A virtual power plant control method and system for regional power grid voltage optimization

Abstract

The present invention discloses a virtual power plant control method and system for regional power grid voltage optimization, the system comprising a voltage control function of a distribution automation system, a virtual power plant control system, and a distributed resource controller. The present invention utilizes the aggregation and control capabilities of the virtual power plant to realize the effective voltage monitoring capability of the distribution automation system for distributed resources, and realizes the information interaction between the distribution automation system and the virtual power plant control system; implements voltage optimization control of the distribution network, improves the voltage qualification rate, and reduces line loss; develops previously idle reactive power adjustable resources, thereby reducing the power grid's investment in reactive power and voltage control.

Description

Technical Field

[0001] The present invention relates to power distribution network technology, and in particular to a virtual power plant control method and system for optimizing regional power grid voltage. Background Art

[0002] With the rapid development of renewable energy, a large number of distributed power sources represented by distributed photovoltaic, distributed wind power, and small hydropower have entered the distribution network, which has brought many problems to the voltage control of the distribution network. At peak power, these distributed power sources will increase the voltage at the end of the distribution network, causing problems such as reduced power quality and changes in the direction of system flow, which have seriously affected normal production and living electricity consumption in some places. Due to the dispersion of user loads, long line power supply radius, small line diameter, seasonal distribution transformer overload or even overload, low voltage problems will also occur in the distribution network, especially at the end of the line. Too low power supply voltage will cause the efficiency of some power equipment to decrease, increase the cost of power distribution, and have an adverse impact on the economic operation of the system. However, for a large number of distributed power sources entering the distribution network, the distribution network system cannot be effectively managed and controlled due to the lack of effective tools and technical measures. This makes the voltage stability problem of the distribution network more prominent, not only causing the voltage quality to decline, affecting normal power consumption, but also increasing the line loss of the distribution network.

[0003] At the same time, on the one hand, virtual power plant technology is developing rapidly in my country. Virtual power plants are the aggregation of multiple distributed resources. Through advanced control, communication, and metering technologies, distributed power sources, energy storage, flexible loads and other adjustable resources can be aggregated, and participate in the unified dispatch of the power grid as a whole, making full use of the coordinated complementarity of distributed resource power generation and regulation characteristics, and realizing the rational optimization and utilization of resources. On the other hand, distributed photovoltaic inverters, energy storage converters, charging pile converters and other power electronic devices are four-quadrant converters, which have the functions of active and reactive power decoupling control and the ability to accurately adjust reactive power. At present, most of my country's distributed resource converters (such as photovoltaic inverters) operate in a constant power factor mode, and their own reactive power adjustable capabilities are idle and have not been developed and utilized.

[0004] Therefore, in the regional distribution network where the virtual power plant is built, the virtual power plant technology can be used for voltage optimization and stability control, and the function of voltage reactive power regulation is added to the virtual power plant control system. The parts of the virtual power plant members with reactive power adjustable capabilities, such as photovoltaic inverters and energy storage converters, are organized and dispatched to participate in the voltage optimization control of the distribution network. The method and system in the present invention exchange information with the local distribution automation system, and accept commands from the distribution automation system to control the voltage of each node in the distribution network. The present invention realizes the information exchange between the distribution automation system and the virtual power plant control system; optimizes the voltage situation in the regional distribution network, improves the power quality, and reduces line loss; develops the previously idle reactive power adjustable force, thereby reducing the power grid's investment in reactive and voltage control, such as the investment in setting up static reactive generators, capacitor banks, etc. in the distribution network. Summary of the invention

[0005] Purpose of the invention: The purpose of the present invention is to provide a virtual power plant control method and system for regional power grid voltage optimization, so as to utilize the reactive power adjustable resources in the virtual power plant to optimize the distribution line voltage control, so as to improve the voltage and power quality of the distribution line and reduce line losses.

