Distributed resource main body active and reactive cooperation P2P regulation and control method and device

Abstract

The invention discloses a distributed resource main body active and reactive cooperation P2P regulation and control method and device, and relates to the field of distributed resource regulation and control. The method comprises the steps of performing active power P2P optimization scheduling by taking the minimum active operation cost of each distributed resource node as a target, and determining the reactive power output obligation amount of each distributed resource main body; solving the optimal power flow model by taking minimization of the sum of the network loss of the power distribution network and the voltage out-of-limit as a target, and obtaining a reactive power regulation threshold value of each distributed resource main body; establishing a reactive P2P regulation and control model of each distributed resource node by taking the minimum reactive operation cost of each distributed resource node as a target and taking the condition that the reactive output of each distributed resource main body is smaller than or equal to the respective reactive regulation threshold value as a constraint; and solving the reactive P2P regulation and control model to obtain a reactive P2P regulation and control result of each distributed resource main body in each distributed resource node. Safe operation of the power distribution network can be ensured, and the photovoltaic bearing capacity of the power distribution network is improved.

Description

Technical Field

[0001] The present application relates to the field of distributed resource control, and in particular to a distributed resource subject active and reactive power collaborative P2P (Peer-to-Peer, peer-to-peer computing) control method and device. Background Art

[0002] At present, distributed photovoltaic and energy storage have been connected to the distribution network on a large scale, but the randomness and volatility of distributed photovoltaic have brought challenges to the operation of the distribution network: the high density and multi-point access of distributed photovoltaic can easily cause sharp instantaneous voltage fluctuations, leading to local overload of the distribution network and frequent voltage over-limit, and voltage safety constraints are the key factors limiting the access and consumption of distributed photovoltaic. If the "one-size-fits-all" access principle is adopted for photovoltaic, there will be a lack of systematic consideration of load-side demand response, photovoltaic storage synergy, photovoltaic inverter power factor adjustment and other means to improve photovoltaic carrying capacity.

[0003] With the large-scale access of distributed resources, distributed resources are invested and operated by different entities. How to promote the maximum consumption of distributed photovoltaics by coordinating the active / reactive regulation capabilities of photovoltaics, energy storage, and controllable loads on the basis of considering the interests of multiple entities, and ensure the safe operation of the distribution network and effectively improve the carrying capacity of the distribution network has become a difficult problem that needs to be solved in the current development of new distribution networks. In-depth research and resolution of these issues are of great significance to promoting the development of distribution networks in a more intelligent and efficient direction.

[0004] In order to solve the contradiction of conflicting interests among multiple subjects in regulation, distributed resource regulation based on distributed P2P mode has been proposed and received widespread attention. In the P2P mode, distributed resource subjects can achieve autonomous regulation through self-organized P2P interaction, thereby stimulating the enthusiasm of distributed resource subjects to participate and promoting the optimization of distribution network operation. In addition, considering that distributed resource subjects are good voltage regulation resources, such as distributed photovoltaics can effectively use the remaining capacity of photovoltaic inverters to absorb or release reactive power and regulate the voltage of the power grid; distributed energy storage can absorb or release energy by regulating reactive power and using the bidirectional converter characteristics of the energy storage system, thereby regulating the voltage of the power grid. Discussion of existing technical solutions On the basis of promoting the local consumption of distributed photovoltaics through active P2P regulation, the reactive regulation capability of distributed resources is utilized to participate in the voltage regulation of the distribution network to ensure the safe operation of the distribution network.

[0005] Among the existing technical solutions for improving photovoltaic carrying capacity through active and reactive power coordinated optimization, there are two technical routes: one is centralized active and reactive power coordinated regulation, and the other is distributed active and reactive power coordinated regulation. The problems existing in the two technical routes are as follows (1)-(2).

[0006] (1) The technical route of centralized active and reactive power coordinated control ensures that the voltage does not exceed the limit by coordinating the operation of distributed resources. However, this technical route is mostly applicable when all devices belong to the same operation entity. With the wide access of distributed resources, the distributed resource entities have the characteristics of diverse interest entities. It is unrealistic for these distributed resource entities to respond to regulation centrally. A distributed operation mode is needed to meet the actual regulation requirements and scenarios.

[0007] (2) The active power regulation objective of distributed active and reactive power coordinated control is to minimize the total operating cost, and the objective function of reactive power regulation is to minimize the network loss and overall voltage deviation of the distribution network. For reactive power regulation, on the one hand, the inverter loss cost caused by the voltage regulation of distributed resource entities is ignored, and on the other hand, the responsibility assignment of each distributed resource entity in the voltage regulation task is not clear. Most of the regulation strategies are determined according to the voltage regulation effect or adjustable capacity, which is difficult to ensure the fair and effective implementation of distribution network regulation. From the perspective of sustainable development, this technical route is not conducive to stimulating distributed resource entities with reactive power regulation capabilities to participate in the distribution network voltage regulation task, thus affecting the consumption of photovoltaic power or the voltage stability of the distribution network. Summary of the Invention

[0008] The purpose of the present application is to provide a distributed resource entity active and reactive power coordinated P2P control method and device, which can ensure the safe operation of the distribution network and improve the photovoltaic carrying capacity of the distribution network.

[0009] To achieve the above object, the present application provides the following solutions.

[0010] In the first aspect, the present application provides a distributed resource entity active and reactive power coordinated P2P control method, including the following steps.

[0011] Taking the minimum active operating cost of each distributed resource node as the goal, perform active power P2P optimal scheduling to obtain the active power regulation results of each distributed resource entity in each distributed resource node; multiple distributed resource entities are installed in each distributed resource node.

[0012] According to the active power regulation results of each distributed resource entity in each distributed resource node, considering the impact of the distributed resource entity on the network voltage, determine the reactive power output obligation amount of each distributed resource entity in each distributed resource node.

[0013] According to the active power regulation results of each distributed resource entity in each distributed resource node, taking the minimization of the sum of distribution network loss and voltage over-limit as the goal, solve the optimal power flow model to obtain the reactive power regulation threshold of each distributed resource entity in each distributed resource node.

[0014] Based on the principle of obtaining rewards for the part where the reactive power capacity exceeds the reactive power output obligation and paying for the part where the reactive power capacity is less than the reactive power output obligation, with the goal of minimizing the reactive power operation cost of each distributed resource node and the reactive power output of each distributed resource entity being less than or equal to its respective reactive power regulation threshold as a constraint, a reactive power P2P regulation model for each distributed resource node is established; the reactive power operation cost includes the inverter loss cost.

[0015] According to the reactive power output obligation and reactive power regulation threshold of each distributed resource entity in each distributed resource node, solve the reactive power P2P regulation model of each distributed resource node to obtain the reactive power P2P regulation result of each distributed resource entity in each distributed resource node.

[0016] In a second aspect, the present application provides a distributed resource entity active and reactive power collaborative P2P regulation device, including: an active power regulation module, a reactive power output obligation determination module, a reactive power regulation threshold solving module, a reactive power P2P regulation model establishment module, and a reactive power P2P regulation solving module.

[0017] The active power regulation module is used to perform active power P2P optimal scheduling with the goal of minimizing the active power operation cost of each distributed resource node to obtain the active power regulation result of each distributed resource entity in each distributed resource node; multiple distributed resource entities are installed in each distributed resource node.

[0018] The reactive power output obligation determination module is used to determine the reactive power output obligation of each distributed resource entity in each distributed resource node according to the active power regulation result of each distributed resource entity in each distributed resource node, considering the impact of the distributed resource entity on the network voltage.

