A distributed power quality management method, system and terminal

Abstract

The application relates to a distributed power supply power quality management method and system and a terminal, relates to the technical field of power management, and comprises the following steps: acquiring a grid-connected trigger signal; acquiring output electrical parameters and target sub-network parameters based on the grid-connected trigger signal; judging whether the output electrical parameters meet the requirements of the target sub-network parameters; if yes, defining a corresponding sub-network as a to-be-grid-connected sub-network and acquiring a to-be-grid-connected quantity; judging whether the to-be-grid-connected quantity meets the requirements of a direct grid-connected quantity; if yes, defining the to-be-grid-connected sub-network as an actual grid-connected sub-network; if not, analyzing the output electrical parameters and the target sub-network parameters to determine an adaptability score; analyzing the adaptability score and the corresponding sub-network to determine the actual grid-connected sub-network; and controlling an inverter to grid-connect the distributed power supply to the actual grid-connected sub-network after adjustment. The application has the effect of improving the power management efficiency of the distributed power supply.

Description

Technical Field

[0001] This application relates to the technical field of power management, and in particular to a method, system and terminal for power quality management of distributed power sources. Background Technology

[0002] Distributed power sources refer to efficient and reliable power generation systems with small power outputs located near users. These systems can operate independently or be connected to the public power grid. They typically use renewable energy sources such as solar, wind, biomass, and small-scale hydropower, as well as some traditional energy sources such as natural gas combined cooling, heating, and power systems.

[0003] In related technologies, in order to ensure the success rate of grid connection and reduce disturbance to the grid, when distributed power sources are connected to the grid, they will adjust their output voltage, frequency and phase through inverters or controllers to ensure that the output electrical parameters are strictly synchronized with the parameters of the target grid.

[0004] Regarding the technologies mentioned above, in traditional power distribution networks, distributed power sources are usually connected to fixed nodes, such as nearby distribution transformers. However, the electrical parameters in the power grid are not constant. Therefore, when the electrical parameters in the power grid change significantly, the output adjustment of the distributed power source will be too large, which can easily cause the inverter or controller to adjust in a timely manner, resulting in low power management efficiency of the distributed power source. There is still room for improvement. Summary of the Invention

[0005] To improve the power management efficiency of distributed power sources, this application provides a method, system, and terminal for power quality management of distributed power sources.

[0006] Firstly, this application provides a distributed power source power quality management method, which adopts the following technical solution:

[0007] A method for power quality management of distributed power sources, comprising:

[0008] Obtain the grid connection trigger signal of the preset distributed power source;

[0009] The output electrical parameters of the distributed power source and the target subnet parameters of the preset subnet are obtained based on the grid connection trigger signal.

[0010] Determine whether the output electrical parameters meet the requirements of the target subnet parameters;

[0011] If the target subnet parameters are met, the corresponding subnet is defined as the subnet to be connected to the grid, and the number of subnets to be connected to the grid is obtained.

[0012] Determine whether the number of units to be connected to the grid meets the preset requirements for the number of units to be directly connected to the grid;

[0013] If the requirement for the number of direct grid connections is met, then the subnet to be connected to the grid is defined as the actual grid-connected subnet;

[0014] If the requirements for the number of direct grid connections are not met, the output electrical parameters and target subnet parameters are analyzed to determine the compatibility score of the distributed power source and the subnet.

[0015] If the requirements of the target subnet parameters are not met, the output electrical parameters and target subnet parameters are analyzed to determine the compatibility score of the distributed power source and the subnet.

[0016] The adaptability scores and corresponding subnets are analyzed to determine the actual grid-connected subnets;

[0017] The inverter, controlled by a preset mechanism, adjusts the distributed power source and then connects it to the actual grid-connected subgrid.

[0018] By adopting the above technical solution, when the output electrical parameters meet the requirements of the target subnet parameters and the number of devices to be connected to the grid meets the requirements of the number of devices to be directly connected to the grid, the subnet to be connected to the grid is defined as the actual grid-connected subnet. However, when the output electrical parameters do not meet the requirements of the target subnet parameters, or the number of devices to be connected to the grid does not meet the requirements of the number of devices to be directly connected to the grid, the compatibility score between the distributed power source and the subnet is determined after analyzing the output electrical parameters and the target subnet parameters. The actual grid-connected subnet is obtained by sorting the compatibility scores. This allows the inverter to adjust the power of the distributed power source and connect it to the actual grid-connected subnet, reducing the degree of adjustment required by the inverter for the distributed power source and thus improving the power management efficiency of the distributed power source.

[0019] Optionally, the steps of analyzing the output electrical parameters and target subnet parameters to determine the compatibility score of the distributed generation and subnet include:

[0020] The target subnet parameters and the preset tolerance threshold ratio are analyzed to determine the subnet constraint parameters;

[0021] Determine whether the output electrical parameters meet the requirements of the subnet constraint parameters;

[0022] If it does not meet the requirements, the corresponding subnet will be removed;

[0023] If they match, then the corresponding target subnet parameters are determined to be compliant subnet parameters;

[0024] The output electrical parameters and conformity subnet parameters are analyzed to determine the compatibility score of the distributed power source and the subnet.

[0025] By adopting the above technical solution, when it is determined that the output electrical parameters do not meet the requirements of the subnet constraint parameters, it indicates that a certain dimension parameter of the distributed power source output does not meet the minimum requirements for grid connection. Therefore, the corresponding grid is eliminated, and the target subnet parameters that meet the requirements are defined as compliant subnet parameters. The adaptability score is determined by analyzing the output electrical parameters and compliant subnet parameters, thereby reducing the number of subnets for adaptability scoring and improving the efficiency of determining the adaptability score.

