Multi-reactive compensation equipment active-reactive voltage cooperative control method considering energy storage

Abstract

An active-reactive voltage cooperative control method for multiple reactive compensation devices considering energy storage comprises the steps that 1, simulation analysis is conducted on time sequence voltage fluctuation characteristics of a high-permeability photovoltaic grid-connected system, and dynamic influences of photovoltaic output fluctuation in different time periods on system node voltage are quantitatively evaluated; 2, solving a non-dominated solution set of the model by adopting a multi-target particle swarm optimization algorithm, realizing collaborative optimization and trade-off analysis of multi-dimensional performance indexes, and establishing a reactive power regulation model and an energy storage active power support model; and organically coupling the reactive power regulation model and the energy storage active power support model. By means of the method, high photovoltaic area voltage treatment can be effectively carried out in real time, and the method has high engineering application value and wide popularization prospects.

Description

Technical Field

[0001] This invention relates to the field of distribution network voltage control, and in particular to a method for coordinated active and reactive voltage control of multiple reactive power compensation devices that considers energy storage. Background Technology

[0002] In recent years, driven by national policies and technologies aimed at promoting low-carbon energy transformation, the large-scale integration of distributed photovoltaic (PV) power into distribution networks has been of great significance to grid transformation and energy reform. By the end of 2023, my country's total installed PV capacity reached 6.09 × 10⁵ kW. However, large-scale PV integration has significantly impacted the power quality of distribution networks. According to grid connection technical specifications, when the node voltage exceeds the safety threshold, distributed PV must be disconnected from the grid within a specified time limit. Voltage exceeding the limit has become a prominent power quality problem in distribution networks, affecting grid stability and user-side safety, and hindering the sustainable development of the PV industry. Therefore, research on voltage regulation methods for distribution networks with a high proportion of distributed PV is urgently needed.

[0003] To address the voltage exceedance and backflow issues arising from high-proportion photovoltaic (PV) grid integration, existing research both domestically and internationally primarily focuses on two aspects: active power management through the charging and discharging of energy storage devices and voltage reactive power control. Energy storage systems absorb excess PV output during the day to suppress voltage exceedances and discharge at night to supplement load demand and support voltage stability, demonstrating flexible regulation capabilities. However, limited by the capacity constraints of energy storage devices, it is difficult to simultaneously achieve both economic efficiency and voltage control effectiveness when managing voltage exceedances. Voltage reactive power control mainly optimizes distribution network operation through reactive power regulation devices such as on-load tap changers, static var compensators (SVCs), and capacitor banks. However, reactive power regulation by distributed reactive power devices may sacrifice their active power output capacity, thus affecting system economics.

[0004] Current research on voltage over-limit control under high-proportion photovoltaic (PV) systems is not comprehensive enough, and energy storage systems are limited by capacity to maximize PV absorption. Furthermore, existing solutions mostly focus on reactive power regulation capabilities, failing to fully analyze the impact of high-penetration PV active power output on distribution network voltage. When PV output is out of balance with load demand, excess active power will lead to voltage over-limit in the distribution network. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention aims to provide a method for coordinated active and reactive voltage control of multiple reactive power compensation devices that considers energy storage, thereby solving the problem of voltage control in high-penetration photovoltaic distribution networks.

[0006] To achieve the above objectives, the adopted technical solution is: a method for coordinated active and reactive voltage control of multiple reactive power compensation devices considering energy storage.

[0007] Step 1: Simulate and analyze the time-series voltage fluctuation characteristics of a high-penetration photovoltaic grid-connected system to quantitatively evaluate the dynamic impact of photovoltaic output fluctuations on system node voltages at different times.

[0008] Simulation analysis reveals the dynamic impact of photovoltaic power output fluctuations on system node voltages over different time periods, causing system node voltages to deviate from the preset safe operating range. Quantitative analysis yields the specific amplitude of voltage exceedances at each node after photovoltaic access to the system. Based on the obtained voltage exceedance index, the modeling work in step two is carried out by coordinating the operating parameters and control strategies of various types of reactive power compensation equipment and energy storage equipment to control the system voltage within the safe operating range.

[0009] Step 2: Use the multi-objective particle swarm optimization algorithm to solve the non-dominated solution set of the model, realize the synergistic optimization and trade-off analysis of multi-dimensional performance indicators, and establish the reactive power regulation model and the energy storage active power support model.