[0019] The reactive power regulation threshold solving module is used to solve the optimal power flow model with the goal of minimizing the sum of the distribution network power loss and voltage violation according to the active power regulation result of each distributed resource entity in each distributed resource node to obtain the reactive power regulation threshold of each distributed resource entity in each distributed resource node.

[0020] The reactive power P2P regulation model establishment module is used to establish a reactive power P2P regulation model for each distributed resource node based on the principle of obtaining rewards for the part where the reactive power capacity exceeds the reactive power output obligation and paying for the part where the reactive power capacity is less than the reactive power output obligation, with the goal of minimizing the reactive power operation cost of each distributed resource node and the reactive power output of each distributed resource entity being less than or equal to its respective reactive power regulation threshold as a constraint; the reactive power operation cost includes the inverter loss cost.

[0021] The reactive power P2P regulation and solution module is used to solve the reactive power P2P regulation model of each distributed resource node according to the reactive power output obligation and reactive power regulation threshold of each distributed resource entity in each distributed resource node, and obtain the reactive power P2P regulation result of each distributed resource entity in each distributed resource node.

[0022] According to the specific embodiments provided by the present application, the present application has the following technical effects.

[0023] The present application provides a method and device for active and reactive power collaborative P2P regulation of distributed resource entities. On the basis of guaranteeing the interests of multiple distributed resource entities, with the goal of minimizing the active power operation cost of each distributed resource node, active power P2P optimal scheduling is carried out; considering the impact of distributed resource entities on the network voltage, the reactive power obligation output of each distributed resource entity is defined, and the voltage regulation responsibility of distributed resource entities is determined preferentially; based on the principle of obtaining rewards for the part where the reactive power capacity exceeds the reactive power output obligation and paying for the part where the reactive power capacity is less than the reactive power output obligation, with the goal of minimizing the reactive power operation cost of each distributed resource node, a reactive power P2P regulation model is established, and the excess or deficiency of the reactive power generated by the distributed resource node compared with the specified obligation is traded in the reactive power P2P optimal regulation, guiding the distributed resource entities to actively participate in the voltage regulation of the distribution network. On the basis of guaranteeing the interests of multiple distributed resource entities, the present application promotes the consumption of photovoltaic power through active power P2P regulation, and at the same time ensures the voltage stability of the distribution network through reactive power P2P regulation, effectively improving the photovoltaic carrying capacity of the distribution network. Description of the Drawings

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required to be used in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0025] Figure 1 It is a schematic flowchart of a method for active and reactive power collaborative P2P regulation of distributed resource entities provided by an embodiment of the present application.

[0026] Figure 2 It is a framework diagram of a method for active and reactive power collaborative P2P regulation of distributed resource entities provided by an embodiment of the present application.

[0027] Figure 3 It is a schematic diagram of the functional modules of a device for active and reactive power collaborative P2P regulation of distributed resource entities provided by another embodiment of the present application. Detailed Embodiments

[0028] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0029] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0030] In an exemplary embodiment, as Figure 1 shown, a distributed resource entity active and reactive power collaborative P2P regulation method is provided, including the following steps 101 to 105.

[0031] Step 101: With the goal of minimizing the active operating cost of each distributed resource node, perform active power P2P optimal scheduling to obtain the active power regulation results of each distributed resource entity in each distributed resource node; multiple distributed resource entities are installed in each distributed resource node.

[0032] Step 102: According to the active power regulation results of each distributed resource entity in each distributed resource node, considering the impact of the distributed resource entity on the network voltage, determine the reactive power output obligation of each distributed resource entity in each distributed resource node.

[0033] Step 103: According to the active power regulation results of each distributed resource entity in each distributed resource node, with the goal of minimizing the sum of the distribution network power loss and voltage violation, solve the optimal power flow model to obtain the reactive power regulation threshold of each distributed resource entity in each distributed resource node.

[0034] Step 104: Based on the principle of obtaining rewards for the part where the reactive power capacity exceeds the reactive power output obligation and paying for the part where the reactive power capacity is less than the reactive power output obligation, with the goal of minimizing the reactive operating cost of each distributed resource node and with the constraint that the reactive power output of each distributed resource entity is less than or equal to its respective reactive power regulation threshold, establish the reactive power P2P regulation model of each distributed resource node; the reactive operating cost includes the inverter loss cost.

[0035] Step 105: According to the reactive power output obligation and reactive power regulation threshold of each distributed resource entity in each distributed resource node, solve the reactive power P2P regulation model of each distributed resource node to obtain the reactive power P2P regulation results of each distributed resource entity in each distributed resource node.

[0036] Implementing the above steps 101 to 105, while ensuring maximum PV accommodation through active P2P regulation and peak-valley arbitrage of energy storage, the reactive P2P regulation is used to guide distributed resource entities to participate in voltage optimization, ensuring the safe operation of the distribution network, and improving the PV carrying capacity from two aspects: active P2P promoting PV accommodation + reactive P2P ensuring voltage stability. The PV carrying capacity generally refers to the maximum capacity of distributed PV that can be connected under the constraints of safe operation.

[0037] In another exemplary embodiment of the present application, it is assumed that each distributed resource node is equipped with distributed resource entities such as distributed generators (DG), photovoltaics (PV), or energy storage (ES), and has a certain adjustable flexible load. When optimizing the active power P2P scheduling, the goal of each distributed resource entity is to minimize its own operating cost through the scheduling of its own distributed resources and the decision-making of P2P trading strategies. For the distributed resource node , where

[0038] ; ; ; In the formula, is the active operating cost of the distributed resource node ; is the active decision variable of the distributed resource node , , is the active decision variable of the distributed resource node at time period 1, is the active decision variable of the distributed resource node at the total scheduling time period , is the active decision variable of the distributed resource node at time period , , is the active decision variable of the distributed resource node at time period for the active power output of the distributed generator in the distributed resource node is the discharge power of the energy storage in the distributed resource node at time period , is the charging power of the energy storage in the distributed resource node at time period . For a time period Distributed resource node And the distributed resource node The transaction price between them For a time period Distributed resource node And the distributed resource node The transaction volume between them For a time period Distributed resource node The transaction power with the upper-level power grid For a time period Distributed resource node The active power demand of the load in it Is the cost function of the distributed generator Is the cost function of the energy storage For a time period The electricity purchase price from the upper-level power grid For a time period The electricity selling price to the upper-level power grid Is the electricity consumption utility parameter Indicates the benefit function of user electricity consumption For the distributed resource node The first cost coefficient, second cost coefficient, and third cost coefficient of the distributed generator in it For the distributed resource node The cost coefficient of the energy storage in it For the distributed resource node The charging efficiency of the energy storage in it Is the distributed resource node The discharging efficiency of the energy storage in it

[0039] The active power regulation constraint conditions include the operation constraints of the distributed generator, the operation constraints of the energy storage, the energy transaction constraints between distributed resource nodes, and the power balance constraints of the distributed resource node. The specific forms are as follows

[0040] ; ; ; ; In the formula Is the distributed generator For the distributed resource node The maximum active power output of the distributed generator in it For a time period Distributed resource node The active power output of the distributed generator is the distributed resource node the maximum ramp efficiency is the distributed resource node the minimum ramp efficiency; is the distributed resource node and the distributed resource node the energy trading constraint between is the time period the distributed resource node and the distributed resource node the maximum trading volume between is the time period the distributed resource node and the distributed resource node the trading volume between is the set of distributed resource nodes other than the distributed resource node ; is the energy storage is the time period the distributed resource node the charging coefficient of the energy storage in is the time period the distributed resource node the discharging coefficient of the energy storage in is the time period the distributed resource node the maximum charging power of the energy storage in is the time period the distributed resource node the maximum discharging power of the energy storage; is the time period the distributed resource node the state of charge of the energy storage in is the time period the distributed resource node the state of charge of the energy storage in is the total energy storage capacity; is the distributed resource node the maximum state of charge of the energy storage in is the distributed resource node the minimum state of charge of the energy storage.