[0026] Optionally, the steps of analyzing the output electrical parameters and conforming subnet parameters to determine the compatibility score of the distributed generation and the subnet include:

[0027] The output electrical parameters and conforming subnet parameters are analyzed to determine the deviation of electrical parameters between the distributed power source and the subnet;

[0028] The deviations of electrical parameters are analyzed to determine the parameter deviation decision matrix;

[0029] The parameter deviation decision matrix and the preset electrical parameter weights are analyzed to determine the weighted standardization matrix;

[0030] The weighted normalization matrix is ​​analyzed to determine the compatibility score of distributed power sources and subnets.

[0031] By adopting the above technical solution, the output electrical parameters and the parameters of the conforming subnet are analyzed and compared in different dimensions to determine the electrical parameter deviation. The electrical parameter deviation is then organized into a parameter deviation decision matrix. Different dimension parameters are assigned weights to the electrical parameters to obtain a weighted standardized matrix, so that electrical parameters of different dimensions occupy corresponding importance proportions, thereby improving the accuracy of determining the suitability score.

[0032] Optionally, the steps of analyzing the weighted normalization matrix to determine the compatibility score of distributed generation and subnet include:

[0033] The weighted normalization matrix is ​​analyzed to determine the positive and negative ideal solutions for the electrical parameters;

[0034] The weighted normalization matrix and the positive ideal solution of the electrical parameters are analyzed to generate the distance between the positive ideal solutions of the electrical parameters;

[0035] The weighted normalization matrix and the negative ideal solution of the electrical parameters are analyzed to generate the distance between the negative ideal solutions of the electrical parameters;

[0036] The distances to the positive and negative electrical ideal solutions are analyzed to generate a fit score.

[0037] By adopting the above technical solution, the distance between the positive ideal solution and the negative ideal solution of the electrical parameters is determined after analyzing the weighted normalized matrix and the positive ideal solution of the electrical parameters. Then, the distance between the negative ideal solution and the negative ideal solution of the electrical parameters is determined after analyzing the weighted normalized matrix and the negative ideal solution of the electrical parameters. By comparing and analyzing the distances between the positive and negative ideal solutions, the fit score is determined, and the accuracy and reliability of the fit score are determined.

[0038] Optionally, the steps of analyzing the distances to the positive and negative electrical ideal solutions to generate a fit score include:

[0039] The distances of the positive and negative electrical ideal solutions are summed to generate the distance of the prime ministerial ideal solution;

[0040] Calculate the quotient between the electrical negative ideal solution distance and the prime minister's ideal solution distance, and define the calculated quotient as the fitness score.

[0041] By adopting the above technical solution, the sum of the electrical positive ideal solution distance and the electrical negative ideal solution distance is calculated to obtain the prime minister's ideal solution distance. Then, the quotient of the electrical negative ideal solution distance and the prime minister's ideal solution distance is calculated to obtain the fit score. The larger the negative ideal solution distance, the smaller the difference between the two, and therefore the higher the fit score, thereby improving the accuracy of the fit score.

[0042] Optionally, after analyzing the output electrical parameters and target subnet parameters to determine the compatibility score of the distributed power source and subnet, a correction step for the compatibility score is also included. Specific steps include:

[0043] Get the rating correction time and historical correction rating;

[0044] Determine whether the score correction time meets the preset baseline correction time requirements;

[0045] If it does not meet the requirements, the historical revised score will be defined as the revised fit score.

[0046] If the conditions are met, then obtain the predicted electrical parameters of the distributed power source and the predicted subnet electrical parameters of the subnet;

[0047] The predicted electrical parameters and predicted subnet electrical parameters are analyzed to determine the adaptability prediction score;

[0048] The fit score is adjusted based on the fit prediction score to generate a revised fit score.

[0049] By adopting the above technical solution, when the score correction time meets the requirements of the benchmark correction time, the predicted electrical parameters and predicted subnet electrical parameters are detected. After analyzing the predicted electrical parameters and predicted subnet electrical parameters, the adaptability prediction score is determined. The adaptability score is then adjusted based on the adaptability prediction score to take into account whether the subnet will match the distributed power source in the future, thereby improving the accuracy of the adaptability score.

[0050] Optionally, the step of adjusting the fit score based on the fit prediction score to generate a revised fit score includes:

[0051] The adaptability score and the preset first allocation weight are analyzed to generate the main adaptability score;

[0052] Obtain the weighted score allocation for the fit prediction score;

[0053] The fit prediction score and score allocation weights are analyzed to generate a subfit score;

[0054] The primary adaptation score and the secondary adaptation score are summed to generate a revised adaptation score.

[0055] By adopting the above technical solution, the adaptation score is adjusted according to the first allocation weight to determine the primary adaptation score, and then the adaptation prediction score is adjusted according to the score allocation weight to obtain the secondary adaptation score. The primary adaptation score and the secondary adaptation score are summed to obtain the adaptation score. The final adaptation score is determined by the importance of the adaptation score at different times, thereby improving the accuracy of the adaptation score.

[0056] Optionally, the steps for obtaining the weighted scores for the fit prediction rating include:

[0057] Obtain the prediction time window for the fit prediction score;

[0058] The prediction time window and preset discount factors are analyzed to generate the weighted score for the suitability prediction score.

[0059] By adopting the above technical solution, the prediction time window is detected, and the scoring allocation weight of the current time window is determined after calculation based on the prediction time window and the discount factor, thereby improving the accuracy of the scoring allocation weight.