[0010] Reactive power regulation model: Input distribution network parameters, load characteristics and photovoltaic power capacity data into the basic regulation layer, set photovoltaic as PQ node and obtain the initial voltage distribution through power flow calculation; then initialize particle swarm algorithm parameters, encode photovoltaic reactive power output, transformer ratio and capacitor bank switching as control variables, screen Pareto non-dominated solutions through multi-objective optimization, and output the optimal control parameters of reactive power compensation equipment that meet voltage constraints.

[0011] The method for establishing the reactive power regulation model is as follows:

[0012] The basic regulation level takes the reactive power output of the photovoltaic power generation system, the reactive power output of the compensation capacitor bank, and the turns ratio of the on-load tap-changing transformer as variables to be optimized. The objective function is set together by minimizing the total active power loss and the total voltage deviation of the distribution network. For the two cases where the voltage exceeds the limit and the reactive power output of the photovoltaic power source exceeds the limit, these are incorporated into the objective function as penalty terms. The established voltage optimization control objective function is as follows:

[0013] (1)

[0014] in

[0015] (2)

[0016] (3)

[0017] (4)

[0018] In the formula: U imax and U iminThe upper and lower limits of the allowable voltage amplitude at unbalanced nodes in the distribution network are defined respectively; P loss U represents the total active power loss of the entire network; i U0 represents the actual operating voltage amplitude of all nodes in the system except for the slack node; λ1 is the weighting coefficient used to minimize the total active power loss target; λ2 is the objective function weighting factor that minimizes the total voltage deviation; η1 is the pre-set penalty factor for node voltage exceeding limits; η2 is the penalty term coefficient set for photovoltaic unit reactive power output exceeding the constraint boundary; n refers to the total number of unbalanced nodes in the system; N PV Indicates the number of photovoltaic units connected within the distribution network;

[0019] The voltage control model for multiple reactive power compensation devices must meet the constraints of power balance, inverter operating capacity, on-load tap changer tap position, and maximum reactive power output of reactive power compensation capacitors.

[0020] (5)

[0021] (6)

[0022] (7)

[0023] (8)

[0024] (9)

[0025] (10)

[0026] (11)

[0027] In the formula: P Gi and Q G P represents the active power and reactive power provided by the transmission network at node i, respectively; PVi and Q PVi This corresponds to the active and reactive power generated by the photovoltaic unit at that node; P Li With Q Li This represents the active and reactive power consumed by the load at this node; Q Ci G represents the reactive power compensation amount of the reactive power compensation device at node i; ij and B ij Here are the conductance and susceptance components of the system admittance matrix; θ ij This represents the voltage phase angle difference between nodes i and j; S PVi P represents the rated operating capacity of the i-th photovoltaic inverter; PVi Q represents the active power generated by the corresponding photovoltaic unit. PViQ represents the reactive power that the inverter can provide. PVi，max and Q PVi，min T represents the upper and lower limits of the reactive power output allowed for the i-th photovoltaic unit, respectively; j，max and T j，min Let Q be the maximum and minimum allowable tap ratio of the j-th on-load tap-changing transformer; Ck，max N refers to the maximum reactive power that can be injected into the k-th group of reactive power compensation capacitors; PV N represents the total number of photovoltaic units in the system; C This refers to the number of capacitor banks installed; N T U represents the total number of adjustable tap changer transformers; i，max and U i，min This represents the maximum and minimum allowable values ​​of the voltage amplitude at node i.

[0028] Energy storage active power support model: Based on the basic regulation level, if the voltage still exceeds the limit, it enters the supplementary optimization level: Based on the energy storage remaining capacity assessment model, it calculates and calls active / reactive power capacity, re-initializes the particle swarm and focuses on minimizing voltage deviation and optimizing cost. After iteration, it outputs the joint control strategy of energy storage and reactive power equipment.

[0029] The method for establishing the energy storage active power support model is as follows:

[0030] The supplementary optimization level uses the energy storage capacity configuration in the photovoltaic-energy storage system as the optimization variable, constructing an objective function that aims to minimize the total life cycle cost of the energy storage system and the total voltage deviation of the entire grid. Node voltage over-limit behavior is reflected in the objective function through a penalty factor.