[0041] Only electricity quantity information is exchanged between distributed resource entities. In any iteration, each distributed resource entity updates its next-round operation and trading strategies through local calculation based on the electricity quantity information transmitted by the distributed resource entities, and transmits the next-round electricity quantity information to other distributed resource entities, as shown in the following formula.

[0042] 。

[0043] Among them, is the time period In the th iteration, the active power trading volume between distributed resource node and distributed resource node . is the cost function of distributed resource node . is the time period In the th iteration, the active power trading volume between distributed resource node and distributed resource node . is the time period In the th iteration, the active power trading volume between distributed resource node and distributed resource node . is the active power trading price between distributed resource node and distributed resource node in the th iteration. is the set of distributed resource nodes other than distributed resource node . is the active power penalty coefficient, represents the parameter value at which a function attains its minimum value in the domain.

[0044] After each round of iteration, the active P2P trading price is updated, and the update formula is as follows.

[0045] 。

[0046] Among them, is the active power trading price between distributed resource node and distributed resource node in the th iteration.

[0047] Judge whether this round of iteration converges according to the following convergence constraints. If it converges, terminate the iteration and obtain the active P2P regulation result of the distributed resource entity.

[0048] 。

[0049] Among them, is the total scheduling time period, is the L2 norm, is the convergence criterion, generally set to 。

[0050] Therefore, the above step 101 can be replaced by the following steps 201 to 203.

[0051] Step 201: Define that each distributed resource node is installed with a distributed generator, a photovoltaic system, energy storage, and an adjustable flexible load.

[0052] Step 202: Taking the active power of each distributed resource entity in each distributed resource node, the active load demand, the transaction power between each distributed resource node and the upper-level power grid, the transaction price between distributed resource nodes, and the transaction volume between distributed resource nodes as active decision variables, and with the minimum active operating cost of each distributed resource node as the objective, establish an active P2P regulation model for each distributed resource node.

[0053] Step 203: Taking the transaction volume between distributed resource nodes as the update variable, iteratively solve the active P2P regulation model to obtain the active power regulation results of each distributed resource entity in each distributed resource node; the active power regulation results include active power and active load demand.

[0054] In another exemplary embodiment of the present application, for a distributed resource entity, both the production and transmission of active power require the support of reactive power. More active power output means that a higher reactive power capacity is needed to achieve effective transmission, and generators at a greater distance also require more reactive power to offset the losses of transmitting active power. Therefore, each distributed resource entity needs to undertake a certain amount of reactive power output obligation to support the transmission of the active power it generates in the system. For the distributed resource entities in the distribution system, define that the reactive power obligation output amount is related to the active power output and the impact on the grid voltage. More active power output means that a higher reactive power capacity is needed to transmit electricity, and the greater the impact on the grid voltage, the more reactive power needs to be output for regulation.

[0055] 1. Reactive power obligation amount based on active power output.

[0056] Distributed generation resources need to have a certain amount of reactive power regulation ability. In addition, they usually must also meet specific power factor requirements (such as 0.95 lag to 0.95 lead) to ensure that they can absorb and provide reactive power. Therefore, the reactive power obligation output amount related to the active power output is proportional to the injected active power, and the proportional coefficient is calculated by the power factor and its calculation formula is as follows.

[0057] .

[0058] In the formula, is the time period Distributed resource node The reactive power obligation output of the distributed generator in is the time period Distributed resource node The active power output of the photovoltaic in is the time period Distributed resource node The reactive power obligation output of the photovoltaic in is the distributed generator connected to the distributed resource node is the photovoltaic connected to the distributed resource node is the time period Distributed resource node The discharge power of the energy storage in is the time period Distributed resource node The reactive power obligation output of the energy storage in is the energy storage connected to the distributed resource node is the time period Distributed resource node The required reactive power obligation, time period Distributed resource node The reactive power obligation that the node needs to inject into the system is the sum of the reactive power obligation outputs of the distributed resources connected to the node, time period Distributed resource node The value of the reactive power obligation based on the active power output is equal to .

[0059] 2. Reactive power obligation output considering the voltage influence result.

[0060] Based on the active P2P regulation result, the distributed resource node will inject or absorb the corresponding active power into the power grid, and the injection or outflow of the active power will cause changes in the node voltage. For any DER node , if you want to obtain the relationship between its active power injection and the system voltage stability level, first assume , , and based on the Newton-Raphson power flow calculation model, calculate the node voltage of the entire system before the active power injection or outflow of the distributed resource node . Form the pre-node voltage sequence with all the node voltages of any distributed resource node in the power system before injecting the active power . is the pre-node voltage sequence of the time period , is the time period ​​​The node voltage of distributed resource node 1 before injecting active power is the time period Distributed resource node The node voltage before injecting active power is the time period Distributed resource node The node voltage before injecting active power.

[0061] If there are nodes with voltage violations , form a set of pre - violation nodes from the nodes with voltage violations in the pre - node voltage sequence, denoted as . Among them, is the time period Distributed resource node The upper voltage limit is the time period Distributed resource node The lower voltage limit. Then assume , that is, after considering the effect of (i.e., injecting active power), the node voltages of the entire system are obtained. Let the post - node voltage sequence be formed by all the node voltages of any distributed resource node in the power system after injecting active power , and let the set of post - violation nodes be formed by the nodes with voltage violations in the post - node voltage sequence, denoted as . Among them, is the time period The post - node voltage sequence is the time period The node voltage of distributed resource node 1 after injecting active power is the time period Distributed resource node The node voltage after injecting active power is the time period Distributed resource node The node voltage after injecting active power.

[0062] For and , the following two cases (1) and (2) need to be considered.

[0063] (1) Compared with , there are no new nodes that do not satisfy the voltage constraint in , that is , as follows.

[0064] .

[0065] For , in other words, injecting active power will not cause voltage security problems to the system, then the quantified reactive power obligation output of this distributed resource node is 0; for , for the nodes that are out of limit both before and after injecting active power, it is necessary to evaluate to what extent the injected active power exacerbates the voltage over-limit of the over-limit voltage nodes , and calculate the reactive power obligation output of the over-limit voltage nodes according to the degree of over-limit.

[0066] .

[0067] Among them, is the reactive power obligation output considering the voltage influence result of the distributed resource node at time interval , is the reactive power obligation amount that should be output by the distributed resource node at time interval to alleviate the over-limit of the over-limit voltage node 1 (caused by the active power injection of the distributed resource node), is the reactive power obligation amount that should be output by the distributed resource node at time interval to alleviate the over-limit of the over-limit voltage node (caused by the active power injection of the distributed resource node), is the reactive power obligation amount that should be output by the distributed resource node at time interval to alleviate the over-limit of the over-limit voltage node (caused by the active power injection of the distributed resource node), is the reactive power obligation amount that should be output by the distributed resource node at time interval for the over-limit voltage node the node voltage after injecting active power by the distributed resource node, is the reactive power obligation amount that should be output by the distributed resource node at time interval for the over-limit voltage node the node voltage before injecting active power by the distributed resource node; is the over-limit voltage node set at time interval represents the voltage-reactive power sensitivity, characterizes the relationship between the voltage change of the over-limit voltage node and the change of unit reactive power of the distributed resource node . can be calculated by the following formula.