[0060] Secondly, this application provides a distributed power source power quality management system, which adopts the following technical solution:

[0061] A distributed power source power quality management system, comprising:

[0062] The acquisition module is used to acquire grid connection trigger signals, output electrical parameters, target subnet parameters, and the number of devices to be connected to the grid.

[0063] A memory for storing a program for a distributed power source power quality management method as described in any of the preceding claims;

[0064] The processor and the program in the memory can be loaded and executed by the processor to implement a distributed power quality management method as described in any of the above.

[0065] By adopting the above technical solution, the processor loads and executes a program for a distributed power source power quality management method stored in the memory. The control acquisition module acquires a series of data related to the distributed power source power quality management. When it is determined that the output electrical parameters meet the requirements of the target subnet parameters and the number of devices to be connected to the grid meets the requirements of the number of devices to be directly connected to the grid, the subnet to be connected to the grid is defined as the actual grid-connected subnet. When the output electrical parameters do not meet the requirements of the target subnet parameters, or the number of devices to be connected to the grid does not meet the requirements of the number of devices to be directly connected to the grid, the compatibility score between the distributed power source and the subnet is determined after analyzing the output electrical parameters and the target subnet parameters. The compatibility scores are then sorted to obtain the actual grid-connected subnets. This allows the inverter to adjust the power of the distributed power source and connect it to the actual grid-connected subnet, reducing the degree of adjustment required by the inverter for the distributed power source and thus improving the power management efficiency of the distributed power source.

[0066] Thirdly, this application provides a smart terminal, which adopts the following technical solution:

[0067] A smart terminal includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as described in any of the preceding claims, a distributed power source power quality management method.

[0068] By adopting the above technical solution, and through the operation of a smart terminal, the processor loads and executes a computer program stored in the memory for a distributed power source power quality management method. When the output electrical parameters meet the requirements of the target subnet parameters, and the number of devices to be connected to the grid meets the requirements of the number of devices to be directly connected, the subnet to be connected to the grid is defined as the actual grid-connected subnet. When the output electrical parameters do not meet the requirements of the target subnet parameters, or the number of devices to be connected to the grid does not meet the requirements of the number of devices to be directly connected, the compatibility score between the distributed power source and the subnet is determined after analyzing the output electrical parameters and the target subnet parameters. The compatibility scores are then ranked to obtain the actual grid-connected subnets. This allows the inverter to adjust the power of the distributed power source before connecting it to the actual grid-connected subnet, reducing the degree of adjustment required by the inverter for the distributed power source and thus improving the power management efficiency of the distributed power source.

[0069] In summary, this application includes at least one of the following beneficial technical effects:

[0070] 1. When the output electrical parameters meet the requirements of the target subnet parameters and the number of devices to be connected to the grid meets the requirements of the number of devices to be directly connected to the grid, the subnet to be connected to the grid is defined as the actual grid-connected subnet. When the output electrical parameters do not meet the requirements of the target subnet parameters, or the number of devices to be connected to the grid does not meet the requirements of the number of devices to be directly connected to the grid, the compatibility score between the distributed power source and the subnet is determined after analyzing the output electrical parameters and the target subnet parameters. The actual grid-connected subnet is obtained by sorting the compatibility scores. This allows the inverter to adjust the power of the distributed power source and connect it to the actual grid-connected subnet, reducing the degree of adjustment required by the inverter for the distributed power source and thus improving the power management efficiency of the distributed power source.

[0071] 2. When it is determined that the output electrical parameters do not meet the requirements of the subnet constraint parameters, it indicates that a certain dimension of the output power of the distributed generation does not meet the minimum requirements for grid connection. Therefore, the corresponding grid is eliminated, and the target subnet parameters that meet the requirements are defined as compliant subnet parameters. The suitability score is determined by analyzing the output electrical parameters and compliant subnet parameters, thereby reducing the number of subnets for suitability scoring and improving the efficiency of determining suitability scores.

[0072] 3. By detecting the predicted electrical parameters and predicted subnet electrical parameters when the score correction time meets the requirements of the benchmark correction time, the adaptability prediction score is determined after analyzing the predicted electrical parameters and predicted subnet electrical parameters. The adaptability score is then adjusted based on the adaptability prediction score to take into account whether the subnet will match the distributed power source in the future, thereby improving the accuracy of the adaptability score. Attached Figure Description

[0073] Figure 1 This is a flowchart of a distributed power source power quality management method according to an embodiment of this application.

[0074] Figure 2 This is a flowchart illustrating the steps in this application embodiment to analyze the output electrical parameters and target subnet parameters to determine the compatibility score of the distributed power source and the subnet.

[0075] Figure 3 This is a flowchart illustrating the steps in this application embodiment to analyze the output electrical parameters and conforming subnet parameters to determine the compatibility score of the distributed power source and the subnet.

[0076] Figure 4 This is a flowchart of the steps in this application embodiment to analyze the weighted normalization matrix to determine the compatibility score of distributed power sources and subnets.

[0077] Figure 5 This is a flowchart of the steps in this application embodiment to analyze the electrical positive ideal solution distance and the electrical negative ideal solution distance to generate a suitability score.

[0078] Figure 6 This is a flowchart of the steps for correcting the adaptability score in the embodiments of this application.

[0079] Figure 7 This is a flowchart illustrating the steps in this application embodiment to adjust the fit score based on the fit prediction score to generate a corrected fit score.

[0080] Figure 8 This is a flowchart of the steps for obtaining the weighting of the fitness prediction score in the embodiments of this application. Detailed Implementation

[0081] To make the purpose, technical solution, and advantages of this application clearer, the following description is provided in conjunction with the appendix. Figures 1 to 8 The present application will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the application.