[0031] (12)

[0032] (13)

[0033] (14)

[0034] In the formula: C BESS Indicates the economic cost of scheduling and operating an energy storage system; C Grid The cost of power trading between the distribution network and the upper-level grid; λ is the weighting factor for minimizing the total voltage deviation objective; η represents the penalty coefficient for exceeding the reactive power output limit of the photovoltaic unit; K BESS Defined as the dispatch cost per unit power of an energy storage system; P dis，n，h (t) and P ch，n，h (t) corresponds to the discharge power and charging power of the energy storage system numbered n in time period h, respectively; η represents the overall charging and discharging efficiency of the system.

[0035] Voltage control of energy storage devices must comply with power balance, network balance, inverter operating capacity, operating limits of energy storage systems, and voltage amplitude constraints of all distribution network nodes.

[0036] (15)

[0037] (16)

[0038] (17)

[0039] (18)

[0040] (19)

[0041] (20)

[0042] In the formula: P main P represents the total active power injected into the distribution network from the upstream power grid. BESSO P represents the total active power released from the energy storage system to the network. BESSI P refers to the total active power absorbed by energy storage devices from the network. load P represents the active power consumed by all loads in the distribution network. loss This represents the total active power loss generated during network transmission; S OC，max With S OC，min These correspond to the upper and lower limits of the permissible operating state of charge for the energy storage system, respectively.

[0043] Step 3: By designing a coordinated control mechanism for the active power output and reactive power compensation equipment of energy storage, the reactive power regulation model and the active power support model of energy storage are organically coupled to obtain the final model.

[0044] A hierarchical-distributed coordinated control architecture is constructed: When the voltage exceeds the lower limit, the reactive power support capability of the photovoltaic inverter is prioritized, and the dynamic reactive power compensation device and transformer tap adjustment are coordinated to achieve an initial voltage rise; if the voltage still exceeds the limit, the remaining capacity of the energy storage system is activated to provide auxiliary reactive power compensation, forming a two-layer reactive power support mechanism; when the voltage exceeds the upper limit, the reactive power output adjustment of the photovoltaic inverter and the switching of the capacitor bank are used to achieve rapid voltage suppression. If the effect is insufficient, the active power absorption capability of the energy storage system is activated, and the transformer turns ratio is adjusted to form coordinated control, ultimately dynamically constraining the node voltage within the safe threshold.

[0045] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0046] The active-reactive voltage coordinated control method for multiple reactive power compensation devices considering energy storage proposed in this invention has significant advantages in voltage management under high photovoltaic conditions. In existing technologies, traditional strategies relying on a single energy storage device to manage voltage exceedances are constrained by the rated capacity and cycle life of the energy storage unit, resulting in boundary conditions for its voltage regulation capability: when the fluctuation range of photovoltaic output exceeds the maximum throughput capacity of the energy storage system, to avoid overcharge / over-discharge protection activation, it is necessary to adopt a curtailment strategy or limit photovoltaic output, objectively compromising the renewable energy absorption rate. This invention, however, utilizes a multi-objective particle swarm optimization algorithm to construct a two-layer architecture of "basic regulation-supplementary optimization." Under the premise of strictly meeting the capacity constraints of the energy storage devices, it collaboratively optimizes the goals of maximizing photovoltaic absorption rate, minimizing network losses, and minimizing overall system cost, achieving multi-dimensional performance-balanced voltage control. This innovative technical solution can effectively manage voltage in high photovoltaic areas in real time, possessing strong engineering application value and broad prospects for promotion. Attached Figure Description

[0047] Figure 1 This is the control flowchart of the present invention;

[0048] Figure 2 This is a schematic diagram of the IEEE 33-node test system in Example 1;

[0049] Figure 3 This is the photovoltaic power output curve from Example 1;

[0050] Figure 4 This is the load output curve diagram from Example 1;

[0051] Figure 5 This is a comparison chart of the voltage at 19:00 in the three cases in Example 1;

[0052] Figure 6 This is a comparison chart of the voltage at 12:00 in three cases in Example 1. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] A method for coordinated active and reactive voltage control of multiple reactive power compensation devices considering energy storage:

[0055] Step 1: Simulate and analyze the time-series voltage fluctuation characteristics of a high-penetration photovoltaic grid-connected system to quantitatively evaluate the dynamic impact of photovoltaic output fluctuations on system node voltages at different times.