[0068] ; Among them, is the voltage, is the reactive power, is the active power, is the partial derivative matrix of the active injection power with respect to the phase angle, is the partial derivative matrix of the active injection power with respect to the voltage, is the partial derivative matrix of the reactive injection power with respect to the phase angle, is the partial derivative matrix of the reactive injection power with respect to the voltage, is the phase angle.

[0069] (2) Compared with , there are new nodes that do not meet the voltage constraint conditions in .

[0070] .

[0071] Among them, is the time period the upper voltage limit allowed for the over-limit voltage node , is the time period the lower voltage limit allowed for the over-limit voltage node .

[0072] For , this means that injecting the active power will cause new voltage security problems in the system. At this time, it is necessary to find out the new voltage over-limit nodes, and represent the set of these nodes as and . Calculate the reactive power obligation of the nodes according to the voltage over-limit situation and the voltage-reactive power sensitivity. The calculation process is as follows.

[0073] .

[0074] Among them is used to relieve the voltage over-limit problem of the over-limit voltage node caused by injecting the active power . For the distributed resource node , the reactive power obligation output that it should have should be the maximum value in , which is expressed as follows.

[0075] .

[0076] For , this means that injecting the active power will not only bring new security problems, but also may exacerbate The over-limit situation of the medium node voltage. Therefore, for nodes, the distributed resource nodes should have the calculation method of the reactive power obligation output for alleviating the over-limit caused by the injected active power as follows. The over-limit of the distributed resource node

[0077] .

[0078] For node , the distributed resource node should have the calculation method of the reactive power obligation output for alleviating the over-limit of the over-limit voltage node caused by the injected active power as follows.

[0079] .

[0080] In summary, for the distributed resource node , the reactive power obligation output it should have should be the maximum value in

[0081] .

[0082] 3. Quantification of the reactive power obligation output of the distributed resource node.

[0083] In short, the reactive power output obligation of the distributed resource node is jointly determined by the obligation based on the active power output and the obligation related to the influence of the system voltage level : .

[0084] Then the above step 102 can be replaced by the following steps 301 to 303.

[0085] Step 301: According to the active power regulation results of each distributed resource entity in each distributed resource node, use the formula to obtain the reactive power obligation based on the active power output.

[0086] Step 302: Considering the impact of the distributed resource entity on the network-wide voltage, determine the reactive power obligation output considering the voltage impact result according to the active power regulation results of each distributed resource entity in each distributed resource node.

[0087] Exemplarily, the specific implementation process of this step 302 can be steps 401 to 404.

[0088] Step 401: Form a pre-node voltage sequence with all node voltages of any distributed resource node in the power system before injecting active power (while other distributed resource nodes inject power normally), and form a pre-overlimit node set with the nodes whose node voltages exceed the limit in the pre-node voltage sequence.

[0089] Step 402: Let all node voltages of any distributed resource node in the power system after injecting active power form a post-node voltage sequence, and let the nodes whose node voltages exceed the limit in the post-node voltage sequence form a post-overlimit node set.

[0090] Step 403: When the post-overlimit node set is the same as the pre-overlimit node set: If both the post-overlimit node set and the pre-overlimit node set are empty sets, the reactive power obligation output of any distributed resource node considering the voltage influence result is zero; if both the post-overlimit node set and the pre-overlimit node set are not empty sets, then use the formula , to calculate the reactive power obligation output of any distributed resource node considering the voltage influence result.

[0091] Step 404: When the post-overlimit node set is different from the pre-overlimit node set: If the pre-overlimit node set is an empty set, then use the formula , to calculate the reactive power obligation output of any distributed resource node considering the voltage influence result; if the pre-overlimit node set is not an empty set, then use the formula , to calculate the reactive power obligation output of any distributed resource node considering the voltage influence result.

[0092] Step 303: Determine the reactive power output obligation of each distributed resource entity among the distributed resource nodes as the maximum value between the reactive power obligation amount based on the active power output and the reactive power obligation output considering the voltage influence result.

[0093] In another exemplary embodiment of the present application, considering that in the reactive P2P regulation scenario, distributed resource entities may overproduce or underproduce reactive power to ensure cost minimization or revenue maximization during the regulation process, which may lead to further voltage problems. Therefore, it is necessary to set an action threshold for distributed reactive power regulation to ensure that the subsequent reactive power regulation scale after P2P regulation is neither too large nor too small. An overly large scale may exacerbate the voltage problems in the distribution network, while an overly small scale cannot ensure that the distribution network obtains sufficient reactive power compensation. Therefore, first determine the reactive power regulation range of distributed resource entities based on the optimal power flow model, that is, obtain the thresholds for reactive power regulation of each distributed resource through the optimal power flow model. The optimal power flow model takes minimizing network losses and voltage overlimits as the objective function, and the specific modeling is as follows.

[0094] ; ; ; ; ; ; ; ; .

[0095] In the formula, is the first reactive power decision variable of the distributed resource node , , is the reactive power decision variable of the distributed resource node in time period 1, is the total scheduling time period for the distributed resource node of the first reactive power decision variable, is the time period for the distributed resource node of the first reactive power decision variable, , is the time period for the distributed resource node of the reactive power regulation threshold of the distributed generator, is the time period for the distributed resource node of the reactive power regulation threshold of the photovoltaic, is the time period for the distributed resource node of the reactive power regulation threshold of the energy storage, is the time period for the distributed resource node of the reactive power regulation threshold, is the time period of the optimal active power flow, is the time period of the optimal reactive power flow; is the number of distributed resource nodes, is the line resistance of the distributed resource node , and are respectively the active power injection and reactive power injection of the distributed resource node in the time period , is the base voltage, is the penalty coefficient, is the time period for the distributed resource node The voltage is the maximum value of the node voltage, and is the time period Optimal active power flow of the line between distributed resource node and distributed resource node ; is the time period Optimal active power flow of the line between distributed resource node and distributed resource node ; is the line resistance between distributed resource node and distributed resource node ; is the square of the line current between distributed resource node and distributed resource node ; is the time period Optimal reactive power flow is the time period Optimal reactive power flow of the line between distributed resource node and distributed resource node ; is the line reactance between distributed resource node and distributed resource node ; is the time period The square of the voltage of distributed resource node ; is the time period The square of the voltage of distributed resource node ; is the set of child nodes of distributed resource node ; is the time period The minimum value of the square of the voltage of distributed resource node ; is the time period The maximum value of the square of the voltage of distributed resource node ; represents the optimized reactive power output of the distributed generator in the time period of distributed resource node ; represents the optimized reactive power output of the PV in the time period of distributed resource node ; represents the optimized reactive power output of the energy storage in the time period of distributed resource node ; is the capacity of the distributed generator unit in the distributed resource node ; is the capacity of the PV inverter in the distributed resource node ; is the capacity of the energy storage inverter in the distributed resource node .