[0006] Technical solution: A virtual power plant control method for regional power grid voltage optimization according to the present invention comprises the following steps:

[0007] S1: The distribution automation system exchanges data with the virtual power plant control system in the distribution network based on the bus voltage value of the distribution line (10KV or 20KV) and the collected operating status parameters of each node of the line. The parameters substituted include power grid network data, real-time voltage data of each node, active power and reactive power of each node, and reactive power margin of the virtual power plant, and starts the voltage control function of the AVC (Automatic Voltage Control) system;

[0008] S2: The distribution network AVC system determines whether the line loss of the distribution line is too high or the voltage exceeds the limit based on the collected data. If so, it proceeds to the next process. If not, the distribution network AVC function ends.

[0009] S3: If the line loss is too high or the voltage exceeds the limit, the AVC system performs an optimal function calculation and substitutes the optimal objective function for calculation. The objective function takes the weighted sum of the minimum line loss and the minimum voltage deviation of the distribution line as the optimal goal, and performs a solution calculation to obtain the voltage setting value of each node, including the virtual nodes of the virtual power plant;

[0010] S4: The distribution network AVC system sends the voltage setting value of the virtual node to the virtual power plant control system. The virtual power plant control system calculates the total reactive power that the virtual power plant needs to generate and determines whether it meets the total real-time reactive power margin limit of the virtual power plant. If so, it proceeds to the next process. If not, it returns to the previous process for further calculation.

[0011] S5: If the total real-time reactive power margin limit of the virtual power plant is met, the virtual power plant control system performs task allocation calculation to obtain the reactive power borne by each internal member;

[0012] S6: The virtual power plant control system sends the calculation results to each member, and each member calculates and judges whether it meets its own real-time reactive power margin limit. If it does, it enters the next process. If not, it returns to the previous process for further calculation.

[0013] S7: If the real-time reactive power margin limit of each member is met, each member of the virtual power plant executes the reactive power output plan;

[0014] S8: After each member of the virtual power plant executes the reactive power output plan, the execution process is recorded and reactive power is measured, thus ending the operation of this AVC system.

[0015] The step S3 is specifically as follows:

[0016] The optimal objective function of the voltage control function of the AVC system in the distribution automation system takes the weighted sum of line network loss and voltage deviation as the minimum as the optimal target value;

[0017] The optimal goal is as follows:

[0018] F=α·minL+minU (1)

[0019] In the formula, minL is the network loss minimization target of the distribution network, minU is the voltage deviation minimization target of each node in the distribution network, and α is the weighting coefficient;

[0020] The network loss minimization objective of the distribution network is as follows:

[0021]

[0022] In the formula, i∈j means that node i is connected to node j; G ij is the admittance value of the line connecting node i and node j; U i，t is the voltage of node i during period t; θ ij，t is the phase angle difference between node i and node j during period t;

[0023] The voltage deviation minimization target of each node in the distribution network is as follows:

[0024]

[0025] Where U i，t is the voltage of node i during period t, U i，rate is the rated voltage of node i;

[0026] The constraints are: for the voltage over-limit caused by the access of distributed photovoltaic and other distributed power sources to the regional power grid, network security constraints need to be considered to ensure the safety and stability of the power grid and give priority to the continuous and reliable supply of electric energy; network security constraints are as shown in formula 4:

[0027]

[0028] In the formula, and are the lower and upper limits of the voltage allowed at node i respectively; S l，t is the transmission capacity of line l; and are the lower and upper limits of the transmission capacity allowed by line l respectively.

[0029] The calculation method of the reactive power margin described in steps S1, S4-S7 is:

[0030] The apparent power S1 of the converters of each distributed resource (such as photovoltaic inverters, energy storage converters, etc.) included in the virtual power plant, and its maximum value S max is fixed. The active power P1 of the converter cannot be adjusted in this function. If the reactive power Q1 of the converter can be adjusted, it must be limited by the apparent power. The converter must calculate the real-time reactive power margin it can generate based on the real-time active power of the converter, as shown in Formula 5:

[0031]

[0032] get

[0033] Therefore, the reactive power adjustable margin of this distributed resource is:

[0034]

[0035] In the formula, S max is the maximum apparent power of the converter, P1 is the active power of the converter, and Q1 is the reactive power of the converter.

