Photovoltaic energy storage system coordinated control method

Abstract

The present application relates to the technical field of power grid data processing, in particular to a photovoltaic energy storage system coordinated control method, comprising the following steps: obtaining power grid topology and line parameters, establishing a power grid admittance matrix, calculating the voltage variation caused by the injection of unit reactive power between any two photovoltaic energy storage system nodes, grouping all photovoltaic energy storage system nodes to obtain a coordinated voltage regulation partition set. The present application establishes a power grid admittance matrix by obtaining power grid topology and line parameters, and calculates the voltage variation caused by the injection of unit reactive power between any two photovoltaic energy storage system nodes, thereby obtaining node voltage sensitivity, and then clearly defining the electrical coupling relationship between nodes, so as to accurately group the nodes and establish a coordinated voltage regulation partition set, making the coordinated control between photovoltaic energy storage system nodes more explicit.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid data processing, and in particular to a coordinated control method for a photovoltaic energy storage system. Background Art

[0002] The coordinated control of photovoltaic energy storage systems is mainly used to coordinate the real-time output of multiple photovoltaic energy storage systems and the charge status of energy storage units when power congestion or voltage fluctuations occur in the power grid.

[0003] Existing technologies directly coordinate the real-time output of each PV energy storage system and the state of charge of the energy storage unit, without establishing a voltage sensitivity model. This results in the actual electrical influence of the node being ignored, and the coordination ability between nodes is assessed only at a macro level, failing to quantify node responsibility. Furthermore, when power flow management tasks occur, only the overall available power of the energy storage equipment is used for rough scheduling, resulting in low scheduling accuracy and failure to fully tap the potential of power flow management, making it difficult to effectively resolve local line congestion in the power grid. Therefore, improvements are needed. Summary of the Invention

[0004] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a coordinated control method for a photovoltaic energy storage system.

[0005] To achieve the above objectives, the present invention adopts the following technical solution, a photovoltaic energy storage system coordinated control method, comprising the following steps:

[0006] Obtain the grid topology and line parameters, establish the grid admittance matrix, calculate the voltage change caused by unit reactive power injection between any two PV energy storage system nodes, group all PV energy storage system nodes, and obtain a set of coordinated voltage regulation partitions;

[0007] Based on the coordinated voltage regulation zone set, the real-time photovoltaic output fluctuation data and the energy storage unit charge state of each photovoltaic energy storage system in each zone are read to obtain the aggregate adjustable power range within the zone, and then the zone coordinated response weight set is established based on the aggregate adjustable power range within the zone;

[0008] Obtain the power transfer distribution factor matrix and congested line identifiers from the grid dispatch center, extract the power transfer distribution factor values ​​of each PV energy storage system's partitioned grid connection point relative to the congested line, and obtain a set of power transfer distribution factors. This set of power transfer distribution factors is then calculated with the partitioned adjustable power to determine the maximum collaborative power flow diversion potential.

[0009] Based on the maximum collaborative power flow diversion potential and the partition collaborative response weight set, an energy storage unit power instruction sequence is generated.

[0010] Preferably, the steps of obtaining the coordinated voltage regulation partition set are:

[0011] obtaining the topological connection relationship of all nodes in the power grid and the electrical parameters of the corresponding lines, calculating the self-impedance and mutual-impedance of the lines one by one according to the topological connection relationship and the electrical parameters of the lines, constructing the power grid impedance matrix based on the self-impedance and mutual-impedance of the lines, and generating the power grid impedance matrix;

[0012] based on the power grid impedance matrix, injecting unit reactive power to each photovoltaic energy storage system node in turn, calculating and recording the voltage variation amplitude of all other nodes in the power grid when the unit reactive power is injected into the node, and obtaining the voltage variation value between nodes;

[0013] based on the voltage variation value between nodes, statistically calculating the voltage variation between each photovoltaic energy storage system node, setting a screening threshold for the voltage variation, classifying the nodes whose voltage variation reaches or exceeds the screening threshold into the same group, and forming a collaborative voltage regulation partition set.

[0014] Preferably, the step of obtaining the aggregated adjustable power range in the partition is:

[0015] based on the collaborative voltage regulation partition set, accessing each photovoltaic energy storage system in each partition one by one, collecting real-time photovoltaic output fluctuation data and state of charge values of the corresponding energy storage units of each photovoltaic energy storage system, and forming a real-time photovoltaic output fluctuation data and energy storage unit state of charge value set;

[0016] based on the real-time photovoltaic output fluctuation data and energy storage unit state of charge value set, calculating the maximum and minimum active power values and the maximum and minimum reactive power values of each photovoltaic energy storage system under the current state, and forming adjustable active and reactive power limits of each photovoltaic energy storage system;

[0017] based on the adjustable active and reactive power limits of each photovoltaic energy storage system, aggregating and calculating the adjustable active power limit sum and the adjustable reactive power limit sum of all photovoltaic energy storage systems in each partition respectively, and forming the aggregated adjustable power range in the partition.

[0018] Preferably, the step of obtaining the partition collaborative response weight set is:

[0019] based on the aggregated adjustable power range in the partition, reading the maximum active power, minimum active power, maximum reactive power and minimum reactive power of each photovoltaic energy storage system in the partition in turn, and synchronously retrieving the voltage variation amplitude of all other nodes in the partition when unit reactive power is injected into the node, and integrating to form a power regulation boundary and node voltage sensitivity value set of photovoltaic energy storage systems in the partition;

[0020] According to the power regulation boundary of the photovoltaic energy storage system in the subarea and the set of node voltage sensitivity values, the collaborative response weight of the photovoltaic energy storage system is calculated;

[0021] Based on the collaborative response weight of the photovoltaic energy storage system, the collaborative response weight results of all photovoltaic energy storage systems in the subarea are summarized and arranged according to the subarea to which the photovoltaic energy storage system belongs, and a set of subarea collaborative response weights is formed.

[0022] Preferably, the step of obtaining the set of power transmission distribution factors is:

[0023] The complete power transmission distribution factor matrix and the identification of the target congested line in the regulation state are called from the power grid dispatching center, the column vector of each photovoltaic energy storage system subarea grid-connected point relative to the target congested line is screened, and a set of power transmission distribution factors is generated.

[0024] Preferably, the step of obtaining the maximum collaborative power flow dredging potential is:

[0025] Based on the set of power transmission distribution factors, the current active power value, the maximum adjustable active power value and the minimum adjustable active power value of all members in each photovoltaic energy storage system subarea are read, and the up-regulation active power difference and the down-regulation active power difference in the same subarea are summed respectively, and a directional adjustable active power pair of the subarea is formed.

[0026] Based on the directional adjustable active power pair of the subarea, the maximum collaborative power flow dredging potential of the target line is calculated.