[0082] This application discloses a distributed power source power quality management method. Specifically, when the processing terminal receives a grid connection trigger signal, the processing terminal responds to the grid connection trigger signal by detecting the output electrical parameters of the distributed power source and the target subnet parameters of the subnet, and compares and analyzes the two. If the output electrical parameters meet the requirements of the target subnet parameters, the corresponding subnet is defined as a subnet to be connected to the grid, and the number of subnets to be connected to the grid is counted. If the number of subnets to be connected to the grid meets the requirements of the number of direct grid connections, the subnet to be connected to the grid is defined as an actual grid-connected subnet. If the output electrical parameters do not meet the requirements of the target subnet parameters, or if the number of subnets to be connected to the grid does not meet the requirements of the number of direct grid connections, the output electrical parameters and the target subnet parameters are analyzed to determine the compatibility score between the distributed power source and the subnet. Based on the compatibility score, the actual grid-connected subnet is determined, and the inverter is controlled to process the power of the distributed power source and connect it to the actual grid-connected subnet, thereby minimizing the degree of adjustment of the distributed power source by the inverter and improving the power management efficiency of the distributed power source.

[0083] Reference Figure 1 This application discloses a method for power quality management of distributed power sources, comprising the following steps:

[0084] Step S100: Obtain the grid connection trigger signal of the preset distributed power source.

[0085] Distributed power sources refer to power generation systems that generate electricity using renewable energy sources such as wind and solar power. Distributed power sources operate independently of the power grid but can be connected to it. The grid connection trigger signal is the signal that triggers the connection between the distributed power source and the power grid, which is input by the operator at the processing terminal.

[0086] Step S101: Obtain the output electrical parameters of the distributed power source and the target subnet parameters of the preset subnet based on the grid connection trigger signal.

[0087] When the processing terminal receives the grid connection trigger signal, it responds to the signal by controlling the corresponding sensors to detect the output electrical parameters of the distributed power source and the target subnet parameters, providing data support for the subsequent determination of the grid-connected subnet.

[0088] A subgrid refers to a power grid in which distributed generation can be connected, such as multiple microgrids in an industrial park. Output electrical parameters refer to the voltage, frequency, and phase of the electrical energy output by the distributed generation. Target subgrid parameters refer to the voltage, frequency, and phase of the subgrid, which are collected in real time by devices such as synchronous phasor measurement units and smart meters deployed at key nodes of the subgrid and distributed generation.

[0089] Step S102: Determine whether the output electrical parameters meet the requirements of the target subnet parameters.

[0090] The requirement for the target subnet parameters refers to them being within the error range of the corresponding parameters of the target subnet. The specific error range is determined by the operator based on the actual situation.

[0091] By processing the terminal to determine whether the voltage, frequency, and phase corresponding to the output electrical parameters are within the error range of the parameters corresponding to the target subnet parameters, it can be determined whether the distributed power source is infinitely close to the parameters of a subnet for direct grid connection.

[0092] Step S1021: If the target subnet parameters are met, the corresponding subnet is defined as the subnet to be connected to the grid, and the number of subnets to be connected to the grid is obtained.

[0093] If the processing terminal determines that the voltage, frequency, and phase corresponding to the output electrical parameters are within the error range of the parameters corresponding to the target subnet parameters, it indicates that the distributed power source is infinitely close to the direct grid connection requirement of a certain subnet. Therefore, the subnet is defined as the subnet to be connected to the grid, and the number of subnets to be connected to the grid is obtained by counting the subnets to be connected to the grid, which provides data support for the subsequent determination of the grid-connected subnets.

[0094] A subnet to be connected to the grid refers to a subnet whose electrical parameters are infinitely close to those of the distributed power source. When the processing terminal determines that the voltage, frequency, and phase corresponding to the output electrical parameters are within the error range of the parameters corresponding to the target subnet, the corresponding subnet is defined as a subnet to be connected to the grid.

[0095] The number of subnets to be connected to the grid refers to the number of subnets to be connected to the grid, which is accumulated by the processing terminal when determining the subnets to be connected to the grid.

[0096] Step S10211: Determine whether the number of grid-connected units meets the preset requirement for the number of direct grid-connected units.

[0097] The number of directly connected subnets refers to the number of subnets that can be directly connected to the distributed power source. In this embodiment, 1 is taken as an example, that is, when there is only one subnet to be connected, the distributed power source can be directly connected to the subnet to be connected. The requirement for the number of directly connected subnets is that it is consistent with the number of directly connected subnets.

[0098] By processing the terminal, it is determined whether the number of subnets to be connected to the grid is consistent with the number of subnets to be directly connected, thereby determining whether the subnets to be connected to the grid can be directly determined.

[0099] Step S102111: If the requirement for the number of direct grid connections is met, then the subnet to be connected is defined as the actual grid-connected subnet.

[0100] If the processing terminal determines that the number of devices to be connected to the grid is the same as the number of devices directly connected to the grid, it indicates that there is only one subnet to be connected to the grid. The distributed power source is infinitely close to the subnet to be connected to the grid. Therefore, the subnet to be connected to the grid is defined as the actual grid-connected subnet, thereby reducing the degree of adjustment of the inverter to the output power of the distributed power source.

[0101] The actual grid-connected subnet refers to the subnet that is actually connected to the distributed power source. In this step, the actual grid-connected subnet is directly defined and determined by the processing terminal based on the subnet to be connected to the grid.

[0102] Step S102112: If the requirement for the number of direct grid connections is not met, the output electrical parameters and target subnet parameters are analyzed to determine the compatibility score of the distributed power source and the subnet.