[0036] The method in which the virtual power plant control system in step S4 calculates the total reactive power that the virtual power plant needs to generate is:

[0037] The voltage difference between the converter output voltage of each distributed resource and its grid-connected node depends on the active power P, reactive power Q and access equivalent impedance, and follows Formula 7:

[0038]

[0039] In the formula, ΔU is the voltage deviation, P is the active power, Q is the reactive power, and U is n is the node rated voltage, R and X are the resistance and reactance in the access equivalent impedance respectively; it can be seen from Formula 7 that when the voltage deviation, active power, node rated voltage and equivalent impedance are obtained, the reactive power Q required to be injected into the distribution network can be calculated.

[0040] The step S5 is specifically as follows:

[0041] The reactive power allocation of each distributed resource in the virtual power plant can be achieved through droop control and node voltage. Assuming that there are n distributed resource members in the virtual power plant, as shown in Formula 8:

[0042] V i =V 0i -n i Q i ,i=1,2,3,…,n (8)

[0043] Where V i is the terminal voltage of distributed resource i, V 0i is the terminal voltage when the distributed resource i has zero output, Q i is the reactive power output of distributed resource i, n i is the reactive power droop coefficient of distributed resource i;

[0044] Since the distributed resources in the virtual power plant are all connected to the same distribution line and the voltage at the outlet remains stable, assuming that the terminal voltage of each distributed resource is equal to the terminal voltage at zero output, we have Equation 9:

[0045] n1Q1=n2Q2=…=n n Q n (9)

[0046] The reactive power task allocation within the virtual power plant is allocated according to the real-time reactive power margin of each distributed resource, as shown in Formula 10:

[0047]

[0048] Where Q i The reactive power task assigned to distributed resource i, Q imax is the maximum reactive power margin of distributed resource i, Q max is the total maximum reactive power margin of the virtual power plant, Q total is the total reactive power task obtained by the virtual power plant;

[0049] Assume that the distributed resource with the largest apparent power is 1. According to formula 10, Q1 of distributed resource 1 can be obtained. Then substitute the obtained Q1 into formula 8 to obtain n1. After n1 is obtained, substitute it into formula 9 to obtain the droop coefficients n of all other distributed resources. i ;

[0050] The virtual power plant control system calculates the droop coefficients n of all distributed resources i It is sent to the controllers of each distributed resource to start executing the reactive power adjustable task.

[0051] A virtual power plant control system for regional power grid voltage optimization, the system adopts the above-mentioned virtual power plant control method for regional power grid voltage optimization, the system includes a voltage control function of a distribution automation system, a virtual power plant control system, and a distributed resource controller;

[0052] The voltage control function of the distribution automation system is realized by the AVC system to control the voltage of each node of the distribution network; the virtual power plant control system includes the system's software functions, system architecture and information access methods; the distributed resource controller can realize the decoupling control of active power and reactive power, and has the ability to accurately adjust reactive power;

[0053] The voltage control function of the distribution automation system collects data and optimizes calculations to obtain the voltage setting value of each node in the distribution network and sends it to various devices including the virtual power plant. After the virtual power plant control system accepts the voltage reactive power regulation task, it assigns the task to the subordinate distributed resources for execution, thereby realizing the voltage optimization management of a large number of distributed resources in the distribution network;

[0054] The virtual power plant control system is divided into five layers, namely, equipment layer, measurement layer, substation layer, network layer, and master station layer; the equipment layer includes distributed photovoltaic, energy storage, electric vehicle charging piles, building users and other electrical equipment; the measurement layer includes smart terminals, smart meters, three-phase multi-functional monitoring equipment, sensors, energy storage converters with measurement capabilities, inverters, etc.; the substation layer includes distributed resource controllers, third-party control systems, etc.; the network layer includes various network communication methods such as GPRS, optical fiber, 5G, and power dedicated networks; the master station layer includes virtual power plant control systems, and security access devices to distribution automation systems and power trading systems.