[0056] Simulation analysis reveals the dynamic impact of photovoltaic power output fluctuations on system node voltages over different time periods, causing system node voltages to deviate from the preset safe operating range. Quantitative analysis yields the specific amplitude of voltage exceedances at each node after photovoltaic access to the system. Based on the obtained voltage exceedance index, the modeling work in step two is carried out by coordinating the operating parameters and control strategies of various types of reactive power compensation equipment and energy storage equipment to control the system voltage within the safe operating range.

[0057] Step 2: Use the multi-objective particle swarm optimization algorithm to solve the non-dominated solution set of the model, realize the synergistic optimization and trade-off analysis of multi-dimensional performance indicators, and establish the reactive power regulation model and the energy storage active power support model.

[0058] Reactive power regulation model: Input distribution network parameters, load characteristics and photovoltaic power capacity data into the basic regulation layer, set photovoltaic as PQ node and obtain the initial voltage distribution through power flow calculation; then initialize particle swarm algorithm parameters, encode photovoltaic reactive power output, transformer ratio and capacitor bank switching as control variables, screen Pareto non-dominated solutions through multi-objective optimization, and output the optimal control parameters of reactive power compensation equipment that meet voltage constraints.

[0059] The method for establishing the reactive power regulation model is as follows:

[0060] The basic regulation level takes the reactive power output of the photovoltaic power generation system, the reactive power output of the compensation capacitor bank, and the turns ratio of the on-load tap-changing transformer as variables to be optimized. The objective function is set together by minimizing the total active power loss and the total voltage deviation of the distribution network. For the two cases where the voltage exceeds the limit and the reactive power output of the photovoltaic power source exceeds the limit, these are incorporated into the objective function as penalty terms. The established voltage optimization control objective function is as follows:

[0061] (1)

[0062] in

[0063] (2)

[0064] (3)

[0065] (4)

[0066] In the formula: U imax and U iminThe upper and lower limits of the allowable voltage amplitude at unbalanced nodes in the distribution network are defined respectively; P loss U represents the total active power loss of the entire network; i U0 represents the actual operating voltage amplitude of all nodes in the system except for the slack node; λ1 is the weighting coefficient used to minimize the total active power loss target; λ2 is the objective function weighting factor that minimizes the total voltage deviation; η1 is the pre-set penalty factor for node voltage exceeding limits; η2 is the penalty term coefficient set for photovoltaic unit reactive power output exceeding the constraint boundary; n refers to the total number of unbalanced nodes in the system; N PV Indicates the number of photovoltaic units connected within the distribution network;

[0067] The voltage control model for multiple reactive power compensation devices must meet the constraints of power balance, inverter operating capacity, on-load tap changer tap position, and maximum reactive power output of reactive power compensation capacitors.

[0068] (5)

[0069] (6)

[0070] (7)

[0071] (8)

[0072] (9)

[0073] (10)

[0074] (11)

[0075] In the formula: P Gi and Q G P represents the active power and reactive power provided by the transmission network at node i, respectively; PVi and Q PVi This corresponds to the active and reactive power generated by the photovoltaic unit at that node; P Li With Q Li This represents the active and reactive power consumed by the load at this node; Q Ci G represents the reactive power compensation amount of the reactive power compensation device at node i; ij and B ij Here are the conductance and susceptance components of the system admittance matrix; θ ij This represents the voltage phase angle difference between nodes i and j; S PVi P represents the rated operating capacity of the i-th photovoltaic inverter; PVi Q represents the active power generated by the corresponding photovoltaic unit. PViQ represents the reactive power that the inverter can provide. PVi，max and Q PVi，min T represents the upper and lower limits of the reactive power output allowed for the i-th photovoltaic unit, respectively; j，max and T j，min Let Q be the maximum and minimum allowable tap ratio of the j-th on-load tap-changing transformer; Ck，max N refers to the maximum reactive power that can be injected into the k-th group of reactive power compensation capacitors; PV N represents the total number of photovoltaic units in the system; C This refers to the number of capacitor banks installed; N T U represents the total number of adjustable tap changer transformers; i，max and U i，min This represents the maximum and minimum allowable values ​​of the voltage amplitude at node i.

[0076] Energy storage active power support model: Based on the basic regulation level, if the voltage still exceeds the limit, it enters the supplementary optimization level: Based on the energy storage remaining capacity assessment model, it calculates and calls active / reactive power capacity, re-initializes the particle swarm and focuses on minimizing voltage deviation and optimizing cost. After iteration, it outputs the joint control strategy of energy storage and reactive power equipment.