[0027] Preferably, the step of obtaining the power instruction sequence of the energy storage unit is:

[0028] The total amount of the power flow dredging task that needs to be completed by the target line is obtained from the power grid dispatching center, and the maximum collaborative power flow dredging potential is called, the contribution value provided by each photovoltaic energy storage system subarea in the process of calculating the maximum collaborative power flow dredging potential is extracted one by one, and the ratio of the contribution value of the subarea to the maximum collaborative power flow dredging potential is taken as the contribution proportion of the subarea, the power dredging instruction allocated to each photovoltaic energy storage system subarea is determined according to the contribution proportion, and the power dredging instruction of the subarea is generated.

[0029] Based on the power dredging instruction of the subarea, the set of subarea collaborative response weights is called and the collaborative response weight of each photovoltaic energy storage system in each subarea is extracted one by one, the collaborative response weight of each photovoltaic energy storage system is divided by the sum of the collaborative response weights of all photovoltaic energy storage systems in the subarea in turn, the normalization processing of the weights in the subarea is completed, and the power dredging instruction of the subarea is subdivided to each photovoltaic energy storage system in the subarea according to the weight values after the normalization processing, and the initial power instruction of each photovoltaic energy storage system is generated.

[0030] Preferably, the step of obtaining the power instruction sequence of the energy storage unit further comprises: based on the initial power instruction of each photovoltaic energy storage system, the state of charge of the current energy storage unit of the corresponding photovoltaic energy storage system and the adjustable active power range of the real-time inverter are retrieved one by one, and it is compared whether the initial power instruction falls within the adjustable active power range of the real-time inverter; if the initial power instruction exceeds the range, the boundary value of the adjustable active power range of the real-time inverter is taken as the corrected power instruction of the photovoltaic energy storage system; after all the corrections are completed, the determined corrected power instruction is issued to the inverter of the corresponding photovoltaic energy storage system, and the power instruction sequence of the energy storage unit is generated.

[0031] Compared with the prior art, the application has the advantages and positive effects that:

[0032] The application obtains the admittance matrix of the power grid by acquiring the topology and line parameters of the power grid, and calculates the voltage variation caused by the injection of unit reactive power between any two photovoltaic energy storage system nodes, thereby obtaining the node voltage sensitivity and explicitly determining the electrical coupling relationship between the nodes, so as to accurately group the nodes and establish the coordinated voltage regulation partition set, making the coordinated control between the photovoltaic energy storage system nodes more explicit; further, the aggregated adjustable power range of each partition is determined by combining the real-time photovoltaic output fluctuation data and the state of charge of the energy storage unit in the partition, and the partition coordinated response weight set is constructed based on the aggregated adjustable power range, so as to realize the quantification of the coordinated response capability of each node and eliminate the disadvantages of fuzzy node adjustment responsibility in the partition; the power transmission distribution factor is calculated in coordination with the partition adjustable power, the actual dredging potential of each partition to the congested line is analyzed, and the power instruction of the energy storage unit is accurately distributed based on the maximum coordinated power flow dredging potential and the partition coordinated response weight, so as to optimize the power dispatching strategy, improve the power flow dredging efficiency, realize the fine-grained control of the photovoltaic energy storage system dispatching decision between partitions and within partitions, and improve the stability of the power grid and the utilization efficiency of renewable energy. BRIEF DESCRIPTION OF DRAWINGS

[0033] Figure 1 The figure is a schematic diagram of the steps of the application. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical scheme and advantages of the application more clear, the application is further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the application and do not limit the application.

[0035] Please refer to Figure 1 The application provides a technical scheme, a photovoltaic energy storage system coordinated control method, comprising the following steps:

[0036] Obtain the topology and line parameters of the power grid, establish the admittance matrix of the power grid, calculate the voltage variation caused by the injection of unit reactive power between any two photovoltaic energy storage system nodes, group all photovoltaic energy storage system nodes, and obtain a coordinated voltage regulation partition set;

[0037] Based on the coordinated voltage regulation partition set, read the real-time photovoltaic output fluctuation data and state of charge of the energy storage unit of each photovoltaic energy storage system in each partition to obtain the aggregated adjustable power range in the partition, and then establish a partition coordinated response weight set according to the aggregated adjustable power range in the partition;

[0038] Obtain the power transmission distribution factor matrix and congested line identifier from the power grid dispatching center, extract the power transmission distribution factor value of the grid-connected point of each photovoltaic energy storage system partition relative to the congested line, obtain a power transmission distribution factor set, and operate the power transmission distribution factor set and the partition adjustable power to determine the maximum coordinated power flow dredging potential;

[0039] Based on the maximum coordinated power flow dredging potential and the partition coordinated response weight set, generate a power instruction sequence for the energy storage unit.

[0040] The acquisition step of the coordinated voltage regulation partition set is as follows:

[0041] Obtain the topology connection relationship of all nodes in the power grid and the electrical parameters of the corresponding lines, calculate the self-admittance and mutual admittance of each line according to the topology connection relationship and the electrical parameters of the lines, construct the admittance matrix of the power grid based on the self-admittance and mutual admittance of the lines, and generate the admittance matrix of the power grid;

[0042] Based on the admittance matrix of the power grid, inject unit reactive power into each photovoltaic energy storage system node in turn, calculate and record the voltage variation amplitude of all other nodes in the power grid when unit reactive power is injected into the node, and obtain the voltage variation value between nodes;

[0043] Based on the voltage variation value between nodes, the voltage variation between photovoltaic energy storage system nodes is calculated node by node, a screening threshold of node voltage variation is set, nodes with voltage variation reaching or exceeding the screening threshold are classified into the same group, and a coordinated voltage regulation partition set is formed.

[0044] Specifically, based on the obtained topology connection relationship of all nodes in the power grid and the electrical parameters of the corresponding lines, first, these basic data are analyzed to clearly identify the unique identifier of each node (such as power plant, substation, load center) and the starting and ending nodes connected by each transmission line, and the key electrical parameters of the line are extracted, including the resistance value, reactance value and ground admittance value per unit length of the line. Multiply these parameters by the length of the line to obtain the total resistance , total reactance and total admittance , then, traverse each transmission line in the grid topology, calculate the series impedance of the line according to its total resistance and total reactance , and get the series admittance of the line by taking the inverse of the series impedance , for the ground admittance of each line, it is equivalent to two π-type equivalent circuits in parallel branches located at both ends of the line, each end is allocated half of the total line admittance value, that is , after completing the calculation of all line parameters, start to build a grid admittance matrix with dimensions, where is the total number of nodes in the grid, each element of the matrix is filled by the following rules: for the non-diagonal elements of the matrix ( ), its value is the inverse of the sum of all branch admittances connecting node and node , that is , if there is no direct line connection between node and node , then is 0, for the diagonal elements of the matrix , the value is the sum of the admittance of all branches connected to node and the parallel admittance of the node to the ground, the calculation formula is where, is the branch admittance between node and node , indicates grounding, by repeating this calculation process for all nodes, the filling of the entire matrix is completed, and the grid admittance matrix is finally obtained.