[0103] If the number of subnets to be connected to the grid determined by the processing terminal is inconsistent with the number to be directly connected, it indicates that there are multiple subnets to be connected. Therefore, the subnet cannot be directly determined. After analyzing the output electrical parameters and target subnet parameters, the compatibility score between the distributed power source and the subnet is determined. The specific method is described in [reference needed]. Figure 2 This step provides data support for subsequently determining the subnet in the grid to be connected that is closest to the distributed power source.

[0104] The adaptability score refers to the degree of matching between the output electrical parameters of the distributed generation source and the electrical parameters of the subnet. The higher the degree of matching between the output electrical parameters of the distributed generation source and the electrical parameters of the subnet, the higher the adaptability score. It is determined by the processing terminal after analyzing the output electrical parameters and the target subnet parameters. For specific methods, please refer to [reference needed]. Figure 2 The steps.

[0105] Step S1022: If the requirements of the target subnet parameters are not met, the output electrical parameters and target subnet parameters are analyzed to determine the compatibility score of the distributed power source and the subnet.

[0106] If the processing terminal determines that the voltage, frequency, and phase corresponding to the output electrical parameters are not within the error range of the parameters corresponding to the target subnet, it indicates that there are differences between the distributed power source and each subnet. Therefore, the output electrical parameters and target subnet parameters are analyzed to determine the compatibility score between the distributed power source and the subnet. The specific method is as follows: Figure 2 This step provides data support for subsequently determining the subnet that is closest to the distributed power source within the subnet.

[0107] The fit score in this step is actually the same as the fit score in step S102112, so it will not be repeated here.

[0108] Step S103: Analyze the adaptability score and the corresponding subnet to determine the actual grid-connected subnet.

[0109] In this step, the actual grid-connected subnet is defined in the same way as the actual grid-connected subnet in step S102111. In this step, the actual grid-connected subnet is sorted by the adaptability score by the processing terminal, and the subnet corresponding to the maximum adaptability score is selected as the actual grid-connected subnet.

[0110] Step S104: Control the preset inverter to adjust the distributed power source and then connect it to the actual grid-connected subgrid.

[0111] In this process, after determining the actual grid-connected subgrid, the processing terminal controls the distributed power source to connect to the actual grid-connected subgrid and controls the inverter to process the electrical energy of the distributed power source, ensuring that the output electrical parameters of the distributed power source match the electrical requirements of the actual grid-connected subgrid, thereby reducing disturbances to the subgrid. An inverter is a power electronic device that adjusts the output electrical parameters of the distributed power source.

[0112] Reference Figure 2 The steps for analyzing the output electrical parameters and target subnet parameters to determine the compatibility score of distributed generation and subnet include:

[0113] Step S200: Analyze the target subnet parameters and the preset tolerance threshold ratio to determine the subnet constraint parameters.

[0114] The tolerance threshold ratio refers to the maximum error range of different parameters that can be connected to the grid. The tolerance threshold ratio is different for different parameters, such as 5% for voltage and 1% for frequency.

[0115] Subnet constraint parameters refer to the minimum required values ​​of different dimension parameters connected to the subnet. The processing terminal calculates the product of the dimension parameter corresponding to the target subnet parameter and the dimension ratio corresponding to the tolerance threshold ratio, and then calculates the difference between the target subnet parameter and the product to obtain the subnet constraint parameters.

[0116] Step S201: Determine whether the output electrical parameters meet the requirements of the subnet constraint parameters.

[0117] The requirement for subnet constraint parameters refers to being within the range of the corresponding dimensional parameters of the subnet constraint parameters. By processing the terminal to determine whether each dimensional parameter of the output electrical parameter pair is within the range of the corresponding dimensional parameters of the subnet constraint parameters, it is possible to determine whether the subnet can be connected to distributed power sources.

[0118] Step S2011: If it does not meet the requirements, the corresponding subnet will be removed.

[0119] If the processing terminal determines that the parameters of each dimension of the output electrical parameter pair are not within the range of the corresponding dimension parameters of the subnet constraint parameters, it indicates that the voltage, frequency or phase of the distributed power source does not meet the minimum access parameters of the subnet. Therefore, the corresponding subnet is removed, thereby reducing the number of subnets for subsequent adaptation score calculation.

[0120] Step S2012: If it matches, then determine that the corresponding target subnet parameters are compliant subnet parameters.

[0121] If the processing terminal determines that all dimensions of the output electrical parameter pair are within the range of the corresponding dimensions of the subnet constraint parameters, it indicates that the voltage, frequency, and phase of the distributed power source meet the minimum access parameters of the subnet. Therefore, the target subnet parameters of the subnet are defined as conforming subnet parameters, providing data support for the subsequent determination of the adaptability score.

[0122] The conforming subnet parameters refer to the electrical parameters of the subnet that can be used for adaptability scoring calculation. When the processing terminal determines that the output electrical parameters of the distributed power source are within the parameter range of the subnet constraint parameters, the processing terminal calls the target subnet parameters of the subnet and defines the target subnet parameters as conforming subnet parameters.

[0123] Step S202: Analyze the output electrical parameters and conforming subnet parameters to determine the compatibility score of the distributed power source and the subnet.

[0124] The compatibility score in this step is consistent with the compatibility scores in steps S102112 and S1022, and is determined by the processing terminal after analyzing the output electrical parameters and conformity subnet parameters. The specific method is as follows: Figure 3 The steps.

[0125] Reference Figure 3 The steps for analyzing the output electrical parameters and conforming subnet parameters to determine the compatibility score of distributed generation and subnet include:

[0126] Step S300: Analyze the output electrical parameters and conforming subnet parameters to determine the deviation of electrical parameters between the distributed power source and the subnet.