[0077] The method for establishing the energy storage active power support model is as follows:

[0078] The supplementary optimization level uses the energy storage capacity configuration in the photovoltaic-energy storage system as the optimization variable, constructing an objective function that aims to minimize the total life cycle cost of the energy storage system and the total voltage deviation of the entire grid. Node voltage over-limit behavior is reflected in the objective function through a penalty factor.

[0079] (12)

[0080] (13)

[0081] (14)

[0082] In the formula: C BESS Indicates the economic cost of scheduling and operating an energy storage system; C Grid The cost of power trading between the distribution network and the upper-level grid; λ is the weighting factor for minimizing the total voltage deviation objective; η represents the penalty coefficient for exceeding the reactive power output limit of the photovoltaic unit; K BESS Defined as the dispatch cost per unit power of an energy storage system; P dis，n，h (t) and P ch，n，h (t) corresponds to the discharge power and charging power of the energy storage system numbered n in time period h, respectively; η represents the overall charging and discharging efficiency of the system.

[0083] Voltage control of energy storage devices must comply with power balance, network balance, inverter operating capacity, operating limits of energy storage systems, and voltage amplitude constraints of all distribution network nodes.

[0084] (15)

[0085] (16)

[0086] (17)

[0087] (18)

[0088] (19)

[0089] (20)

[0090] In the formula: P main P represents the total active power injected into the distribution network from the upstream power grid. BESSO P represents the total active power released from the energy storage system to the network. BESSI P refers to the total active power absorbed by energy storage devices from the network. load P represents the active power consumed by all loads in the distribution network. loss This represents the total active power loss generated during network transmission; S OC，max With S OC，min These correspond to the upper and lower limits of the permissible operating state of charge for the energy storage system, respectively.

[0091] Step 3: By designing a coordinated control mechanism for the active power output and reactive power compensation equipment of energy storage, the reactive power regulation model and the active power support model of energy storage are organically coupled to obtain the final model.

[0092] A hierarchical-distributed coordinated control architecture is constructed: When the voltage exceeds the lower limit, the reactive power support capability of the photovoltaic inverter is prioritized, and the dynamic reactive power compensation device and transformer tap adjustment are coordinated to achieve an initial voltage rise; if the voltage still exceeds the limit, the remaining capacity of the energy storage system is activated to provide auxiliary reactive power compensation, forming a two-layer reactive power support mechanism; when the voltage exceeds the upper limit, the reactive power output adjustment of the photovoltaic inverter and the switching of the capacitor bank are used to achieve rapid voltage suppression. If the effect is insufficient, the active power absorption capability of the energy storage system is activated, and the transformer turns ratio is adjusted to form coordinated control, ultimately dynamically constraining the node voltage within the safe threshold.

[0093] Example 1:

[0094] This example uses the IEEE-33 node system as a case study. The topology of the IEEE-33 node system is shown below. Figure 2 As shown below, see the description for details:

[0095] Photovoltaic systems were configured at nodes 10, 15, and 30. Figure 3 and Figure 4 The photovoltaic power generation curve and load power variation curve are displayed respectively. System improvement measures include: adding an on-load tap-changing transformer between buses 1 and 2, with an adjustable ratio range of 0.95 to 1.05, a total of 9 taps, and a step adjustment increment of 0.25%; connecting a set of reactive power compensation capacitors to buses 16 and 31 respectively; and deploying energy storage devices on buses 12, 17, and 28. For the above example system, the optimization strategy proposed in this invention is applied to improve voltage quality and optimize operational performance. The relevant algorithm parameters are set as follows: the particle swarm optimization algorithm has a population size N=100, a maximum number of iterations k=150, an inertia weight coefficient ω=0.8, and acceleration constants c1 and c2 are both set to 2.0.

[0096] The following three scenarios are compared: I. Initial power flow; II. Voltage control of multiple reactive power compensation devices; III. Active-reactive voltage control of energy storage devices in conjunction with multiple reactive power compensation devices.

[0097] Voltages at each node before and after voltage control at 19:00 are as follows: Figure 5 As shown. Figure 6 The voltage distribution at each node during the noon period (12:00) before and after the implementation of the voltage control strategy is shown.