[0055] Beneficial effects: Compared with the prior art, the present invention has the following advantages:

[0056] 1. The present invention realizes that the distribution automation system uses the virtual power plant system to coordinate and optimize the voltage of each node of the distribution network, improve the voltage qualification rate, and reduce network loss;

[0057] 2. The present invention enables the distribution automation system to interact with the virtual power plant control system for graphical data and accept data collected by the external system;

[0058] 3. The present invention utilizes virtual power plants to aggregate and utilize the reactive power adjustable resources of distributed resources that were previously unavailable, thereby enhancing the reactive power adjustable capacity of the distribution network;

[0059] 4. The present invention reduces the investment of the power grid in hardware equipment for reactive power and voltage control. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 This is a schematic diagram of the distribution network line;

[0061] Figure 2 It is the line conversion diagram of the distribution network;

[0062] Figure 3 To execute the flow chart;

[0063] Figure 4 This is the functional architecture diagram of the virtual power plant control system;

[0064] Figure 5 This is the system diagram of the virtual power plant. DETAILED DESCRIPTION

[0065] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0066] A virtual power plant control method for regional power grid voltage optimization comprises the following steps:

[0067] S1: The distribution automation system exchanges data with the virtual power plant control system in the distribution network based on the bus voltage value of the distribution line (10KV or 20KV) and the collected operating status parameters of each node of the line. The parameters substituted include power grid network data, real-time voltage data of each node, active power and reactive power of each node, and reactive power margin of the virtual power plant, and starts the voltage control function of the AVC (Automatic Voltage Control) system.

[0068] like Figure 1 As shown in the example, in the distribution line, the distributed resources connected in the line, such as distributed power sources, energy storage, electric vehicle charging piles, etc., are aggregated into a virtual power plant. Through circuit conversion calculation, for the voltage control function of the distribution automation system, the virtual power plant is regarded as an independent entity in the distribution line, an AC generator with bidirectional energy flow, connected to the distribution network through a virtual node i. When calculating the AVC function, the virtual node i is also directly used as the object.

[0069] S2: The distribution network AVC system determines based on the collected data whether the line loss of the distribution line is too high or the voltage exceeds the limit. If so, it proceeds to the next process. If not, the distribution network AVC function ends.

[0070] S3: If the line loss is too high or the voltage exceeds the limit, the AVC system calculates the optimal function and substitutes the optimal objective function for calculation. The objective function takes the weighted sum of the minimum line loss and the minimum voltage deviation of the distribution line as the optimal goal, and solves the calculation to obtain the voltage setting value of each node (including the virtual nodes of the virtual power plant).

[0071] The optimal objective function of the voltage control function of the AVC system in the distribution automation system takes the weighted sum of line network loss and voltage deviation as the minimum as the optimal target value;

[0072] The optimal goal is as follows:

[0073] F=α·minL+minU (1)

[0074] In the formula, minL is the network loss minimization target of the distribution network, minU is the voltage deviation minimization target of each node in the distribution network, and α is the weighting coefficient;

[0075] The network loss minimization objective of the distribution network is as follows:

[0076]

[0077] In the formula, i∈j means that node i is connected to node j; G ij is the admittance value of the line connecting node i and node j; U i，t is the voltage of node i during period t; θ ij，t is the phase angle difference between node i and node j during period t;

[0078] The voltage deviation minimization target of each node in the distribution network is as follows:

[0079]

[0080] Where U i，t is the voltage of node i during period t, U i，rate is the rated voltage of node i;

[0081] The constraints are: for the voltage over-limit caused by the access of distributed photovoltaic and other distributed power sources to the regional power grid, network security constraints need to be considered to ensure the safety and stability of the power grid and give priority to the continuous and reliable supply of electric energy; network security constraints are as shown in formula 4:

[0082]

[0083] In the formula, and are the lower and upper limits of the voltage allowed at node i respectively; S l，t is the transmission capacity of line 1; and They are respectively the lower and upper limits of the transmission capacity allowed for line 1.

[0084] S4: The distribution network AVC system sends the voltage setting value of the virtual node to the virtual power plant control system. The virtual power plant control system calculates the total reactive power that the virtual power plant needs to emit and determines whether it meets the total real-time reactive power margin limit of the virtual power plant. If so, it enters the next process. If not, it returns to the previous process for further calculation.