[0045] Based on the grid admittance matrix generated in the previous process, to determine the electrical coupling strength between the nodes of each photovoltaic energy storage system, it is necessary to calculate the voltage sensitivity, first, perform the inverse operation on the grid admittance matrix to obtain the grid impedance matrix which is one-to-one corresponding to the grid admittance matrix, each element of the impedance matrix has the physical meaning of the voltage response at node when a unit current is injected into node , then identify all nodes in the grid that deploy photovoltaic energy storage systems and create a node list, then perform simulation calculation of unit reactive power injection for each photovoltaic energy storage system node in the list in turn, the specific operation is that when the th photovoltaic energy storage system node is analyzed, set a reactive power increment with an amplitude of 1 per unit value injected into the node, that is , in power system load flow calculation, the complex power injected by the node is related to the node voltage and the injected current The relationship is , from which the change in node injection current can be derived and reactive power variation In the common case where the system voltage amplitude is close to 1 per unit, the relationship can be approximated as , so, to the node Injecting unit reactive power is approximately equivalent to injecting a current of 1 per unit and a phase of -90 degrees into the node. Then, the grid impedance matrix is ​​used to calculate the voltage change caused by this injection on all other nodes in the grid. For any node , the voltage change It can be calculated by the corresponding elements of the impedance matrix: Since the injected reactive power is unit, the calculated voltage change amplitude is That is the node For Node Voltage sensitivity coefficient ,Right now Repeat the above injection and calculation process for each photovoltaic energy storage system node in the list, and record the voltage change amplitude of all other nodes in the grid (especially other photovoltaic energy storage system nodes) during each injection, and compile all these calculation results into a The matrix of is the number of photovoltaic energy storage system nodes, is the total number of nodes in the power grid, and this matrix is ​​the voltage change value between each node.

[0046] Based on the voltage change values ​​between nodes obtained in the previous steps, i.e., the voltage sensitivity matrix, the PV energy storage system needs to be grouped to form partitions. First, from the complete voltage sensitivity matrix, a sub-matrix involving only the mutual influence between the nodes of the PV energy storage system is extracted. The dimension of this sub-matrix is , where the elements Indicates in The unit reactive power injected by each photovoltaic energy storage system node is The voltage variation amplitude caused by each photovoltaic energy storage system node is then divided into areas with close electrical coupling. A clear screening threshold for node voltage variation needs to be set. The setting of this threshold adopts statistical methods to ensure its rationality. Specifically, the voltage variation values ​​between all different photovoltaic energy storage system node pairs (i.e. All a set of values, calculate the arithmetic mean and the standard deviation of all values in the set, for example, if the average is 0.045 and the standard deviation is 0.02, the screening threshold can be set as the average plus a preset multiple of the standard deviation, such as "average + 1.5 times standard deviation", that is The threshold is used as the basis for determining whether two nodes belong to the same strong coupling region. Subsequently, a graph theory-based connected component search algorithm is used for grouping. Each photovoltaic energy storage system node is regarded as a vertex of a graph, and all pairs of photovoltaic energy storage system nodes are traversed If the mutual voltage variation between them Or At least one of them reaches or exceeds the set screening threshold 0.075, an edge is added between the vertices representing the two nodes, indicating that there is a strong electrical coupling relationship between them. When all node pairs have been judged and all edges have been constructed, the entire photovoltaic energy storage system network forms an undirected graph. Finally, a depth-first search or breadth-first search algorithm is applied to find all connected components in the graph. Each independent connected component represents a coordinated voltage regulation partition, and all nodes contained in it form the members of a partition. All found connected components are aggregated to obtain the set of coordinated voltage regulation partitions.

[0047] The acquisition steps of the aggregated adjustable power range in the partition are as follows:

[0048] Based on the set of coordinated voltage regulation partitions, each photovoltaic energy storage system in each partition is accessed, and real-time photovoltaic output fluctuation data and state of charge values of the corresponding energy storage unit of each photovoltaic energy storage system are collected to form a set of real-time photovoltaic output fluctuation data and state of charge values.

[0049] Based on the set of real-time photovoltaic output fluctuation data and state of charge values, the maximum and minimum active power values and the maximum and minimum reactive power values that can be adjusted by each photovoltaic energy storage system under the current state are calculated one by one to form adjustable active and reactive power limits of each photovoltaic energy storage system.

[0050] Based on the adjustable active and reactive power limits of each photovoltaic energy storage system, the adjustable active power limit sum and the adjustable reactive power limit sum of all photovoltaic energy storage systems in each partition are aggregated and calculated respectively to form the aggregated adjustable power range in the partition.

[0051] Specifically, based on the coordinated voltage regulation partition set, the system first establishes a connection with the local monitoring unit or energy management system (EMS) of each photovoltaic energy storage system in the partition according to the partition identifier through a pre-set communication network address list. The connection adopts Modbus or IEC 61850 MMS protocol based on TCP / IP to ensure the real-time and reliability of data transmission. For each photovoltaic energy storage system, a data acquisition task is triggered to execute at a fixed time period, for example, every 5 seconds. In each acquisition period, the system requests two types of core data from the target photovoltaic energy storage system: the first type is the real-time power output of the photovoltaic array, which is acquired by querying the DC side or AC side power metering point of the grid-connected inverter within a 1-second window period, for example, [510kW, 512kW, 509kW, 513kW, 511kW] is acquired, and the standard deviation of the 5 sample points is calculated, and the obtained value (about 1.58kW in this example) is defined as the photovoltaic output fluctuation data at the current time; the second type is the state of charge (SOC) value of the energy storage unit, which is obtained by directly querying the corresponding data register of the battery management system (BMS), for example, 85.5% is read. These acquired raw data are attached with a time stamp and a unique device identification code before transmission, and are aggregated to the central computing node through the communication link. After receiving the data, the central node will classify them into corresponding photovoltaic energy storage systems according to the unique device identification code, and preliminarily arrange them according to the partition information, and compile the photovoltaic output fluctuation data and the state of charge value of all members in the same partition within the same acquisition period to form a real-time photovoltaic output fluctuation data and state of charge value set.

[0052] Based on the real-time photovoltaic output fluctuation data and state of charge value set, the system calls the pre-configured device profile parameters of each photovoltaic energy storage system in the set, which includes the rated apparent power of the inverter , the rated capacity of the energy storage unit , the maximum charge / discharge rate , and the upper and lower limits of the state of charge for safe operation (for example, , ). First, the regulation range of active power is calculated, the maximum adjustable active power depends on the sum of the current photovoltaic output and the maximum discharge power of the energy storage unit , wherein is the smaller value of the rated power of the energy storage unit and the current state of charge allowable discharge power, which is the power calculated to prevent the SOC from being lower than in the next scheduling period (for example, 15 minutes), and the minimum adjustable active power PV output Subtract the maximum charging power of the energy storage unit Get the maximum active power limit of the PV energy storage system Similarly, limited by the rated charging power and the power limit to prevent SOC from exceeding , then calculate the adjustment range of reactive power, which is closely related to the current system active power output, the maximum adjustable reactive power and the minimum adjustable reactive power determined by the PQ capability curve of the inverter, the calculation formula is: Where, is the current total active power output of the PV energy storage system, that is, Therefore, And For example, a PV energy storage system inverter rated apparent power is 1.2 MVA, the current PV output is 0.8 MW, the SOC of the energy storage unit is 60%, and the maximum charging and discharging power is 0.5 MW, then its maximum active power limit is But limited by the rated power of the inverter, the actual output cannot exceed 1.2 MW, its minimum active power limit is Its maximum reactive power limit is The minimum reactive power limit is -0.89 MVar, and the system performs this set of calculations for each PV energy storage system to finally obtain the adjustable active and reactive power limits of each PV energy storage system.