[0098] After configuring multiple sets of reactive power compensation devices, the voltage exceeding the limit situation was improved to some extent, and the voltage stability of the system was also enhanced. However, some voltage values ​​still exceeded the safe voltage range, and the voltage exceeding the limit problem was not completely resolved. Furthermore, by adding energy storage devices and implementing a combined active and reactive power voltage control strategy in conjunction with multiple sets of reactive power compensation devices, the voltage value was successfully reduced to within the safe voltage range. At this point, the voltage levels of each node in the system were closer to the rated voltage value, the voltage distribution balance was significantly enhanced, the goal of voltage balance convergence was achieved, and the voltage quality and operational stability of the power system were effectively improved.

Claims

1. A method for coordinated active and reactive voltage control of multiple reactive power compensation devices considering energy storage, characterized in that: Step 1: Simulate and analyze the time-series voltage fluctuation characteristics of a high-penetration photovoltaic grid-connected system to quantitatively evaluate the dynamic impact of photovoltaic output fluctuations on system node voltages at different times. Step 2: Use the multi-objective particle swarm optimization algorithm to solve the non-dominated solution set of the model, realize the synergistic optimization and trade-off analysis of multi-dimensional performance indicators, and establish the reactive power regulation model and the energy storage active power support model. Step 3: By designing a coordinated control mechanism for the active power output and reactive power compensation equipment of energy storage, the reactive power regulation model and the active power support model of energy storage are organically coupled to obtain the final model.

2. The active-reactive voltage coordinated control method for multiple reactive power compensation devices considering energy storage according to claim 1, characterized in that, In step one, the specific method is as follows: based on simulation analysis, the dynamic impact of photovoltaic power output fluctuations on system node voltages at different time periods is obtained, causing the system node voltages to deviate from the preset safe operating range. Quantitative analysis is performed to determine the specific amplitude of voltage exceedance at each node after photovoltaic access to the system. Based on the obtained voltage exceedance index, the modeling work in step two is carried out by coordinating the operating parameters and control strategies of multiple types of reactive power compensation equipment and energy storage equipment to control the system voltage within the safe operating range.

3. The active-reactive voltage coordinated control method for multiple reactive power compensation devices considering energy storage according to claim 1, characterized in that, In step two, the reactive power regulation model involves: inputting distribution network parameters, load characteristics, and photovoltaic power capacity data into the basic regulation layer; setting the photovoltaic system as a PQ node and obtaining the initial voltage distribution through power flow calculation; subsequently initializing the particle swarm optimization parameters; encoding the photovoltaic reactive power output, transformer ratio, and capacitor bank switching as control variables; filtering Pareto non-dominated solutions through multi-objective optimization; and outputting the optimal control parameters of the reactive power compensation equipment that satisfy voltage constraints.

4. The active-reactive voltage coordinated control method for multiple reactive power compensation devices considering energy storage according to claim 3, characterized in that, The method for establishing the reactive power regulation model is as follows: The basic regulation level takes the reactive power output of the photovoltaic power generation system, the reactive power output of the compensation capacitor bank, and the turns ratio of the on-load tap-changing transformer as variables to be optimized. The objective function is set together by minimizing the total active power loss and the total voltage deviation of the distribution network. For the two cases where the voltage exceeds the limit and the reactive power output of the photovoltaic power source exceeds the limit, these are incorporated into the objective function as penalty terms. The established voltage optimization control objective function is as follows: （1） in （2） （3） （4） In the formula: U imax and U imin The upper and lower limits of the allowable voltage amplitude at unbalanced nodes in the distribution network are defined respectively; P loss U represents the total active power loss of the entire network; i U0 represents the actual operating voltage amplitude of all nodes in the system except for the balancing node; U0 represents the reference voltage value set for each node. λ1 is the weighting coefficient used to minimize the total active power loss target; λ2 is the weighting factor of the objective function that minimizes the total voltage deviation; η1 is a pre-set penalty factor for node voltage exceeding limits; η2 is a penalty coefficient set for photovoltaic unit reactive power output exceeding constraint boundaries; n refers to the total number of unbalanced nodes in the system; N PV Indicates the number of photovoltaic units connected within the distribution network; The voltage control model for multiple reactive power compensation devices must meet the constraints of power balance, inverter operating capacity, on-load tap changer tap position, and maximum reactive power output of reactive power compensation capacitors. （5） （6） （7） （8） （9） （10） （11） In the formula: P Gi and Q G P represents the active power and reactive power provided by the transmission network at node i, respectively; PVi and Q PVi This corresponds to the active and reactive power generated by the photovoltaic unit at that node; P Li With Q Li This represents the active and reactive power consumed by the load at this node; Q Ci G represents the reactive power compensation amount of the reactive power compensation device at node i; ij and B ij For the conductance and susceptance components of the system admittance matrix; θ ij This represents the voltage phase angle difference between nodes i and j; S PVi P represents the rated operating capacity of the i-th photovoltaic inverter; PVi Q represents the active power generated by the corresponding photovoltaic unit. PVi Q represents the reactive power that the inverter can provide. PVi，max and Q PVi，min These represent the upper and lower limits of the reactive power output allowed for the i-th photovoltaic unit, respectively. T j，max and T j，min Let Q be the maximum and minimum allowable tap ratio of the j-th on-load tap-changing transformer; Ck，max N refers to the maximum reactive power that can be injected into the k-th group of reactive power compensation capacitors; PV N represents the total number of photovoltaic units in the system; C This refers to the number of capacitor banks installed; N T U represents the total number of adjustable tap changer transformers; i，max and U i，min This represents the maximum and minimum allowable values ​​of the voltage amplitude at node i.

