality of distributed energy sources include: According to the order of the power generation, the first power generation and the second power generation are added to obtain a first value; If the first value is not greater than the real-time load, the first value is added to the third power generation to obtain a second value; If the second value is greater than the real-time load, supplying power to the load through the target distributed energy corresponding to the first power generation, the second power generation and the third power generation; Power is supplied to the energy storage system through non-targeted distributed energy resources.

4. The microgrid multi-source coordinated control method according to claim 1, characterized in that: The step of calculating the median power generation of the current regulation cycle according to the multiple historical power generation and the multiple medians of the historical power generation comprises: Get the pre-trained LSTM model; The multiple historical power generation amounts and the multiple medians of the historical power generation amounts are input into different LSTM layers in the LSTM model to obtain the median power generation amount of the current regulation cycle.

5. The microgrid multi-source coordinated control method according to claim 4, characterized in that: The step of inputting the multiple historical power generation amounts and the multiple medians of the historical power generation amounts into different LSTM layers in the LSTM model to obtain the median power generation amount in the current regulation cycle includes: Inputting the plurality of historical power generation amounts into a first LSTM layer to obtain first output data; the first LSTM layer includes a plurality of LSTM units; Inputting the medians of the multiple historical power generation amounts into a second LSTM layer to obtain second output data; the second LSTM layer includes multiple LSTM units; The first output data and the second output data are input into a third LSTM layer to obtain a median of power generation in a current regulation cycle; the third LSTM layer includes a plurality of LSTM units.

6. The microgrid multi-source coordinated control method according to claim 4, characterized in that: Before the step of obtaining the pre-trained LSTM model, the following steps are also included: Step A1: obtaining a plurality of sample power generation amounts corresponding to a plurality of sample control cycles, a median of the sample power generation amounts corresponding to a plurality of sample control cycles, and a training label; Step A2: input multiple sample power generation and multiple sample power generation medians into the initial LSTM model to obtain training results; Step A3: calculating the error between the training result and the training label, and adjusting the initial LSTM model according to the error between the training result and the training label; Step A4: Based on different sample power generation, sample power generation median and training labels, repeat steps A2 to A3 until a preset number of training times is reached to obtain the pre-trained LSTM model.

7. A microgrid multi-source coordinated control device, characterized in that: The microgrid multi-source coordinated control device comprises: A first acquisition unit is used to acquire a plurality of historical power generation amounts corresponding to each of a plurality of historical control cycles and a median of historical power generation amounts corresponding to each of a plurality of historical control cycles; the historical control cycle refers to a control cycle adjacent to a current control cycle; the median of historical power generation amounts refers to a median of a plurality of historical power generation amounts; A first calculation unit, configured to calculate a median power generation in a current regulation cycle according to the plurality of historical power generation and the medians of the plurality of historical power generation; A second acquisition unit is used to acquire the real-time load of the microgrid and the power storage capacity of the energy storage system; The second calculation unit is used to obtain the real-time power generation and the upper limit of the capacity of the energy storage system at the current moment; Substitute the real-time power generation, capacity upper limit, median power generation, real-time load and power storage into the preset model to obtain the supply and demand balance index; The preset model is: in, represents the supply-demand balance index, represents the median power generation, represents the real-time power generation at the current time t, represents the real-time load at the current time t, represents the amount of electricity stored at the current time t, represents the upper capacity limit of the energy storage system, , and represents the weight factor; A matching unit is used to match the control strategy of the current control cycle according to the supply and demand balance index.

8. A terminal device, characterized in that: The device comprises: a memory, a processor, and a load control program stored in the memory and executable on the processor, wherein the load control program is configured to implement the microgrid multi-source coordinated control steps as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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