[0053] Based on the adjustable active and reactive power limits of each PV energy storage system, the system calls the coordinated voltage regulation partition set generated in the previous step to perform power aggregation operation in partition units. This process is executed by traversing each partition in the coordinated voltage regulation partition set. For the th partition being processed, the system first extracts the unique identifier list of all PV energy storage system members contained in the partition from the partition definition, then according to this list, queries and extracts the 、 、 and four values of all these members from the adjustable active and reactive power limit set of each PV energy storage system, and then performs partition-level aggregation calculation. The aggregated maximum adjustable active power of the partition is obtained by algebraic summation of the of all members in the partition, that is, Similarly, the aggregated minimum adjustable active power of the partition , the aggregated maximum adjustable reactive power and the aggregated minimum adjustable reactive power The sum of the limits corresponding to all members in the partition is also calculated, for example, a certain partition contains two photovoltaic energy storage systems A and B, the adjustable active power limit of system A is [0.3 MW, 1.2 MW], the adjustable reactive power limit is [-0.89 MVar, 0.89 MVar], the adjustable active power limit of system B is [0.2 MW, 1.0 MW], and the adjustable reactive power limit is [-0.6 MVar, 0.6 MVar], then the sum of the aggregated adjustable active power limits of the partition is [0.5 MW, 2.2 MW], and the sum of the aggregated adjustable reactive power limits is [-1.49 MVar, 1.49 MVar], the system sequentially completes this aggregation calculation for all partitions, and stores the four aggregated limit values of each partition in association with the partition identifier, forming the aggregated adjustable power range in the partition.

[0054] The acquisition step of the partition collaborative response weight set is:

[0055] Based on the aggregated adjustable power range in the partition, the maximum active power, the minimum active power, the maximum reactive power and the minimum reactive power of each photovoltaic energy storage system in the partition are sequentially read, and the voltage change amplitude generated by the injection of unit reactive power by all other nodes in the partition is synchronously retrieved, and the power adjustment boundary of the photovoltaic energy storage system in the partition and the node voltage sensitivity value set are integrated;

[0056] According to the power adjustment boundary of the photovoltaic energy storage system in the partition and the node voltage sensitivity value set, the collaborative response weight of the photovoltaic energy storage system is calculated, and the calculation formula is:

[0057] ;

[0058] Among them, is the collaborative response weight of the i-th photovoltaic energy storage system, is the maximum active power limit of the i-th photovoltaic energy storage system, is the minimum active power limit of the i-th photovoltaic energy storage system, is the maximum reactive power limit of the i-th photovoltaic energy storage system, is the minimum reactive power limit of the i-th photovoltaic energy storage system, is the voltage change amplitude generated by the injection of unit reactive power by the i-th photovoltaic energy storage system node to the j-th node, is the voltage change amplitude generated by the injection of unit reactive power by the i-th photovoltaic energy storage system node to the j-th node, is the voltage change amplitude generated by the injection of unit reactive power by the i-th photovoltaic energy storage system node to the j-th node, is the voltage change amplitude generated by the injection of unit reactive power by the i-th photovoltaic energy storage system node to the j-th node, is the voltage change amplitude generated by the injection of unit reactive power by the i-th photovoltaic energy storage system node to the j-th node, is the voltage change amplitude generated by the injection of unit reactive power by the i-th photovoltaic energy storage system node to the j-th node, is the voltage change amplitude generated by the injection of unit reactive power by the i-th photovoltaic energy storage system node to the j-th node, is the voltage change amplitude generated by the injection of unit reactive power by the i-th photovoltaic energy storage system node to the j-th node, is the voltage change amplitude generated by the injection of unit reactive power by the i-th photovoltaic energy storage system node to the j-th node, is the voltage change amplitude generated by the injection of unit reactive power by the i-th photovoltaic energy storage system node to the j-th node, The voltage change amplitude generated when a node injects unit reactive power, is the total number of photovoltaic energy storage systems in the zone, is the power regulation capability evaluation index, It is the electrical impact assessment index;

[0059] Based on the coordinated response weights of the photovoltaic energy storage systems, the coordinated response weight results of all photovoltaic energy storage systems in the partition are summarized and sorted item by item according to the partition to which they belong, forming a partition coordinated response weight set.

[0060] Specifically, based on the coordinated voltage regulation partition set, the data integration process is started. First, each partition identifier in the partition set is traversed. For each partition, the system obtains the unique device addresses of all photovoltaic energy storage systems from its member list. Then, the system uses these addresses to extract the maximum active power of each member system from the "adjustable active and reactive power limits of each photovoltaic energy storage system" data set calculated and stored in the previous step. , minimum active power , maximum reactive power and minimum reactive power These four key power regulation boundary parameters, while extracting the power boundary parameters, the system performs a parallel query operation to retrieve the "voltage change value between each node" matrix calculated and stored at an earlier stage, for any photovoltaic energy storage system in the partition , the system will traverse all other member systems in the partition (in ), and find and extract the corresponding voltage sensitivity value from the voltage change value matrix , that is, node When unit reactive power is injected at the node This process ensures that only the electrical coupling relationship between the internal members of the partition is considered, while the impact on the nodes outside the partition is ignored. All the power regulation boundary parameters and internal node voltage sensitivity values ​​extracted for the photovoltaic energy storage systems in the same partition are organized together to form a temporary data structure. For example, for partition 1, which contains systems A, B, and C, a data structure containing four power limits for A, B, and C will be formed, as well as 、 、 、 、 、 By repeatedly executing this data extraction and pairing process for all partitions, the data packets of all internal sensitivity values ​​are finally integrated to form the power regulation boundary and node voltage sensitivity value set of the photovoltaic energy storage system in the partition.

[0061] Formula: ;

[0062] The benefit of the formula is that the modulus of the two-dimensional vector composed of the active and reactive power adjustment range, i.e. , comprehensively measures the comprehensive adjustment margin of each photovoltaic energy storage system in the power plane, avoiding the one-sidedness of evaluating the active or reactive power alone. Secondly, by calculating the average voltage sensitivity of the photovoltaic energy storage system to all other nodes in the partition, i.e. , the electrical influence of the photovoltaic energy storage system in the partition is depicted. Thirdly, adjustable evaluation indexes and are introduced, so that the grid dispatchers can flexibly adjust the weights of the two indexes according to the current operation target of the power grid (for example, prioritizing power balance or prioritizing voltage stability). Finally, through normalization processing (divided by the sum of the evaluation values of all members in the partition), the relative and fair weights are ensured.