[0085] The distribution network AVC system sends the voltage setting value of the virtual node to the virtual power plant control system. The method by which the virtual power plant control system calculates the total reactive power that the virtual power plant needs to generate is:

[0086] The voltage difference between the converter output voltage of each distributed resource and its grid-connected node depends on the active power P, reactive power Q and access equivalent impedance, and follows Formula 7:

[0087]

[0088] In the formula, ΔU is the voltage deviation, P is the active power, Q is the reactive power, and U is n is the node rated voltage, R and X are the resistance and reactance in the access equivalent impedance respectively; it can be seen from Formula 7 that when the voltage deviation, active power, node rated voltage and equivalent impedance are obtained, the reactive power Q required to be injected into the distribution network can be calculated.

[0089] S5: If the total real-time reactive power margin limit of the virtual power plant is met, the virtual power plant control system performs task allocation calculations to obtain the reactive power borne by each internal member.

[0090] The reactive power allocation of each distributed resource in the virtual power plant can be achieved through droop control and node voltage. Assuming that there are n distributed resource members in the virtual power plant, as shown in Formula 8:

[0091] V i =V 0i -n i Q i ,i=1,2,3,…,n (8)

[0092] Where V i is the terminal voltage of distributed resource i, V 0i is the terminal voltage when the distributed resource i has zero output, Q i is the reactive power output of distributed resource i, n iis the reactive power droop coefficient of distributed resource i;

[0093] Since the distributed resources in the virtual power plant are all connected to the same distribution line and the voltage at the outlet remains stable, assuming that the terminal voltage of each distributed resource is equal to the terminal voltage at zero output, we have Equation 9:

[0094] n1Q1=n2Q2=…=n n Q n (9)

[0095] The reactive power task allocation within the virtual power plant is allocated according to the real-time reactive power margin of each distributed resource, as shown in Formula 10:

[0096]

[0097] Where Q i The reactive power task assigned to distributed resource i, Q imax is the maximum reactive power margin of distributed resource i, Q max is the total maximum reactive power margin of the virtual power plant, Q total is the total reactive power task obtained by the virtual power plant;

[0098] Assume that the distributed resource with the largest apparent power is 1. According to formula 10, Q1 of distributed resource 1 can be obtained. Then substitute the obtained Q1 into formula 8 to obtain n1. After n1 is obtained, substitute it into formula 9 to obtain the droop coefficients n of all other distributed resources. i ;

[0099] The virtual power plant control system calculates the droop coefficients n of all distributed resources i It is sent to the controllers of each distributed resource to start executing the reactive power adjustable task.

[0100] S6: The virtual power plant control system sends the calculation results to each member, and each member makes its own calculations to determine whether it meets its own real-time reactive power margin limit. If so, it enters the next process; if not, it returns to the previous process and calculates again.

[0101] S7: If the real-time reactive power margin limit of each member is met, each member of the virtual power plant executes the reactive power output plan.

[0102] The calculation method of the reactive power margin described in steps S1, S4-S7 is:

[0103] The apparent power S1 of the converters of each distributed resource (such as photovoltaic inverters, energy storage converters, etc.) included in the virtual power plant, and its maximum value S maxis fixed. The active power P1 of the converter cannot be adjusted in this function. If the reactive power Q1 of the converter can be adjusted, it must be limited by the apparent power. The converter must calculate the real-time reactive power margin it can generate based on the real-time active power of the converter, as shown in Formula 5:

[0104]

[0105] get

[0106] Therefore, the reactive power adjustable margin of this distributed resource is:

[0107]

[0108] In the formula, S max is the maximum apparent power of the converter, P1 is the active power of the converter, and Q1 is the reactive power of the converter.

[0109] S8: After each member of the virtual power plant executes the reactive power output plan, the execution process is recorded and reactive power is measured, thus ending the operation of this AVC system.

[0110] A virtual power plant control system for regional power grid voltage optimization, the system adopts the above-mentioned virtual power plant control method for regional power grid voltage optimization, the system is divided into five layers, namely equipment layer, measurement layer, substation layer, network layer, and main station layer; the equipment layer includes distributed photovoltaic, energy storage, electric vehicle charging piles, and building users; the measurement layer includes smart terminals, smart meters, three-phase multifunctional monitoring equipment, sensors, energy storage converters with measurement capabilities, and inverters; the substation layer includes distributed resource controllers and third-party control systems; the network layer includes GPRS, optical fiber, 5G, and power dedicated networks; the main station layer includes a virtual power plant control system and a security access device to a distribution automation system and a power trading system.