[0096] In another exemplary embodiment of the present application, based on the active power regulation result, reactive power obligation output, and reactive power regulation range of the distributed resource entity, a reactive power P2P regulation model of the distributed resource entity is established, and a reactive power output strategy for the distributed resource entity to participate in voltage regulation is obtained. According to the reactive power obligation power generation, distributed resources with reactive power capacity exceeding the obligation demand can obtain rewards, while distributed resource entities that cannot generate sufficient reactive power need to pay for the insufficient part. The distributed resource node can be regulated through an optimization strategy in reactive power P2P regulation. The specific reactive power regulation objective function is modeled as follows.

[0097] ; ; .

[0098] In the formula, is the reactive power regulation cost function of the distributed resource node ; is the second reactive power decision variable of the distributed resource node ; , is the second reactive power decision variable of the distributed resource node at time period 1; is the second reactive power decision variable of the distributed resource node at the total scheduling time period ; is the second reactive power decision variable of the distributed resource node at time period ; , represents the optimized reactive power output of the distributed generator in the distributed resource node at time period ; represents the optimized reactive power output of the PV in the distributed resource node at time period ; represents the optimized reactive power output of the energy storage in the distributed resource node at time period ; is the time period Distributed resource node Optimize the reactive power load in For the time period Distributed resource node And the distributed resource node The reactive power trading price between For the time period Distributed resource node And the distributed resource node The reactive power trading capacity between For the distributed resource node The reactive power regulation cost function of the distributed generator in For the distributed resource node The reactive power regulation cost function of the energy storage in For the distributed resource node The reactive power regulation cost function of the photovoltaic in For the distributed resource node The set of distributed resource nodes other than For the distributed resource node The set of distributed resource nodes other than For the coefficient of the first constant term For the coefficient of the first linear term For the coefficient of the first quadratic term For the reactive power cost function of the distributed resource For the time period Distributed resource node The reactive power output of For the time period Distributed resource node The reactive power cost caused by the increase in inverter power loss in For the time period Distributed resource node The inverter life attenuation cost in For the time period The cost coefficient of For the time period Distributed resource node The additional power loss in For the coefficient of the second constant term For the coefficient of the second linear term For the coefficient of the second quadratic term For the time period Distributed resource node The active power output of For the time period Distributed resource node The inverter capacity in is the coefficient of the third constant term, is the coefficient of the third linear term, is the coefficient of the third quadratic term, is the coefficient of the cubic term.

[0099] The reactive power regulation constraint conditions are as follows.

[0100] ; .

[0101] In the formula, is the time period Distributed resource node The reactive power output obligation amount of, is the time period Distributed resource node And distributed resource node The reactive power trading volume between, is the time period Distributed resource node The reactive power regulation threshold of the distributed generator in, is the time period Distributed resource node The reactive power regulation threshold of the photovoltaic in, is the time period Distributed resource node The reactive power regulation threshold of the energy storage in, is the time period Distributed resource node The reactive power regulation threshold in.

[0102] In another exemplary embodiment of the present application, only reactive power quantity information is exchanged between distributed resource entities , in any iteration number, each distributed resource entity updates its next-round operation and trading strategy through local calculation based on the decision information transmitted by the distributed resource entity, and transmits the trading information to other distributed resource entities, as shown in the following formula.

[0103] .

[0104] Among them, is the time period In the th iteration, the reactive power trading volume between distributed resource node and distributed resource node , is the reactive power regulation cost function of distributed resource node , is the time period In the The reactive power trading volume between distributed resource nodes in the nth iteration and the distributed resource nodes is for time period In the nth iteration, the reactive power trading volume between distributed resource nodes and the distributed resource nodes is The reactive power trading price between the distributed resource nodes in the nth iteration and the distributed resource nodes is The reactive power penalty coefficient is is the above decision-making information, is the above trading information.

[0105] After each round of iteration, update the reactive power P2P regulation price, and the update formula is as follows.

[0106] .

[0107] Judge whether this round of iteration converges according to the following convergence constraints. If it converges, terminate the iteration and obtain the reactive power P2P regulation result of the distributed resource entity.

[0108] .

[0109] It can be seen that the above step 105 can be: according to the reactive power output obligation amount and reactive power regulation threshold of each distributed resource entity in each distributed resource node, using the reactive power trading power between distributed resource nodes as the update variable, iteratively solve the reactive power P2P regulation model, and obtain the reactive power P2P regulation result of each distributed resource entity in each distributed resource node.

[0110] The reactive power P2P regulation result includes: the optimized reactive power output of the distributed generator in each distributed resource node, the optimized reactive power output of the photovoltaic in each distributed resource node, the optimized reactive power output of the energy storage in each distributed resource node, the optimized reactive power load in each distributed resource node, the reactive power trading price between the connected distributed resource nodes, and the reactive power trading capacity between the connected distributed resource nodes.

[0111] Figure 2 is the framework diagram of a method for coordinated active and reactive P2P regulation of distributed resource entities in this application. As Figure 2As shown in the figure, first, a multi-distributed resource entity active P2P regulation model is established to obtain the regulation results of active P2P transactions without considering network constraints. Secondly, considering that reactive power support is a necessary condition for the generation and transmission of active power, a method for quantifying the reactive power obligation output of distributed resource entities is proposed. This obligation output is not only related to the active power output of distributed resource nodes but also related to the impact of distributed resource entities on the overall network voltage. Then, a reactive P2P regulation model for distributed resource entities is established, with the minimum operating cost of distributed resource entities as the objective function for modeling, to promote the efficient utilization of reactive power resources and ensure voltage security. In the case of deregulated P2P reactive power regulation, distributed resource entities may produce excessive or insufficient reactive electrical energy to maximize their profits, leading to potential voltage problems. Therefore, an optimal power flow model with the minimum network loss and voltage deviation as the objective is established to obtain the threshold of the reactive power regulation amount of distributed resource entities.

[0112] The key points of this application are as follows.

[0113] 1. A P2P distributed framework through distributed active and reactive power coordination is proposed to implement a strategy for improving the photovoltaic carrying capacity of the distribution network. On the basis of ensuring the interests of multiple distributed resource entities, active P2P regulation is used to promote the consumption of photovoltaic power, and at the same time, reactive P2P regulation is used to ensure the voltage stability of the distribution network, effectively improving the carrying capacity of the distribution network.

[0114] 2. A method for quantifying the reactive power obligation output of distributed resource nodes is proposed to clarify the reactive power output responsibility that distributed resources should bear when participating in active power transactions. The reactive power obligation of distributed resources is quantified from two aspects: active power output and voltage influence results. If the reactive power generated by distributed resource nodes exceeds the specified obligation, they can obtain compensation; if their reactive power capacity cannot meet the minimum demand, they need to pay the corresponding amount.

[0115] 3. A reactive power regulation method based on a distributed P2P framework is proposed. An optimization model is established with the minimum operating cost of each distributed resource entity as the objective function to guide distributed resource entities to actively participate in the voltage regulation of the distribution network. In addition, considering that in the deregulated P2P reactive power regulation scenario, distributed resource entities may produce excessive or insufficient reactive electrical energy to maximize their profits, leading to potential voltage problems, an optimal power flow model with the minimum network loss and voltage deviation as the objective is established to obtain the regulation threshold of the reactive power regulation amount of distributed resource entities to ensure that the optimized reactive P2P regulation scale is neither too large nor too small.