[0063] , , , The acquisition steps of represent the adjustable power boundaries of the first photovoltaic energy storage system, which are not directly set but dynamically calculated according to the aforementioned step "based on the real-time photovoltaic output fluctuation data and the state of charge value set of the energy storage unit, the maximum and minimum active power values and the maximum and minimum reactive power values that each photovoltaic energy storage system can adjust under the current state are calculated one by one". These values are directly read from the "adjustable active and reactive power limits of each photovoltaic energy storage system" data set generated by this step for the currently processed photovoltaic energy storage system , for example, in the example, for photovoltaic energy storage system A in a certain partition, the current adjustable power limits are obtained by querying: the maximum active power , the minimum active power , the maximum reactive power , and the minimum reactive power These values reflect the true adjustment potential of the device under the current working condition.

[0064] The acquisition step of represents the voltage sensitivity of the first The voltage sensitivity, which is the voltage variation amplitude when a node injects a unit of reactive power, is derived from the matrix of voltage variation values between nodes generated in the early step of injecting a unit of reactive power to each PV-ES node and recording the voltage variation of all other nodes. When calculating the weight of a specific subzone, the system extracts the voltage sensitivity values between all internal members of the subzone from the matrix. For example, when calculating the weight of system A in a subzone containing systems A, B, and C, the voltage sensitivity of B and C to A is needed, which can be obtained by querying , ;

[0065] The acquisition step of the parameter, which represents the total number of PV-ES systems in the current subzone, is to count the number of elements in the member list of a specific subzone in the collaborative voltage regulation subzone set. For example, if the current subzone contains PV-ES systems A, B, and C, the system reads the member list of the subzone and counts the number of elements to obtain ;

[0066] and The acquisition step of the two parameters, power regulation capability evaluation index and electrical influence evaluation index, is to determine their values based on the grid operation strategy and optimize them through offline simulation analysis. The specific setting process is as follows: construct a series of typical grid operation scenarios (such as load peak, PV high output, line light load, etc.), in each scenario, set a group of initial values for and (e.g. , ), run the coordination control simulation, and evaluate the control effect, including voltage out-of-limit rate, power fluctuation suppression effect, and regulation response speed, then adjust the values of and within the preset range (e.g. 0.5 to 2.0) using grid search or gradient descent optimization algorithm, repeat the simulation and evaluation until a set of and values are found that can make the comprehensive evaluation index optimal. In this example, it is set that , , which means that the power regulation capability and electrical influence are considered equally important.

[0067] Calculation process:

[0068] Taking a subzone containing three PV-ES systems A, B, and C as an example, the collaborative response weight of each system is calculated , the known parameters are as follows:

[0069] System A: , , , ;

[0070] System B: , , , ;

[0071] System C: , , , ;

[0072] Voltage sensitivity: , , , , , ;

[0073] Total number of systems in the partition , evaluation index , ;

[0074] First, calculate the unnormalized evaluation value (i.e., the numerator of the formula) for each system separately:

[0075] For System A:

[0076] Power regulation capability items: ;

[0077] Electrical impact items: ;

[0078] Evaluation value of system A: ;

[0079] For System B:

[0080] Power regulation capability items: ;

[0081] Evaluation value of system B: ;

[0082] For System C:

[0083] Power regulation capability items: ;

[0084] Electrical impact items: ;

[0085] Evaluation value of system C: ;

[0086] Then, the normalization denominator (i.e. the sum of all system evaluation values) is calculated:

[0087] Denominator = ;

[0088] Finally, the synergistic response weight of each system is calculated:

[0089] ;

[0090] ;

[0091] ;

[0092] The result shows that the synergistic response weights of systems A, B and C in this partition are 0.3297, 0.2638 and 0.4065 respectively, these values are dimensionless relative weights, and their sum is 1, among them, the weight of system C is the highest, which means that its comprehensive adjustment ability and electrical influence are the best among the three, and it should undertake the largest proportion of tasks in the subsequent power instruction allocation, and the weight of system B is the lowest, which means that it undertakes the smallest proportion of adjustment tasks, these calculated weight values are the synergistic response weights of the photovoltaic energy storage system.

[0093] Based on the synergistic response weights of the photovoltaic energy storage system calculated in the previous step, the system starts the generation program of the weight set, the goal of this program is to create a structured data collection to store the weight allocation results of all partitions, the program first initializes an empty data structure as the final output, that is, the partition synergistic response weight set, then the program starts to traverse each partition in the synergistic pressure partition set one by one, for the specific partition being processed, the system has obtained the synergistic response weight values of all photovoltaic energy storage system members in this partition, for example, for partition 1, the weights of its members A, B and C are calculated as 0.3297, 0.2638 and 0.4065 respectively, the program takes the unique identifier of this partition (for example, "Partition_1") as the primary key, and takes the "device ID-weight value" pairs of all members in this partition (for example, {"System_A": 0.3297, "System_B": 0.2638, "System_C": 0.4065}) as the values associated with this primary key, then this complete "partition-weight list" entry is stored in the partition synergistic response weight set initialized before, this process is repeated constantly, and the program will continue to process partition 2, partition 3, until all partitions in the synergistic pressure partition set are processed, and their respective weight allocation results are all collected and sorted in a unified format into the final set, forming the partition synergistic response weight set.

[0094] The obtaining step of the power transmission distribution factor set is:

[0095] The complete power transmission distribution factor matrix and the target congested line identification in the control state are called from the power grid dispatching center, the column vectors of each photovoltaic energy storage system partition and the grid connection point relative to the target congested line are screened, and the power transmission distribution factor set is generated.

[0096] Specifically, through the MMS secure communication link established with the energy management system (EMS) of the power grid dispatching center based on the IEC 61850 standard, a data request is initiated to call the complete power transmission distribution factor (PTDF) matrix stored on the server in the dispatching center and the identification of the target congested line currently in the real-time monitoring and control state, wherein the complete power transmission distribution factor matrix is a large sparse matrix calculated offline in advance, the row index corresponds to the unique number of all power transmission lines in the power grid, the column index corresponds to the unique number of all power grid nodes, and the matrix element represents the contribution of the node injecting unit active power to the line The target congested line identification is generated by the line overload monitoring module of the dispatching center, for example, when it is monitored that the real-time power transmission of the line “L-45-78” (connecting the 45th node and the 78th node) reaches 95% of its thermal stability limit, the system will issue “L-45-78” as the target congested line identification. After obtaining these two data, the system first locates the corresponding row in the complete power transmission distribution factor matrix according to the target congested line identification “L-45-78”, then the system needs to identify the node number of the grid connection point of each photovoltaic energy storage system partition, which is read from the pre-configured “partition-grid connection point mapping table”. This table lists the unique number of the aggregated equivalent grid connection node of each coordinated voltage regulation partition in the power grid topology in detail, for example, the grid connection point of partition 1 is the 23rd node, and the grid connection point of partition 2 is the 56th node. Then, the system indexes these grid connection point node numbers in the “L-45-78” row of the complete power transmission distribution factor matrix to screen the corresponding column vector elements, that is, and The “partition identification-PTDF value” pairs screened out are summarized to generate the power transmission distribution factor set.