[0111] The method and system submitted in the present invention are applicable to the distribution lines (10KV or 20KV) in which virtual power plants are built, with the purpose of controlling and optimizing the line loss and voltage deviation rate of the distribution lines, and taking the virtual power plants as the control objects. The distribution automation system establishes reactive voltage monitoring of the entire distribution line, performs voltage optimization calculation on the entire distribution line, obtains the voltage setting value and sends it to the virtual power plant control system for execution. Figure 1 In the example shown in the figure, there is a radial distribution line. After the distribution line busbar is connected, there are 1 to 10 nodes in sequence. Among them, the distributed resources under nodes 2 to 6, such as distributed power sources, energy storage, electric vehicle charging piles, etc., are aggregated into a virtual power plant, and the other nodes are loads. The distributed resources under nodes 2 to 6 are aggregated to build a virtual power plant. Figure 2Through circuit conversion calculation, the virtual power plant can be regarded as an AC generator with bidirectional energy flow, connected to the distribution network through a virtual node i, and regarded as an independent entity in the distribution line. Multiple virtual nodes can also be set according to the grid access status of each member under the virtual power plant.

[0112] like Figure 3 The figure shows the process of using the virtual power plant to participate in the reactive power voltage control method of the distribution network. First, the voltage control function (AVC system) in the distribution network automation system is started; the distribution network AVC system determines whether the line loss of the 10KV distribution line is too high or the voltage exceeds the limit based on the collected data. If so, the next process is carried out, if not, the distribution network AVC action is terminated; if the line loss is too high or the voltage exceeds the limit, the AVC calculates the optimal function and obtains the calculation result; the distribution network AVC system sends the calculation result to the virtual power plant control system, and the virtual power plant control system calculates and determines whether it meets the virtual power plant control system. The total real-time reactive power margin limit of the plant, if met, will enter the next process, if not, return to the previous process and calculate again; if the total real-time reactive power margin limit of the virtual power plant is met, the virtual power plant control system calculates and obtains the reactive power borne by each internal member; the virtual power plant control system sends the calculation result to each member, and each member calculates and judges whether it meets its own real-time reactive power margin limit. If met, it will enter the next process, if not, return to the previous process and calculate again; if the real-time reactive power margin limit of each member is met, each member of the virtual power plant executes the reactive output plan; end.

[0113] The virtual power plant control system in the present invention can complete the interaction of graphic model data with the distribution automation system, and realize the monitoring, control and analysis functions of the distribution network voltage and line loss based on this model. The virtual power plant control system can complete the construction of distributed resource models, graphic drawing and other tasks, and establish a graphic model relationship with the distribution automation system, establish the relationship of "distributed resources-substation-medium voltage distribution transformer", and realize the monitoring, control and analysis functions based on this model. The voltage and reactive power adjustable function of the virtual power plant control system obtains the distribution network model and data of the distribution automation system. The model data can be in CIME file format, and the data can be in E file format. The distribution automation system receives 400V distributed photovoltaic measurement data and ledger information forwarded by the virtual power plant platform.

[0114] like Figure 4The virtual power plant control system in the present invention is shown, and the functional modules mainly include archive management, virtual power plant data management, forecasting function, virtual power plant construction, virtual power plant dispatching control, market transaction, demand response, system interaction interface, and voltage reactive power adjustable, a total of nine functional modules. The system first builds a virtual power plant through the registration and data management of participating users, determines the total resource volume of the virtual power plant (including total active power adjustable potential, total reactive power margin, etc.), and then aggregates it into a unified entity, which can participate in power grid regulation, electricity transactions, demand response transactions and other power transactions, and manages and maintains users and equipment participating in the virtual power plant.

[0115] Among them, the voltage reactive power adjustable function module undertakes the task of the virtual power plant participating in the voltage and reactive power optimization of the distribution network, and includes four sub-function modules: reactive power margin, reactive task allocation, voltage deviation, and execution result. The reactive power margin is used for real-time calculation of reactive power margin, including the total real-time margin and the real-time margin of each subject. The reactive task allocation is used for the reactive power task allocation of each member in the virtual power plant, that is, the reactive power borne by each member in real time. The voltage deviation is used for real-time monitoring of the voltage of each node (including virtual nodes) of the virtual power plant in the distribution network, and for real-time display of the deviation between the actual voltage and the voltage setting value. The execution result is used for each member to record the execution status and measure the execution results after completing the voltage and reactive power adjustment tasks.