[0116] On the basis of safeguarding the interests of multiple parties of distributed resources, this application promotes the smooth implementation of key links such as photovoltaic accommodation and energy storage peak-valley arbitrage through active P2P regulation. At the same time, in the scheme considering the participation of distributed resources in reactive voltage regulation, the voltage regulation responsibilities of distributed resource entities are determined by defining the priority of reactive obligation output, and a reactive P2P optimization model of distributed resource entities is established based on this obligation. The excess or deficiency of the reactive power generated by distributed resource nodes compared with the specified obligation is traded in the reactive P2P optimization regulation, guiding distributed resources to participate in reactive voltage regulation, ensuring the safe operation of the distribution network, and improving the photovoltaic carrying capacity of the distribution network.

[0117] Based on the same inventive concept, an embodiment of this application also provides a distributed resource entity active and reactive collaborative P2P regulation device for implementing the above-mentioned distributed resource entity active and reactive collaborative P2P regulation method. The implementation solutions provided by this device to solve problems are similar to the implementation solutions described in the above method. Therefore, the specific limitations in one or more embodiments of the distributed resource entity active and reactive collaborative P2P regulation device provided below can refer to the limitations on the distributed resource entity active and reactive collaborative P2P regulation method in the above text, and will not be repeated here.

[0118] In an exemplary embodiment, as Figure 3 shown, a distributed resource entity active and reactive collaborative P2P regulation device is provided, including: an active regulation module, a reactive output obligation determination module, a reactive regulation threshold solution module, a reactive P2P regulation model establishment module, and a reactive P2P regulation solution module.

[0119] The active regulation module is used to perform active power P2P optimization scheduling with the goal of minimizing the active operation cost of each distributed resource node, and obtain the active power regulation result of each distributed resource entity in each distributed resource node; multiple distributed resource entities are installed in each distributed resource node.

[0120] The reactive output obligation determination module is used to determine the reactive power output obligation of each distributed resource entity in each distributed resource node according to the active power regulation result of each distributed resource entity in each distributed resource node, considering the impact of the distributed resource entity on the network-wide voltage.

[0121] The reactive regulation threshold solution module is used to solve the optimal power flow model with the goal of minimizing the sum of distribution network power loss and voltage violation according to the active power regulation result of each distributed resource entity in each distributed resource node, and obtain the reactive regulation threshold of each distributed resource entity in each distributed resource node.

[0122] The reactive power P2P regulation model establishment module is used to obtain rewards based on the part where the reactive power capacity exceeds the reactive power output obligation, and pay for the part where the reactive power capacity is less than the reactive power output obligation. With the goal of minimizing the reactive power operation cost of each distributed resource node and the constraint that the reactive power output of each distributed resource entity is less than or equal to its respective reactive power regulation threshold, the reactive power P2P regulation model of each distributed resource node is established; the reactive power operation cost includes the inverter loss cost.

[0123] The reactive power P2P regulation solution module is used to solve the reactive power P2P regulation model of each distributed resource node according to the reactive power output obligation and the reactive power regulation threshold of each distributed resource entity in each distributed resource node, and obtain the reactive power P2P regulation result of each distributed resource entity in each distributed resource node.

[0124] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered to be within the scope described in this specification.

[0125] In this article, specific examples are used to elaborate on the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, based on the idea of this application, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be construed as a limitation to this application.

Claims

1. A distributed resource entity active and reactive power collaborative P2P regulation method, characterized in that, Including: Taking the minimum active operating cost of each distributed resource node as the goal, performing active power P2P optimal scheduling, and obtaining the active power regulation results of each distributed resource entity in each distributed resource node; multiple distributed resource entities are installed in each distributed resource node; According to the active power regulation results of each distributed resource entity in each distributed resource node, considering the impact of the distributed resource entity on the whole network voltage, determining the reactive power output obligation amount of each distributed resource entity in each distributed resource node; According to the active power regulation results of each distributed resource entity in each distributed resource node, taking the minimization of the sum of the distribution network power loss and voltage violation as the goal, solving the optimal power flow model, and obtaining the reactive power regulation threshold of each distributed resource entity in each distributed resource node; Based on the principle of obtaining rewards for the part where the reactive power capacity exceeds the reactive power output obligation amount and paying for the part where the reactive power capacity is less than the reactive power output obligation amount, taking the minimum reactive operating cost of each distributed resource node as the goal and the reactive power output of each distributed resource entity being less than or equal to its respective reactive power regulation threshold as the constraint, establishing the reactive P2P regulation model of each distributed resource node; the reactive operating cost includes the inverter loss cost; According to the reactive power output obligation amount and reactive power regulation threshold of each distributed resource entity in each distributed resource node, solving the reactive P2P regulation model of each distributed resource node, and obtaining the reactive P2P regulation results of each distributed resource entity in each distributed resource node.

2. The distributed resource entity active and reactive power collaborative P2P regulation method according to claim 1, characterized in that, Taking the minimum active operating cost of each distributed resource node as the goal, performing active power P2P optimal scheduling, and obtaining the active power regulation results of each distributed resource entity in each distributed resource node, specifically including: Defining that each distributed resource node is equipped with a distributed generator, photovoltaic, energy storage, and adjustable flexible load; Taking the active power of each distributed resource entity in each distributed resource node, the active load demand, the transaction power between each distributed resource node and the upper-level power grid, the transaction price between distributed resource nodes, and the transaction volume between distributed resource nodes as active decision variables, and taking the minimum active operating cost of each distributed resource node as the goal, establishing the active P2P regulation model of each distributed resource node; Taking the transaction volume between distributed resource nodes as the update variable, iteratively solving the active P2P regulation model, and obtaining the active power regulation results of each distributed resource entity in each distributed resource node; the active power regulation results include active power and active load demand; in each iteration, each distributed resource entity uses the formula ， Update the trading volume for their respective next iterations and pass it to other distributed resource entities; based on the trading volume of each distributed resource entity for its respective next iteration, determine whether each iteration meets , if not, perform the next iteration, and if so, terminate the iteration; Among them, is the time period In the th iteration, the active power trading volume between distributed resource node and distributed resource node is the cost function of distributed resource node . is the time period In the th iteration, the active power trading volume between distributed resource node and distributed resource node is the time period In the th iteration, the active power trading volume between distributed resource node and distributed resource node is the active power trading price between distributed resource node and distributed resource node in the th iteration. is the set of distributed resource nodes other than distributed resource node is the active power penalty parameter, is the number of distributed resource nodes, represents the parameter value at which a function obtains the minimum value in the domain; is the total scheduling time period, is the L2 norm, is the convergence criterion.