[0097] The obtaining step of the maximum coordinated power flow relief potential is:

[0098] Based on the power transmission distribution factor set, the current active power value, the maximum adjustable active power value and the minimum adjustable active power value of all members in each photovoltaic energy storage system partition are read, and the up-regulation active power difference and the down-regulation active power difference in the same partition are summed up respectively to form the partition directional adjustable active power pair.

[0099] The maximum coordinated flow diversion potential of the target line is calculated based on the adjustable active power of the partition direction, and the calculation formula is:

[0100] ;

[0101] wherein, is the maximum coordinated flow diversion potential of the target line, is the number of photovoltaic energy storage system partitions, is the first partition and the power transmission distribution factor of the target congested line, is the first partition and the total upward adjustable active power, is the first partition and the total downward adjustable active power, is the first partition and the coordinated response quality factor, is the quality factor influence index, is the sign function of the symbol value.

[0102] Specifically, based on the power transmission distribution factor set generated in the previous process, the system starts the calculation process of the partition adjustable power, which is based on the coordinated voltage regulation partition set and iterates. For each partition in the partition set, for example, the first partition, the system first identifies the list of all photovoltaic energy storage system members contained in the partition, then for each member in the list (for example, member ), the system reads its three key state values: the current active power value , which is obtained by reading the power meter of the photovoltaic energy storage system grid-connected point in real time; the maximum adjustable active power value and the minimum adjustable active power value , which are dynamically calculated according to the photovoltaic output, the state of charge of the energy storage and the physical constraints of the equipment, through the internal data interface from the “adjustable active and reactive power limits of each photovoltaic energy storage system” data set. Next, the system calculates the upward and downward active power adjustment margin for each member , the upward adjustable active power difference is defined as , and the downward adjustable active power difference is defined as After completing the difference calculation of all members in the partition, the system aggregates these differences at the partition level, i.e. sums up the upward active power differences of all members in the same partition to obtain the total upward adjustment capacity of the partition , and similarly, sums up the downward active power differences of all members to obtain the total downward adjustment capacity ​, this pair of aggregated values ( , ) is associated with the partition identifier , and finally, by performing this calculation for all partitions, the partition-wise adjustable active power pair is formed.

[0103] The formula is: The advantage of the formula is that, by the sign function , it automatically selects the optimal adjustment direction for each partition as a smart switch. If the power injection of a certain partition exacerbates congestion ( ), the formula automatically calls its ability to lower power ; conversely, if its power injection can alleviate congestion ( ), it calls its ability to increase power . This design makes the development of power flow mitigation strategies have physical self-adaptability. In addition, the formula multiplies the adjustment amount by the absolute value of the power transmission distribution factor , ensuring that the greater the impact on the line flow of the partition, the greater its weight in the total potential. More importantly, the introduction of the cooperative response quality factor and the influence index brings in soft indicators such as internal coordination and communication reliability of the partition, making the evaluation results not only reflect "how much can be adjusted", but also reflect "how well it is adjusted".

[0104] The acquisition step is that this parameter is the total number of photovoltaic energy storage system partitions, and its value is determined by querying and counting the number of independent partitions contained in the "cooperative voltage regulation partition set" generated in the initial step of "a photovoltaic energy storage system coordinated control method". This process is automatically counted by software. For example, if the system divides all photovoltaic energy storage systems into 3 independent cooperative voltage regulation partitions after voltage sensitivity clustering analysis, the value of is 3.

[0105] The acquisition step is that this parameter is the power transmission distribution factor of the th partition point relative to the target congested line, and its value is directly read from the "power transmission distribution factor set" generated in the previous step of this method. This set has been filtered according to the target congested line identifier issued by the grid dispatching center, and stores the key-value pairs of each partition and its corresponding power transmission distribution factor value. For example, for the congested line L-45-78, the factor of partition 1 is , the factor of partition 2 is , and the factor of partition 3 is These dimensionless values are directly used in subsequent calculations.

[0106] and The acquisition step of the two parameters respectively represents the total amount of active power that the first partition can adjust upwards and downwards, and the values are derived from the "partition directionality adjustable active power pair" data set generated immediately before this step, which stores the aggregated upward and downward power margins of each partition, for example, the system queries the set to obtain: the adjustable power pair of partition 1 is ( , ), the adjustable power pair of partition 2 is ( , ), and the adjustable power pair of partition 3 is ( , );

[0107] The acquisition step of the parameter is the coordination response quality factor of the first partition, which is used to quantify the coordination performance within the partition, taking into account the stability of communication and the consistency of energy storage state, and the calculation formula is: wherein, is the normalized value of the average communication delay of all members in the partition, is the normalized value of the standard deviation of the state of charge of all members in the partition, and the weights and are set according to operation and maintenance experience, for example, take , to indicate that both are equally important, for example, the average communication delays of the three partitions are [80ms, 120ms, 70ms] and the SOC standard deviations are [4%, 9%, 3%], the reasonable range of communication delay is [50ms, 150ms], and the reasonable range of SOC standard deviation is [2%, 10%], and the maximum and minimum normalization method is used to calculate: , and similarly , ;

[0108] The acquisition step of the parameter is the quality factor influence index, which is pre-set by the grid dispatching strategy and is used to adjust the influence of the coordination response quality factor in the calculation, and the value is determined by regression analysis on historical dispatching data, and the success rate of power flow diversion and the adjustment cost are analyzed under different values (for example, from 0.5 to 2.0, step 0.1), and the value with the best comprehensive benefit is selected, for example, analysis shows that when , the system can more effectively utilize high-quality resources and avoid secondary adjustment due to poor response of low-quality resources, so is set in this calculation;

[0109] Calculation process:

[0110] According to the above parameter acquisition results, the calculation of the maximum coordinated flow dredging potential is carried out:

[0111] Partition 1 ( ): , the up-regulation power should be used.

[0112] Contribution value = ;

[0113] Partition 2 ( ): , the down-regulation power should be used.

[0114] Contribution value = ;

[0115] Partition 3 ( ): , the up-regulation power should be used.

[0116] Contribution value = ;

[0117] Sum the contribution values of each partition:

[0118] ;

[0119] The results show that the maximum flow reduction that can be achieved on the target congested line by the current all photovoltaic energy storage system partition collaborative action is 1.57149 MW, which is the maximum coordinated flow dredging potential of the target line. It provides direct and quantitative decision-making basis for the grid dispatching center to judge whether the current line congestion problem can be solved only by relying on these distributed resources. If the flow reduction required by the dispatching center is less than 1.57149 MW, the task can be executed; otherwise, other backup measures need to be started.