Claims

1. A virtual power plant control method for regional power grid voltage optimization, characterized in that: The following steps are involved: S1: The distribution automation system exchanges data with the virtual power plant control system in the distribution network based on the bus voltage value of the distribution line and the collected operating status parameters of each node of the line. The input data includes the power grid network data, the real-time voltage data of each node, the active power and reactive power of each node, and the reactive power margin of the virtual power plant, and starts the voltage control function of the AVC system under the distribution automation system; S2: The distribution network AVC system determines whether the line loss of the distribution line is too high or the voltage exceeds the limit based on the collected data. If so, it proceeds to the next process. If not, the distribution network AVC function ends. S3: If the line loss is too high or the voltage exceeds the limit, the AVC system calculates the optimal function and substitutes it into the optimal objective function for calculation. The objective function takes the weighted sum of the minimum line loss and the minimum voltage deviation of the distribution line as the optimal goal, and solves the calculation to obtain the voltage setting value of each node; S4: The distribution network AVC system sends the voltage setting value of the virtual node to the virtual power plant control system. The virtual power plant control system calculates the total reactive power that the virtual power plant needs to generate and determines whether it meets the total real-time reactive power margin limit of the virtual power plant. If so, it proceeds to the next process. If not, it returns to the previous process for further calculation. S5: If the total real-time reactive power margin limit of the virtual power plant is met, the virtual power plant control system performs task allocation calculation to obtain the reactive power borne by each internal member; S6: The virtual power plant control system sends the calculation results to each member, and each member calculates and judges whether it meets its own real-time reactive power margin limit. If it does, it enters the next process. If not, it returns to the previous process for further calculation. S7: If the real-time reactive power margin limit of each member is met, each member of the virtual power plant executes the reactive power output plan; S8: After each member of the virtual power plant executes the reactive power output plan, the execution process is recorded and reactive power is measured, ending the operation of this AVC system; The step S3 is specifically as follows: The optimal objective function of the voltage control function of the AVC system in the distribution automation system takes the weighted sum of line network loss and voltage deviation as the minimum as the optimal target value; The optimal goal is as follows: F=α·minL+minU(1) In the formula, minL is the network loss minimization target of the distribution network, minU is the voltage deviation minimization target of each node in the distribution network, and α is the weighting coefficient; The network loss minimization objective of the distribution network is as follows: In the formula, i∈j means that node i is connected to node j; G ij is the admittance value of the line connecting node i and node j; U i,t is the voltage of node i during period t; θ ij,t is the phase angle difference between node i and node j during period t; The voltage deviation minimization target of each node in the distribution network is as follows: Where U i,t is the voltage of node i during period t, U i,rate is the rated voltage of node i; The constraints are: for the voltage over-limit caused by the access of distributed photovoltaic and other distributed power sources to the regional power grid, network security constraints need to be considered to ensure the safety and stability of the power grid and give priority to the continuous and reliable supply of electric energy; network security constraints are as shown in formula 4: In the formula, and are the lower and upper limits of the voltage allowed at node i respectively; S l,t is the transmission capacity of line l; and are the lower and upper limits of the transmission capacity allowed by line l respectively; The calculation method of the reactive power margin described in steps S1, S4-S7 is: The apparent power S1 of the converter of each distributed resource included in the virtual power plant, and its maximum value S max is fixed. The active power P1 of the converter cannot be adjusted in this function. If the reactive power Q1 of the converter can be adjusted, it must be limited by the apparent power. The converter must calculate the real-time reactive power margin it can generate based on the real-time active power of the converter, as shown in Formula 5: get Therefore, the reactive power adjustable margin of this distributed resource is: In the formula, S max is the maximum apparent power of the converter, P1 is the active power of the converter, and Q1 is the reactive power of the converter.