3. The distributed resource entity active and reactive power collaborative P2P regulation method according to claim 2, characterized in that The active P2P regulation model includes: an active regulation objective function and active regulation constraint conditions; The active regulation objective function is: ； ； ； Wherein, is the active operating cost of the distributed resource node ; is the active decision variable of the distributed resource node , , is the active decision variable of the distributed resource node at time period 1, is the active decision variable of the distributed resource node during the total scheduling time period ; is the active decision variable of the distributed resource node at time period , , is the active power output of the distributed generator in the distributed resource node at time period ; is the discharging power of the energy storage in the distributed resource node at time period ; is the charging power of the energy storage in the distributed resource node at time period ; is the trading price between the distributed resource node and the distributed resource node at time period ; is the trading volume between the distributed resource node and the distributed resource node at time period ; is the trading power between the distributed resource node and the upper-level power grid at time period ; is the active power demand of the load in the distributed resource node at time period ; is the cost function of the distributed generator, is the cost function of the energy storage, is the electricity purchase price from the upper-level power grid at time period , is the electricity selling price to the upper-level power grid at time period , is the electricity consumption utility parameter, indicating the benefit function of user electricity consumption; are the first cost coefficient, the second cost coefficient, and the third cost coefficient of the distributed generator in the distributed resource node , is the distributed resource node The cost coefficient of the energy storage in the distributed resource node The charging efficiency of the energy storage in the distributed resource node The discharging efficiency of the energy storage; The active regulation constraint conditions are: ； ； ； ； Wherein, is a distributed generator, is a distributed resource node The maximum active power output of the distributed generator in is the time period Distributed resource node The active power output of the distributed generator in is a distributed resource node The maximum ramp efficiency of is a distributed resource node The minimum ramp efficiency of is a distributed resource node and distributed resource node The energy trading constraint between is the time period Distributed resource node and distributed resource node The maximum trading volume between is the time period Distributed resource node and distributed resource node The trading volume between is the set of distributed resource nodes other than distributed resource node is energy storage, is the time period Distributed resource node The charging coefficient of the energy storage in is the time period Distributed resource node The discharging coefficient of the energy storage in is the time period Distributed resource node The maximum charging power of the energy storage in is the time period Distributed resource node The maximum discharging power of the energy storage in is the time period Distributed resource node The state of charge of the energy storage in is the time period Distributed resource node The state of charge of the energy storage in is the total energy storage capacity; is a distributed resource node The maximum state of charge of the energy storage in is a distributed resource node The minimum state of charge of the energy storage in 4. The distributed resource entity active and reactive power collaborative P2P regulation method according to claim 1, characterized in that According to the active power regulation results of each distributed resource entity in each distributed resource node, considering the impact of the distributed resource entity on the whole network voltage, determining the reactive power output obligation amount of each distributed resource entity in each distributed resource node, specifically including: According to the active power regulation results of each distributed resource entity in each distributed resource node, use the formula , to obtain the reactive power obligation based on the active power output; in the formula, is the proportionality coefficient, is the power factor, is the time period Distributed resource node The active power output of the distributed generator in is the time period Distributed resource node The reactive power obligation output of the distributed generator in is the time period Distributed resource node The active power output of the photovoltaic in is the time period Distributed resource node The reactive power obligation output of the photovoltaic in is the distributed generator connected to the distributed resource node , is the photovoltaic connected to the distributed resource node , is the time period Distributed resource node The charging power of the energy storage in is the time period Distributed resource node The charging coefficient of the energy storage in is the time period Distributed resource node The discharging power of the energy storage in is the time period Distributed resource node The discharging coefficient of the energy storage in is the time period Distributed resource node The reactive power obligation output of the energy storage in is the energy storage connected to the distributed resource node , is the time period Distributed resource node The required reactive power obligation, the time period Distributed resource node The reactive power obligation that the node needs to inject into the system is the sum of the reactive power obligation outputs of the distributed resources connected to the node. The time period Distributed resource node The value of the reactive power obligation based on the active power output is equal to ; Considering the impact of distributed resource entities on the voltage of the entire network, based on the active power regulation results of each distributed resource entity in each distributed resource node, determine the reactive power obligation output considering the voltage impact result; Determine the reactive power output obligation of each distributed resource entity in each distributed resource node as the maximum value between the reactive power obligation based on the active power output and the reactive power obligation output considering the voltage impact result.

5. The distributed resource entity active and reactive power collaborative P2P control method according to claim 4, characterized in that Considering the impact of distributed resource entities on the voltage of the entire network, based on the active power regulation results of each distributed resource entity in each distributed resource node, determine the reactive power obligation output considering the voltage impact result, specifically including: Form the pre-node voltage sequence of all node voltages before injecting active power at any distributed resource node in the power system, and form the pre-overlimit node set for the nodes with over-limited node voltages in the pre-node voltage sequence; Let the post-node voltage sequence of all node voltages after injecting active power at any distributed resource node in the power system, and let the post-overlimit node set be formed by the nodes with over-limited node voltages in the post-node voltage sequence; When the set of post-overlimit nodes is the same as the set of pre-overlimit nodes: If both the set of post-overlimit nodes and the set of pre-overlimit nodes are empty sets, the reactive power obligation output of any distributed resource node considering the voltage influence result is zero; if both the set of post-overlimit nodes and the set of pre-overlimit nodes are not empty sets, then use the formula to calculate the reactive power obligation output of any distributed resource node considering the voltage influence result; in the formula, is the time period The reactive power obligation output of the distributed resource node considering the voltage influence result, is the time period The distributed resource node is the reactive power obligation amount that should be output to relieve the overlimit of the overlimit voltage node 1, is the time period The distributed resource node is to relieve the overlimit voltage node The reactive power obligation amount that should be output for the overlimit, is the time period The distributed resource node is to relieve the overlimit voltage node The reactive power obligation amount that should be output for the overlimit, is the time period The overlimit voltage node at the distributed resource node The node voltage after injecting active power, is the time period The overlimit voltage node at the distributed resource node The node voltage before injecting active power; represents the voltage-reactive power sensitivity, characterizes the overlimit voltage node The relationship between the voltage change and the unit reactive power change of the distributed resource node , , is the voltage, is the reactive power, is the active power, is the partial derivative matrix of the active injection power with respect to the phase angle, is the partial derivative matrix of the active injection power with respect to the voltage, is the partial derivative matrix of the reactive injection power with respect to the phase angle, is the partial derivative matrix of the reactive injection power with respect to the voltage, is the phase angle; is the time period The set of overlimit voltage nodes; When the post-overlimit node set is different from the pre-overlimit node set: If the pre-overlimit node set is an empty set, use the formula to calculate the reactive power obligation output of any distributed resource node considering the voltage influence result; if the pre-overlimit node set is not an empty set, use the formula to calculate the reactive power obligation output of any distributed resource node considering the voltage influence result; in the formula, is the upper limit of the allowable voltage of the overlimit voltage node in the time period , is the pre-overlimit node set in the time period , is the post-overlimit node set in the time period .