[0120] The steps for obtaining the power instruction sequence of the energy storage unit are:

[0121] Obtain the total amount of flow dredging task that needs to be completed by the target line from the grid dispatching center, and call the maximum coordinated flow dredging potential. Extract the contribution value provided by each photovoltaic energy storage system partition in the process of calculating the maximum coordinated flow dredging potential, and use the ratio of the contribution value of the partition to the maximum coordinated flow dredging potential as the contribution proportion of the partition. According to the contribution proportion, determine the power dredging instruction allocated to each photovoltaic energy storage system partition, and generate the power dredging instruction of the partition;

[0122] Based on the partitioned power grooming instructions, the partitioned coordinated response weight set is called and the coordinated response weights of all PV energy storage systems in each partition are extracted one by one. The coordinated response weight of each PV energy storage system is divided by the sum of the coordinated response weights of all PV energy storage systems in the partition to complete the normalization of the weights within the partition. The partitioned power grooming instructions are then subdivided into each PV energy storage system in the partition based on the normalized weight values ​​to generate the initial power instruction for each PV energy storage system.

[0123] Based on the initial power command of each photovoltaic energy storage system, the real-time state of charge of the current energy storage unit of the corresponding photovoltaic energy storage system and the real-time adjustable active power range of the inverter are retrieved one by one to compare whether the initial power command falls within the real-time adjustable active power range of the inverter. If the initial power command exceeds the range, the boundary value of the real-time adjustable active power range of the inverter is used as the corrected power command of the photovoltaic energy storage system. After all corrections are completed, the determined corrected power command is sent to the inverter of the corresponding photovoltaic energy storage system to generate a power command sequence for the energy storage unit.

[0124] Specifically, first, through the preset communication interface with the power grid dispatching center, the total amount of current flow diversion tasks currently required to be completed by the target line issued by it is received. For example, the dispatching center specifies that a 1.2MW flow reduction is required on the congested line L-45-78. This value is the total task amount. At the same time, the system calls the "maximum collaborative flow diversion potential" calculated in the previous key step, whose value is 1.57149MW. Since the total task amount is less than the maximum potential, the system confirms the feasibility of the task and continues to execute it. Then, the system traces back the calculation process of the maximum collaborative flow diversion potential and extracts the contribution value provided by each photovoltaic energy storage system partition in the calculation one by one. These contribution values ​​are intermediate results that have comprehensively considered the regulation capacity, electrical impact and collaborative response quality of each partition. For example, the contribution values ​​extracted from partitions 1, 2, and 3 are 0.8034MW, 0.13725MW and 0.63084MW respectively. Then, the system calculates the contribution ratio of each partition, that is, divides the contribution value of a single partition by the maximum collaborative flow diversion potential, and obtains the contribution ratio of partition 1. , the proportion of partition 2 is , the proportion of partition 3 is Based on this contribution ratio, the system distributes the total power flow diversion task in proportion and determines the power regulation amount that each partition needs to bear. This regulation amount refers to the amount of active power injection that needs to be increased or decreased at the partition grid connection point. The calculation method is to first calculate a global regulation ratio, that is, the ratio of the total task amount to the maximum potential ( ), and then apply this ratio to the original adjustable power amount of each zone when calculating the potential. Specifically, for zone 1 that needs to increase power (its original increase potential is 5.2MW), its power regulation instruction is For zone 2, which needs to down-regulate power (its original down-regulation potential is 6.1 MW), its instruction is and for zone 3, which needs to up-regulate power (its original up-regulation potential is 7.0 MW), its instruction is where the positive sign means to increase active power, and the negative sign means to decrease, and finally, these calculated power adjustment values are bound with the corresponding zone identifiers to generate the power steering instructions for the zones.

[0125] Based on the power steering instructions for the zones generated in the previous process, the system starts the instruction refinement procedure, which processes each zone one by one. For any zone, for example, zone 1, the system first reads its power steering instruction from the instruction set, which is a total of 3.97 MW of active power that needs to be increased. Next, the system calls the previously calculated and stored "zone collaborative response weight set" to extract the collaborative response weights of all photovoltaic energy storage systems within zone 1, for example, zone 1 contains systems A, B, and C, whose corresponding collaborative response weights are 0.3297, 0.2638, and 0.4065, respectively. Since these weights have been normalized by dividing by the sum of the evaluation values of all members in the zone during calculation, their sum is exactly 1, so there is no need to perform normalization again. The system directly uses these weight values as the basis for power allocation, and subdivides the total power steering instruction for the zone into each photovoltaic energy storage system within the zone according to the weight proportion. For system A, the power adjustment amount it should undertake is the total instruction for the zone multiplied by its own weight, that is, Similarly, the adjustment amount that system B should undertake is and the adjustment amount that system C should undertake is These calculated values represent the ideal power change requirements for each photovoltaic energy storage system. The system repeats this allocation process for all zones and their internal members, decomposing the macro power instruction for each zone into specific power adjustment values for each individual photovoltaic energy storage system, and finally aggregates these values to generate the initial power instruction for each photovoltaic energy storage system.

[0126] Based on the initial power instruction for each photovoltaic energy storage system, the system enters the final instruction verification and issuance phase, which traverses each photovoltaic energy storage system to ensure the executability of the instruction. For a single photovoltaic energy storage system, for example, system A, the system first reads its initial power instruction as an increase of 1.31 MW. Then, the system retrieves the running state data of the system at the current time, including the current active power value of its grid-connected point (for example, 0.8 MW), and the previously calculated inverter real-time adjustable active power range, which has fully considered the equipment physical limitations and the energy storage state of charge, for example, the range of system A is [0.3 MW, 1.2 MW], the system calculates the target power set value of system A according to the initial instruction, that is , then, the target value is compared with the adjustable range, and it is found that 2.11 MW exceeds the upper limit of the maximum adjustable active power 1.2 MW, therefore, the initial power instruction is not feasible for system A, the system starts the correction program, and the power instruction of the system is corrected to the boundary value of the adjustable range, that is, the corrected target power set value is 1.2 MW, which is the corrected power instruction of the photovoltaic energy storage system, after completing the instruction verification and necessary correction of all photovoltaic energy storage systems, the system converts the finally determined and executable corrected power instructions into specific operation instructions for the energy storage units, specifically, the power instruction of the energy storage unit is obtained by subtracting the real-time output of the current photovoltaic array from the corrected total power instruction, for example, if the real-time output of the photovoltaic array of system A is 0.8 MW, and the corrected power instruction is 1.2 MW, the instruction issued to the energy storage unit is , which indicates that the energy storage unit needs to discharge 0.4 MW, finally, the system encapsulates these calculated energy storage unit power instruction values into messages conforming to the device communication protocol (such as Modbus or IEC 61850), and issues them to the corresponding inverter or energy management system of the photovoltaic energy storage system through the communication network for execution, thereby generating the energy storage unit power instruction sequence.