[0127] Among them, electrical parameter deviation refers to the parameter deviation values ​​of distributed power source and subnet in voltage, frequency and phase. It is obtained by the processing terminal subtracting the voltage, frequency and phase corresponding to the output electrical parameters and the voltage, frequency and phase corresponding to the subnet parameters respectively.

[0128] Step S301: Analyze the electrical parameter deviations to determine the parameter deviation decision matrix.

[0129] The parameter deviation decision matrix refers to the standard matrix formed by electrical parameter deviations, which is used to calculate the suitability score in the subsequent calculation. First, the parameters corresponding to each electrical parameter deviation are standardized. For example, for voltage deviation, the square root of the sum of the squares of all voltage deviations is first calculated to obtain the standard denominator. Then, all voltage deviations are used as numerators to obtain all standard voltage deviations. The standard frequency deviation and standard phase deviation are obtained by following the same steps. With each column as the same dimension and each row as the same subnet structure, the standard voltage deviation, standard frequency deviation and standard phase deviation are sorted to form the parameter deviation decision matrix.

[0130] Step S302: Analyze the parameter deviation decision matrix and the preset electrical parameter weights to determine the weighted standardization matrix.

[0131] Among them, the weight of electrical parameters refers to the proportion of importance of different electrical parameters in the adaptability score. In the embodiment of this application, the weight of voltage deviation is 0.4, the weight of frequency deviation is 0.3, and the weight of phase deviation is 0.3.

[0132] The weighted standardization matrix is ​​a standard matrix after assigning weights to electrical parameters. The processing terminal multiplies each element in the parameter deviation decision matrix by the corresponding electrical parameter weight to obtain the weighted standardization matrix, thereby ensuring that different electrical parameters have different importance when calculating the suitability score.

[0133] Step S303: Analyze the weighted normalization matrix to determine the compatibility score of distributed power sources and subnets.

[0134] The fit score in this step is the same as the fit score in step S202, and will not be repeated here. It is determined by the processing terminal after analyzing the weighted normalization matrix. The specific method is as follows: Figure 4 The steps.

[0135] Reference Figure 4 The steps for analyzing the weighted normalization matrix to determine the compatibility score of distributed generation and subnet include:

[0136] Step S400: Analyze the weighted normalization matrix to determine the positive ideal solution and the negative ideal solution of the electrical parameters.

[0137] The positive ideal solution for electrical parameters refers to the minimum deviation value of the electrical parameters, such as the minimum voltage deviation, minimum frequency deviation, and minimum phase deviation, which is obtained by the processing terminal identifying the minimum value in each column of the weighted normalization matrix. The negative ideal solution for electrical parameters refers to the maximum deviation value of the electrical parameters, such as the maximum voltage deviation, maximum frequency deviation, and maximum phase deviation, which is obtained by the processing terminal identifying the maximum value in each column of the weighted normalization matrix.

[0138] Step S401: Analyze the weighted normalization matrix and the positive ideal solution of the electrical parameters to generate the distance between the positive ideal solutions of the electrical parameters.

[0139] The electrical positive ideal solution distance refers to the Euclidean distance between the electrical parameter deviation and the positive ideal solution of each subnet and distributed power source. The smaller the electrical positive ideal solution distance, the smaller the electrical deviation between the subnet and the distributed power source. It is obtained by the processing terminal calculating the sum of squares of the differences between each row element in the weighted normalization matrix and the corresponding electrical parameter positive ideal solution, and then taking the square root.

[0140] Step S402: Analyze the weighted normalization matrix and the negative ideal solution of the electrical parameters to generate the distance of the negative ideal solution of the electrical parameters.

[0141] The electrical negative ideal solution distance refers to the Euclidean distance between the electrical parameter deviation between each subnet and the distributed power source and the negative ideal solution. The larger the electrical negative ideal solution distance, the smaller the electrical deviation between the subnet and the distributed power source. It is obtained by taking the square root of the sum of the squares of the differences between each row element in the weighted normalization matrix and the corresponding electrical parameter negative ideal solution.

[0142] Step S403: Analyze the distances to the positive and negative electrical ideal solutions to generate a fit score.

[0143] The adaptability score in this step is consistent with the adaptability score in step S303. It is determined by the processing terminal after calculating and analyzing the electrical positive ideal solution distance and the electrical negative ideal solution distance. The specific analysis method is as follows: Figure 5 The steps.

[0144] Reference Figure 5 The steps for analyzing the distances to the positive and negative electrical ideal solutions to generate a fit score include:

[0145] Step S500: Summate the electrical positive ideal solution distance and the electrical negative ideal solution distance to generate the general ideal solution distance.

[0146] Among them, the ideal solution distance refers to the comprehensive distance between the electrical deviation and the positive and negative ideal solutions, which is obtained by the processing terminal calculating the sum of the electrical positive ideal solution distance and the electrical negative ideal solution distance.

[0147] Step S501: Calculate the quotient between the electrical negative ideal solution distance and the prime ministerial ideal solution distance, and define the calculated quotient as the fitness score.

[0148] In this step, the adaptability score is consistent with that in step S403. It is obtained by the processing terminal by calculating the quotient between the electrical negative ideal solution distance and the electrical positive ideal solution distance. When the electrical negative ideal solution distance is large and the electrical positive ideal solution distance is small, the adaptability score is close to 1, indicating that the subnet is very well adapted to the distributed power source. When the electrical negative ideal solution distance is small but the electrical positive ideal solution distance is large, the adaptability score is close to 0, indicating that the subnet is not well adapted to the distributed power source.

[0149] Reference Figure 6 After analyzing the output electrical parameters and target subnet parameters to determine the compatibility score of the distributed power source and subnet, the process also includes a correction step for the compatibility score. Specific steps include:

[0150] Step S600: Obtain the score correction time and historical score correction.