6. The distributed resource entity active and reactive power collaborative P2P regulation method according to claim 1, wherein The optimal power flow model is: ； Wherein, is the first reactive power decision variable of the distributed resource node , , is the reactive power decision variable of the distributed resource node in time period 1 is the total scheduling time period The first reactive power decision variable of the distributed resource node , is the time period The first reactive power decision variable of the distributed resource node , , is the time period The reactive power regulation threshold of the distributed generator in the distributed resource node , is the time period The reactive power regulation threshold of the photovoltaic in the distributed resource node , is the time period The reactive power regulation threshold of the energy storage in the distributed resource node , is the time period The reactive power regulation threshold in the distributed resource node , is the time period Optimal active power flow is the time period Optimal reactive power flow; is the number of distributed resource nodes is the line resistance of the distributed resource node , and are the active power injection and reactive power injection of the distributed resource node in time period respectively is the reference voltage is the penalty coefficient is the time period The voltage of the distributed resource node , is the maximum node voltage is the minimum node voltage; is the time period The optimal active power flow of the line between the distributed resource node and the distributed resource node , is the time period The optimal active power flow of the line between the distributed resource node and the distributed resource node respectively is the line resistance between and the distributed resource nodes ; is the square of the line current between and the distributed resource nodes ; is the time period optimal reactive power flow, is the time period the optimal reactive power flow of the line between and the distributed resource nodes ; is the line reactance between and the distributed resource nodes ; is the time period the square of the voltage of the distributed resource node ; is the time period the square of the voltage of the distributed resource node ; is the set of child nodes of the distributed resource node ; is the time period the minimum value of the square of the voltage of the distributed resource node ; is the time period the maximum value of the square of the voltage of the distributed resource node ; represents the optimized reactive power output of the distributed generator in the time period of the distributed resource node ; represents the optimized reactive power output of the PV in the time period of the distributed resource node ; represents the optimized reactive power output of the energy storage in the time period of the distributed resource node ; is the capacity of the distributed generator unit in the distributed resource node ; is the time period the active power output of the distributed generator in the distributed resource node ; is the capacity of the PV inverter in the distributed resource node ; is the time period the active power output of the PV in the distributed resource node ; is the capacity of the energy storage inverter in the distributed resource node is the time period is the discharge power of the energy storage in the distributed resource node is the time period is the discharge coefficient of the energy storage in the distributed resource node is the time period is the charging power of the energy storage in the distributed resource node is the time period is the charging coefficient of the energy storage in the distributed resource node is the time period is the charging power of the energy storage in the distributed resource node is the time period is the charging coefficient of the energy storage in the distributed resource node in the distributed resource node 7. The active and reactive power coordinated P2P control method for distributed resource entities according to claim 1, wherein According to the reactive power output obligation and reactive power regulation threshold of each distributed resource entity in each distributed resource node, solve the reactive power P2P regulation model of each distributed resource node to obtain the reactive power P2P regulation results of each distributed resource entity in each distributed resource node, specifically including: According to the reactive power output obligation and reactive power regulation threshold of each distributed resource entity in each distributed resource node, with the reactive power transaction electricity between distributed resource nodes as the update variable, iteratively solve the reactive power P2P regulation model to obtain the reactive power P2P regulation results of each distributed resource entity in each distributed resource node; in each iteration, each distributed resource entity uses the formula ， Update the reactive power trading power for their respective next iterations and pass it to other distributed resource entities; Based on the reactive power trading power for each distributed resource entity's respective next iteration, determine whether each iteration meets , if not, perform the next iteration, and if so, terminate the iteration; wherein, is a time period in the th iteration, the reactive power trading volume between distributed resource nodes and distributed resource node ; is the reactive power regulation cost function of distributed resource node ; is a time period in the th iteration, the reactive power trading volume between distributed resource nodes and distributed resource node ; is a time period in the th iteration, the reactive power trading volume between distributed resource nodes and distributed resource node ; is the reactive power trading price between distributed resource nodes and distributed resource node in the th iteration; is the set of distributed resource nodes other than distributed resource node ; is the reactive power penalty coefficient; is the number of distributed resource nodes; represents the parameter value at which a function attains the minimum value in its domain; is the total scheduling time period; is the L2 norm; is the convergence criterion.

8. The distributed resource entity active and reactive power collaborative P2P control method according to claim 1, characterized in that The reactive power P2P regulation model includes: a reactive power regulation objective function and reactive power regulation constraint conditions; The reactive power regulation objective function is: ； ； ； ； ； ； Wherein, is the reactive power regulation cost function of the distributed resource node , is the total scheduling period, is the second reactive power decision variable of the distributed resource node , , is the second reactive power decision variable of the distributed resource node at time period 1, is the second reactive power decision variable of the distributed resource node at the total scheduling period , is the time period the second reactive power decision variable of the distributed resource node , , represents the optimized reactive power output of the distributed generator in the distributed resource node at time period , represents the optimized reactive power output of the photovoltaic in the distributed resource node at time period , represents the optimized reactive power output of the energy storage in the distributed resource node at time period , is the optimized reactive power load in the distributed resource node at time period , is the reactive power trading price between the distributed resource node and the distributed resource node at time period , is the reactive power trading capacity between the distributed resource node and the distributed resource node at time period ; is the reactive power regulation cost function of the distributed generator in the distributed resource node , is the reactive power regulation cost function of the energy storage in the distributed resource node , is the reactive power regulation cost function of the photovoltaic in the distributed resource node , is the set of distributed resource nodes other than the distributed resource node , is the set of distributed resource nodes other than the distributed resource node ; is the coefficient of the first constant term, is the coefficient of the first linear term, is the coefficient of the first quadratic term; is the reactive power cost function of the distributed resource, is the time period distributed resource node 's reactive power output, is the time period distributed resource node the reactive power cost caused by the increase in inverter power loss in, is the time period distributed resource node the inverter life attenuation cost in, is the time period 's cost coefficient, is the time period distributed resource node the additional power loss in, is the coefficient of the second constant term, is the coefficient of the second linear term, is the coefficient of the second quadratic term, is the time period distributed resource node 's active power output, is the time period distributed resource node the inverter capacity in, is the coefficient of the third constant term, is the coefficient of the third linear term, is the coefficient of the third quadratic term, is the coefficient of the cubic term; The reactive power regulation constraint conditions are: ； ； Wherein, is the time period Distributed resource node of the reactive power output obligation volume, is the time period Distributed resource node and distributed resource node of the reactive power trading volume between them, is the time period Distributed resource node of the reactive power regulation threshold of the distributed generator therein, is the time period Distributed resource node of the reactive power regulation threshold of the photovoltaic therein, is the time period Distributed resource node of the reactive power regulation threshold of the energy storage therein, is the time period Distributed resource node of the reactive power regulation threshold therein.

9. The distributed resource main body active and reactive power collaborative P2P regulation method according to claim 8, wherein, The reactive power P2P regulation results include: the optimized reactive power output of distributed generators in each distributed resource node, the optimized reactive power output of photovoltaics in each distributed resource node, the optimized reactive power output of energy storage in each distributed resource node, the optimized reactive power load in each distributed resource node, the reactive power transaction price between connected distributed resource nodes, and the reactive power transaction capacity between connected distributed resource nodes.

10. A distributed resource main body active and reactive power collaborative P2P control device, characterized in that, Include: An active power regulation module, which aims to minimize the active power operation cost of each distributed resource node, performs active power P2P optimal scheduling, and obtains the active power regulation results of each distributed resource entity in each distributed resource node; multiple distributed resource entities are installed in each distributed resource node; A reactive power output obligation determination module, which is used to determine the reactive power output obligation of each distributed resource entity in each distributed resource node according to the active power regulation results of each distributed resource entity in each distributed resource node, considering the impact of distributed resource entities on the voltage of the entire network; A reactive power regulation threshold solving module, which is used to solve the optimal power flow model with the goal of minimizing the sum of the distribution network power loss and voltage violation according to the active power regulation results of each distributed resource entity in each distributed resource node, so as to obtain the reactive power regulation threshold of each distributed resource entity in each distributed resource node; A reactive power P2P regulation model establishing module, which is used to establish the reactive power P2P regulation model of each distributed resource node with the goal of minimizing the reactive power operation cost of each distributed resource node based on the principle that the part of the reactive power capacity exceeding the reactive power output obligation is rewarded and the part of the reactive power capacity less than the reactive power output obligation is paid, and the constraint that the reactive power output of each distributed resource entity is less than or equal to its respective reactive power regulation threshold; the reactive power operation cost includes the inverter loss cost; A reactive power P2P regulation solving module, which is used to solve the reactive power P2P regulation model of each distributed resource node according to the reactive power output obligation and reactive power regulation threshold of each distributed resource entity in each distributed resource node, so as to obtain the reactive power P2P regulation result of each distributed resource entity in each distributed resource node.

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