2. A virtual power plant control method for regional power grid voltage optimization according to claim 1, characterized in that: The voltage of the power distribution line described in step S1 is 10KV or 20KV.

3. A virtual power plant control method for regional power grid voltage optimization according to claim 1, characterized in that: The nodes described in step S3 include virtual nodes of the virtual power plant.

4. A virtual power plant control method for regional power grid voltage optimization according to claim 1, characterized in that: The method in which the virtual power plant control system in step S4 calculates the total reactive power that the virtual power plant needs to generate is: The voltage difference between the converter output voltage of each distributed resource and its grid-connected node depends on the active power P, reactive power Q and access equivalent impedance, and follows Formula 7: In the formula, ΔU is the voltage deviation, P is the active power, Q is the reactive power, and U is n is the node rated voltage, R and X are the resistance and reactance in the access equivalent impedance respectively; from Formula 7, it can be seen that when the voltage deviation, active power, node rated voltage and equivalent impedance are obtained, the reactive power Q required to be injected into the distribution network can be calculated.

5. A virtual power plant control method for regional power grid voltage optimization according to claim 1, characterized in that: The step S5 is specifically as follows: The reactive power allocation of each distributed resource in the virtual power plant can be achieved through droop control and node voltage. Assuming that there are n distributed resource members in the virtual power plant, as shown in Formula 8: V i =V 0i -n i Q i ,i=1,2,3,…,n (8) Where V i is the terminal voltage of distributed resource i, V 0i is the terminal voltage when the distributed resource i has zero output, Q i is the reactive power output of distributed resource i, n i is the reactive power droop coefficient of distributed resource i; Since the distributed resources in the virtual power plant are all connected to the same distribution line and the voltage at the outlet remains stable, assuming that the terminal voltage of each distributed resource is equal to the terminal voltage at zero output, we have Equation 9: n1Q1=n2Q2=…=n n Q n (9) The reactive power task allocation within the virtual power plant is allocated according to the real-time reactive power margin of each distributed resource, as shown in Formula 10: Where Q i The reactive power task assigned to distributed resource i, Q imax is the maximum reactive power margin of distributed resource i, Q max is the total maximum reactive power margin of the virtual power plant, Q total is the total reactive power task obtained by the virtual power plant; Assume that the distributed resource with the largest apparent power is 1. According to formula 10, Q1 of distributed resource 1 can be obtained. Then substitute the obtained Q1 into formula 8 to obtain n1. After n1 is obtained, substitute it into formula 9 to obtain the droop coefficients n of all other distributed resources. i ; The virtual power plant control system calculates the droop coefficients n of all distributed resources i It is sent to the controllers of each distributed resource to start executing the reactive power regulation task.

6. A virtual power plant control system for regional power grid voltage optimization, the system adopts a virtual power plant control method for regional power grid voltage optimization as claimed in any one of claims 1 to 5, characterized in that: The system includes the voltage control function of the distribution automation system, the virtual power plant control system, and the distributed resource controller; The voltage control function of the distribution automation system is realized by the AVC system to control the voltage of each node of the distribution network; the virtual power plant control system includes the system's software functions, system architecture and information access methods; the distributed resource controller can realize the decoupling control of active power and reactive power, and has the ability to accurately adjust reactive power; The voltage control function of the distribution automation system collects data and optimizes calculations to obtain the voltage setting value of each node in the distribution network and sends it to various devices including the virtual power plant. After the virtual power plant control system accepts the voltage reactive power regulation task, it assigns the task to the subordinate distributed resources for execution, thereby realizing the voltage optimization management of a large number of distributed resources in the distribution network; The virtual power plant control system is divided into five layers, namely, equipment layer, measurement layer, substation layer, network layer, and master station layer; the equipment layer includes distributed photovoltaics, energy storage, electric vehicle charging piles, and building users; the measurement layer includes smart terminals, smart meters, three-phase multifunctional monitoring equipment, sensors, energy storage converters with measurement capabilities, and inverters; the substation layer includes distributed resource controllers and third-party control systems; the network layer includes GPRS, optical fiber, 5G, and power dedicated networks; the master station layer includes a virtual power plant control system and a secure access device to the distribution automation system and the power trading system.

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