[0151] The score correction time refers to the interval between the previous correction of the adaptability score and the previous correction time, which is obtained by the processing terminal. The historical correction score refers to the adaptability score calculated last time, which is backed up by the processing terminal and defined as the historical correction score.

[0152] Step S601: Determine whether the scoring correction time meets the preset baseline correction time requirement.

[0153] The baseline correction time refers to the shortest time to correct the fit score once. The specific value is determined by the operator based on the actual situation. The requirement for the baseline rest time is that it should not be less than the baseline correction time.

[0154] The system determines whether the fit score needs to be corrected by processing the terminal to see if the score correction time is not lower than the baseline correction time.

[0155] Step S6011: If it does not meet the requirements, the historical corrected score is defined as the corrected fit score.

[0156] If the processing terminal determines that the score correction time is lower than the baseline correction time, it indicates that it is not yet time to correct the fit score. Therefore, the historical corrected score is defined as the corrected fit score.

[0157] Step S6012: If the conditions are met, obtain the predicted electrical parameters of the distributed power source and the predicted subnet electrical parameters of the subnet.

[0158] If the processing terminal determines that the score correction time is not lower than the baseline correction time, it indicates that the adaptability score has reached the time when correction is required. Therefore, the predicted electrical parameters of the distributed power source and the predicted subnet electrical parameters of the subnet are obtained to provide data support for the subsequent correction of the adaptability score.

[0159] Predicted electrical parameters refer to the predicted electrical parameters of distributed electrical systems over a future period of time, while predicted subgrid electrical parameters refer to the predicted electrical parameters of subgrids over a future period of time. Both are predicted by the processing terminal based on the M-TCN model. Based on a deep learning framework for multivariate time series, the model captures long-term dependencies through dilated convolution and asymmetric residual blocks. In power systems, changes in voltage, frequency, and phase can be regarded as multivariate time series data. The M-TCN model can simultaneously predict parameter changes in multiple future steps through joint training with multivariate inputs.

[0160] Step S602: Analyze the predicted electrical parameters and predicted subnet electrical parameters to determine the adaptability prediction score.

[0161] The adaptability prediction score refers to the degree of adaptability between distributed power sources and subnets within a future timeframe. It is determined by the processing terminal after analyzing the predicted electrical parameters and predicted subnet electrical parameters. The specific method is similar to... Figures 2 to 5 The steps are the same as those in the previous section, so I will not repeat them here.

[0162] Step S603: Adjust the fitness score based on the fitness prediction score to generate a corrected fitness score.

[0163] In this process, after the adaptation prediction score is obtained at the processing terminal, the adaptation prediction score and the actual adaptation score are comprehensively considered to obtain the final corrected adaptation score. The specific method is described in [reference needed]. Figure 7 The steps are to ensure that the matching degree between the subnet and the distributed power supply remains at a high level for a period of time in the future, and to back up the corrected adaptability score as a historical corrected score for future use.

[0164] Reference Figure 7 The steps for adjusting the fit score based on the fit prediction score to generate a revised fit score include:

[0165] Step S700: Analyze the adaptability score and the preset first allocation weight to generate the master adaptability score.

[0166] Wherein, the first allocation weight refers to the proportion of the real-time adaptability score in the final score, which is 1 in this embodiment. The main adaptability score refers to the main adaptability score, which is obtained by the processing terminal by multiplying the adaptability score by the first allocation weight.

[0167] Step S701: Obtain the score allocation weights for the fitness prediction score.

[0168] The weighting allocation refers to the weight of the fit prediction score in the final score. For details on how to obtain this weighting, please refer to [link / reference needed]. Figure 8 The steps.

[0169] Step S702: Analyze the fitness prediction score and the score allocation weights to generate a subfit score.

[0170] The subfit score refers to the score of the predicted fit score in the final score. It is obtained by the processing terminal by multiplying the fit prediction score and the score allocation weight. There are multiple subfit scores.

[0171] Step S703: Sum the primary adaptation score and the secondary adaptation score to generate a corrected adaptation score.

[0172] In this process, after determining the primary adaptation score and the secondary adaptation score, the processing terminal calculates the sum of the primary adaptation score and the secondary adaptation score to obtain the corrected adaptation score.

[0173] Reference Figure 8 The steps for obtaining the weighted scores for the fit prediction rating include:

[0174] Step S800: Obtain the prediction time window for the fitness prediction score.

[0175] The prediction time window refers to the prediction time corresponding to the suitability prediction score. In this embodiment, an integer prediction time is used as an example.

[0176] Step S801: Analyze the prediction time window and the preset discount factor to generate the score allocation weights for the suitability prediction score.

[0177] The discount factor refers to the basic factor that changes the weight over time; in this embodiment, 0.9 is used as an example. The scoring allocation weight in this step is consistent with the scoring allocation weight in step S701. The processing terminal calculates the scoring allocation weight by raising the prediction time window to the power of the discount factor, using the discount factor as the base and the prediction time window as the exponent, thus ensuring that the later the prediction time, the lower the score.

[0178] Based on the same inventive concept, embodiments of this application provide a distributed power supply power quality management system, including:

[0179] The acquisition module is used to acquire grid connection trigger signal, output electrical parameters, target subnet parameters, number of devices to be connected to the grid, score correction time, historical corrected scores, predicted electrical parameters, predicted subnet electrical parameters, score allocation weights, and prediction time window.

[0180] A memory for storing a program for a distributed power source power quality management method;

[0181] The processor can load and execute programs in memory to implement a distributed power quality management method.

[0182] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0183] This application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed as a distributed power supply power quality management method.