[0127] The above is only a preferred embodiment of the present application, and does not limit the present application in other forms, any skilled person in the art can modify or change the above disclosed technical content to equivalent embodiments applied to other fields, but any simple modification, equivalent change and modification made according to the technical essence of the present application to the above embodiments without departing from the technical solution content of the present application still belongs to the protection scope of the present application technical solution.

Claims

1. A photovoltaic energy storage system coordinated control method, characterized in that: The following steps are involved: Obtain the grid topology and line parameters, establish the grid admittance matrix, calculate the voltage change caused by unit reactive power injection between any two PV energy storage system nodes, group all PV energy storage system nodes, and obtain a set of coordinated voltage regulation partitions; Based on the coordinated voltage regulation zone set, the real-time photovoltaic output fluctuation data and the energy storage unit charge state of each photovoltaic energy storage system in each zone are read to obtain the aggregate adjustable power range within the zone, and then the zone coordinated response weight set is established based on the aggregate adjustable power range within the zone; Obtain the power transfer distribution factor matrix and congested line identifiers from the grid dispatch center, extract the power transfer distribution factor values ​​of each PV energy storage system's partitioned grid connection point relative to the congested line, and obtain a set of power transfer distribution factors. This set of power transfer distribution factors is then calculated with the partitioned adjustable power to determine the maximum collaborative power flow diversion potential. generating a power instruction sequence for an energy storage unit based on the maximum collaborative power flow diversion potential and the partition collaborative response weight set; The steps for obtaining the coordinated voltage regulation partition set are: Obtaining the topological connection relationship of all nodes in the power grid and the electrical parameters of the corresponding lines, calculating the self-admittance and mutual-admittance of the lines one by one based on the topological connection relationship and the electrical parameters of the lines, and constructing a power grid admittance matrix based on the self-admittance and mutual-admittance of the lines to generate a power grid admittance matrix; Based on the grid admittance matrix, inject unit reactive power into each photovoltaic energy storage system node in turn, calculate and record the voltage change amplitude of all other nodes in the grid when the node injects unit reactive power, and obtain the voltage change value between each node; Based on the voltage variation values ​​between the nodes, the voltage variation between the nodes of the photovoltaic energy storage system is counted node by node, a screening threshold for the node voltage variation is set, and nodes whose voltage variation reaches or exceeds the screening threshold are classified into the same group to form a coordinated voltage regulation partition set; The steps for obtaining the aggregate adjustable power range within the partition are: Based on the coordinated voltage regulation zone set, each photovoltaic energy storage system in each zone is visited one by one, and the current photovoltaic output fluctuation data and the state of charge value of the corresponding energy storage unit of each photovoltaic energy storage system are collected in real time to form a set of real-time photovoltaic output fluctuation data and energy storage unit state of charge value; Based on the real-time photovoltaic output fluctuation data and the energy storage unit state of charge value set, the maximum and minimum active power values, as well as the maximum and minimum reactive power values, that can be adjusted for each photovoltaic energy storage system in its current state are calculated one by one to form the adjustable active and reactive power limits of each photovoltaic energy storage system; Based on the adjustable active and reactive power limits of each photovoltaic energy storage system, the sum of the adjustable active power limits and the sum of the adjustable reactive power limits of all photovoltaic energy storage systems in each partition are aggregated and calculated to form an aggregated adjustable power range within the partition.

2. The photovoltaic energy storage system coordinated control method according to claim 1, characterized in that: The steps for obtaining the partition coordinated response weight set are: Based on the aggregated adjustable power range within the partition, the maximum active power, minimum active power, maximum reactive power, and minimum reactive power of each photovoltaic energy storage system in the partition are sequentially read, and the voltage change amplitude generated by the node when injecting unit reactive power to all other nodes in the partition is simultaneously retrieved, and the power regulation boundary and node voltage sensitivity value set of the photovoltaic energy storage system in the partition are integrated; Calculating a coordinated response weight of the photovoltaic energy storage system based on a power regulation boundary and a node voltage sensitivity value set of the photovoltaic energy storage system in the partition; Based on the coordinated response weights of the photovoltaic energy storage systems, the coordinated response weight results of all photovoltaic energy storage systems in the partition are summarized and sorted item by item according to the partition to which they belong, forming a partition coordinated response weight set.

3. The photovoltaic energy storage system coordinated control method according to claim 1, characterized in that: The steps for obtaining the power transmission distribution factor set are: The complete power transfer distribution factor matrix and the identifier of the target congested line in the control state are retrieved from the power grid dispatching center. The column vectors of the grid connection points of each photovoltaic energy storage system partition relative to the target congested line are screened to generate a set of power transfer distribution factors.

4. The photovoltaic energy storage system coordinated control method according to claim 1, characterized in that: The steps for obtaining the maximum collaborative flow diversion potential are: Based on the power transfer distribution factor set, read the current active power value, maximum adjustable active power value, and minimum adjustable active power value of all members in each photovoltaic energy storage system partition, and sum the upward active power difference and downward active power difference within the same partition to form a partition directional adjustable active power pair; Based on the partitioned directional adjustable active power pairs, the maximum collaborative power flow diversion potential of the target line is calculated.

5. The photovoltaic energy storage system coordinated control method according to claim 1, characterized in that: The steps for obtaining the power instruction sequence of the energy storage unit are: The total amount of power flow grooming tasks currently required to be completed on the target line is obtained from the power grid dispatching center. The maximum collaborative power flow grooming potential is called, and the contribution value provided by each photovoltaic energy storage system partition in the calculation of the maximum collaborative power flow grooming potential is extracted one by one. The ratio of the partition's contribution value to the maximum collaborative power flow grooming potential is used as the partition's contribution ratio. The power grooming instructions allocated to each photovoltaic energy storage system partition are determined based on the contribution ratio, and the power grooming instructions for the partition are generated. Based on the partitioned power grooming instructions, the partitioned coordinated response weight set is called and the coordinated response weights of all photovoltaic energy storage systems in each partition are extracted one by one. The coordinated response weight of each photovoltaic energy storage system is divided by the sum of the coordinated response weights of all photovoltaic energy storage systems in the partition in turn to complete the normalization of the weights within the partition. The partitioned power grooming instructions are then subdivided into each photovoltaic energy storage system in the partition according to the normalized weight values ​​to generate an initial power instruction for each photovoltaic energy storage system.

6. The photovoltaic energy storage system coordinated control method according to claim 5, characterized in that: The step of acquiring the energy storage unit power instruction sequence further includes: based on the initial power instruction of each photovoltaic energy storage system, retrieving the real-time state of charge of the current energy storage unit of the corresponding photovoltaic energy storage system and the real-time adjustable active power range of the inverter one by one, comparing whether the initial power instruction falls within the real-time adjustable active power range of the inverter; if the initial power instruction exceeds the range, using the boundary value of the real-time adjustable active power range of the inverter as the corrected power instruction of the photovoltaic energy storage system; after all corrections are completed, issuing the determined corrected power instruction to the inverter of the corresponding photovoltaic energy storage system to generate the energy storage unit power instruction sequence.

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