5. The active-reactive voltage coordinated control method for multiple reactive power compensation devices considering energy storage according to claim 1, characterized in that, In step two, the energy storage active power support model: on the basis of the basic regulation level, if the voltage still exceeds the limit, it enters the supplementary optimization layer: based on the energy storage remaining capacity assessment model, it calculates and calls the active / reactive power capacity, re-initializes the particle swarm and focuses on minimizing voltage deviation and optimizing cost, and outputs the joint control strategy of energy storage and reactive power equipment after iteration.

6. The active-reactive voltage coordinated control method for multiple reactive power compensation devices considering energy storage according to claim 1, characterized in that, The method for establishing the energy storage active power support model is as follows: The supplementary optimization level uses the energy storage capacity configuration in the photovoltaic-energy storage system as the optimization variable, constructing an objective function that aims to minimize the total life cycle cost of the energy storage system and the total voltage deviation of the entire grid. Node voltage over-limit behavior is reflected in the objective function through a penalty factor. （12） （13） （14） In the formula: C BESS Indicates the economic cost of scheduling and operating an energy storage system; C Grid The cost of power trading between the distribution network and the upper-level grid; λ is the weighting factor for minimizing the total voltage deviation objective; η represents the penalty coefficient for exceeding the reactive power output limit of the photovoltaic unit; K BESS Defined as the dispatch cost per unit power of an energy storage system; P dis，n，h (t) and P ch，n，h (t) corresponds to the discharge power and charging power of the energy storage system numbered n in time period h, respectively; η represents the overall charging and discharging efficiency of the system. Voltage control of energy storage devices must comply with power balance, network balance, inverter operating capacity, operating limits of energy storage systems, and voltage amplitude constraints of all distribution network nodes. （15） （16） （17） （18） （19） （20） In the formula: P main P represents the total active power injected into the distribution network from the upstream power grid. BESSO P represents the total active power released from the energy storage system to the network. BESSI P refers to the total active power absorbed by energy storage devices from the network. load P represents the active power consumed by all loads in the distribution network. loss This represents the total active power loss generated during network transmission; S OC，max With S OC，min These correspond to the upper and lower limits of the permissible operating state of charge for the energy storage system, respectively.

7. The active-reactive voltage coordinated control method for multiple reactive power compensation devices considering energy storage according to claim 1, characterized in that, In step three, the specific method is to construct a hierarchical-distributed coordinated control architecture: when the voltage exceeds the lower limit, the reactive power support capability of the photovoltaic inverter is prioritized, and the dynamic reactive power compensation device and transformer tap adjustment are coordinated to achieve an initial voltage rise; if the voltage still exceeds the limit, the remaining capacity of the energy storage system is activated to provide auxiliary reactive power compensation, forming a two-layer reactive power support mechanism; when the voltage exceeds the upper limit, the reactive power output adjustment of the photovoltaic inverter and the switching of the capacitor bank are used to achieve rapid voltage suppression. If the effect is insufficient, the active power absorption capability of the energy storage system is activated, and the transformer turns ratio is adjusted to form coordinated control, ultimately dynamically constraining the node voltage within the safe threshold.

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