[0184] Computer storage media include, for example, USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media that can store program code.

[0185] Based on the same inventive concept, embodiments of this application provide a smart terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded and executed by the processor to provide a distributed power quality management method.

[0186] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0187] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only one example of a series of equivalent or similar features.

Claims

1. A method for power quality management of distributed power sources, characterized in that, include: Obtain the grid connection trigger signal of the preset distributed power source; The output electrical parameters of the distributed power source and the target subnet parameters of the preset subnet are obtained based on the grid connection trigger signal. Determine whether the output electrical parameters meet the requirements of the target subnet parameters; If the target subnet parameters are met, the corresponding subnet is defined as the subnet to be connected to the grid, and the number of subnets to be connected to the grid is obtained. Determine whether the number of units to be connected to the grid meets the preset requirements for the number of units to be directly connected to the grid; If the requirement for the number of direct grid connections is met, then the subnet to be connected to the grid is defined as the actual grid-connected subnet; If the requirements for the number of direct grid connections are not met, the output electrical parameters and target subnet parameters are analyzed to determine the compatibility score of the distributed power source and the subnet. If the requirements of the target subnet parameters are not met, the output electrical parameters and target subnet parameters are analyzed to determine the compatibility score of the distributed power source and the subnet. The adaptability scores and corresponding subnets are analyzed to determine the actual grid-connected subnets; The inverter, controlled by a preset mechanism, adjusts the distributed power source and then connects it to the actual grid-connected subgrid.

2. The distributed power source power quality management method according to claim 1, characterized in that, The steps for analyzing the output electrical parameters and target subnet parameters to determine the compatibility score of the distributed generation and subnet include: The target subnet parameters and the preset tolerance threshold ratio are analyzed to determine the subnet constraint parameters; Determine whether the output electrical parameters meet the requirements of the subnet constraint parameters; If it does not meet the requirements, the corresponding subnet will be removed; If they match, then the corresponding target subnet parameters are determined to be compliant subnet parameters; The output electrical parameters and conformity subnet parameters are analyzed to determine the compatibility score of the distributed power source and the subnet.

3. The distributed power source power quality management method according to claim 2, characterized in that, The steps for analyzing output electrical parameters and conforming subnet parameters to determine the compatibility score of distributed generation and subnet include: The output electrical parameters and conforming subnet parameters are analyzed to determine the deviation of electrical parameters between the distributed power source and the subnet; The deviations of electrical parameters are analyzed to determine the parameter deviation decision matrix; The parameter deviation decision matrix and the preset electrical parameter weights are analyzed to determine the weighted standardization matrix; The weighted normalization matrix is ​​analyzed to determine the compatibility score of distributed power sources and subnets.

4. A distributed power source power quality management method according to claim 3, characterized in that, The steps for analyzing the weighted normalization matrix to determine the compatibility scores of distributed generation and subnets include: The weighted normalization matrix is ​​analyzed to determine the positive and negative ideal solutions for the electrical parameters; The weighted normalization matrix and the positive ideal solution of the electrical parameters are analyzed to generate the distance between the positive ideal solutions of the electrical parameters; The weighted normalization matrix and the negative ideal solution of the electrical parameters are analyzed to generate the distance between the negative ideal solutions of the electrical parameters; The distances to the positive and negative electrical ideal solutions are analyzed to generate a fit score.

5. A distributed power source power quality management method according to claim 4, characterized in that, The steps for analyzing the distances to the positive and negative electrical ideal solutions to generate a fit score include: The distances of the positive and negative electrical ideal solutions are summed to generate the distance of the prime ministerial ideal solution; Calculate the quotient between the electrical negative ideal solution distance and the prime minister's ideal solution distance, and define the calculated quotient as the fitness score.

6. A distributed power source power quality management method according to claim 1, characterized in that, After analyzing the output electrical parameters and target subnet parameters to determine the compatibility score of the distributed power source and subnet, the process also includes a correction step for the compatibility score. Specific steps include: Get the rating correction time and historical correction rating; Determine whether the score correction time meets the preset baseline correction time requirements; If it does not meet the requirements, the historical revised score will be defined as the revised fit score. If the conditions are met, then obtain the predicted electrical parameters of the distributed power source and the predicted subnet electrical parameters of the subnet; The predicted electrical parameters and predicted subnet electrical parameters are analyzed to determine the adaptability prediction score; The fit score is adjusted based on the fit prediction score to generate a revised fit score.

7. A distributed power source power quality management method according to claim 6, characterized in that, The steps for adjusting the fit score based on the fit prediction score to generate a revised fit score include: The adaptability score and the preset first allocation weight are analyzed to generate the main adaptability score; Obtain the weighted score allocation for the fit prediction score; The fit prediction score and score allocation weights are analyzed to generate a subfit score; The primary adaptation score and the secondary adaptation score are summed to generate a revised adaptation score.

8. A distributed power source power quality management method according to claim 7, characterized in that, The steps for obtaining the weighted scores of the fit prediction rating include: Obtain the prediction time window for the fit prediction score; The prediction time window and preset discount factors are analyzed to generate the weighted score for the suitability prediction score.

9. A distributed power source power quality management system, characterized in that, include: The acquisition module is used to acquire grid connection trigger signals, output electrical parameters, target subnet parameters, and the number of devices to be connected to the grid. A memory for storing a program of a distributed power source power quality management method as described in any one of claims 1 to 8; The processor and the program in the memory can be loaded and executed by the processor to implement the distributed power quality management method as described in any one of claims 1 to 8.

10. A smart terminal, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as described in any one of claims 1 to 8, which is a distributed power source power quality management method.

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