Virtual power plant distributed regulation and control method and system based on communication review

Abstract

A virtual power plant distributed regulation and control method based on communication review is characterized by comprising the following steps: step 1, generating a distributed regulation and control model of node power in a virtual power plant and between virtual power plants by using a direct current power flow constraint problem; 2, solving the distributed regulation and control model based on an alternating direction multiplier method, and introducing a local variable of the virtual power plant, a local intermediate variable of the virtual power plant and a global variable of the virtual power plant; 3, presetting a communication review mechanism, updating the variables in the iteration process, and judging whether the iteration meets the communication requirement or not according to the communication review mechanism; and step 4, performing communication on the variables meeting the communication requirements, and performing distributed regulation and control of the virtual power plant based on a communication result. According to the method, the operation cost of virtual power plant communication scheduling is minimum, and the economic benefit is maximized.

Description

Technical Field

[0001] The present invention relates to a field, and more specifically, to a distributed control method and system for a virtual power plant based on communication review. Background Art

[0003] Distributed Energy Resources (DER) are gradually becoming an important alternative to meet the growing demand for electricity. In the era of smart grid technology, Virtual Power Plant (VPP) is a modern energy management paradigm that integrates various DERs into a unified and coordinated system. VPP can be understood as a distributed, multi-type energy aggregation management and operation mode. Through advanced information and communication technology and monitoring technology, massive distributed generation, demand side and energy storage resources are aggregated and uniformly coordinated and controlled.

[0004] Optimal power flow calculations are key to ensuring safe, economical, and efficient operation of the power grid. By performing optimal power flow (OPF) calculations, system operators can determine economical and effective branch power allocation schemes while considering operational constraints such as generator capacity and transmission line limitations. Until today, most optimization and control algorithms in power systems, such as OPF, are calculated in a centralized manner. However, with the increasing popularity of distributed energy resources, the feasibility of the centralized computing paradigm is threatened, including privacy threats, computational complexity threats, storage threats, etc.

[0005] The core of the concept of virtual power plant can be summarized as "communication" and "aggregation", but the current OPF algorithm does not take into account the problem of communication cost. Therefore, the current distributed control algorithm has the following problems: communication and information exchange are carried out after each iteration update in the virtual power plant, which increases the communication cost. In particular, as the number of communication nodes and the iteration update coefficient increase, the communication cost will be too high, which directly affects the distributed control to achieve the optimal goal.

[0006] Therefore, it is of great practical significance to improve communication efficiency, reduce communication costs, and achieve efficient communication in the distributed control algorithm of virtual power plants. However, there is no optimization protocol in the prior art that can select high communication efficiency and low communication cost according to whether the distributed control process is effective.

[0007] In view of the above problems, a new distributed control method and system for virtual power plants is urgently needed. Summary of the invention

[0008] In order to solve the deficiencies in the prior art, the present invention provides a distributed control method and system for a virtual power plant based on communication review, which utilizes the DC optimal power flow to obtain the control mode, sets the communication parameters with the parameters of the alternating direction multiplier method to assist in communication review, and solves the optimal control result.

[0009] The present invention adopts the following technical solution.

[0010] The first aspect of the present invention relates to a distributed control method of a virtual power plant based on communication review, the method comprising the following steps: step 1, using a DC power flow constraint problem to generate a distributed control model of node power within a virtual power plant and between virtual power plants; step 2, solving the distributed control model based on an alternating direction multiplier method, and introducing local variables of the virtual power plant, local intermediate variables of the virtual power plant, and global variables; step 3, presetting a communication review mechanism, updating variables during the iteration process, and judging whether this iteration meets the communication requirements according to the communication review mechanism; step 4, implementing communication for variables that meet the communication requirements, and implementing distributed control of the virtual power plant based on the communication results.

[0011] Preferably, a distributed control model of node power within a virtual power plant and between virtual power plants is generated using the DC power flow constraint problem, including: taking the distributed motor grid-connected bus as a node to obtain the distributed control model topology of the virtual power plant; and generating a distributed control model with the minimum sum of node scheduling costs as the model's goal and the DC power flow constraint as the model's constraint.

[0012] Preferably, the goal of the model is to minimize the sum of node scheduling costs, including:

[0013] The i-th node is in state x i The scheduling cost under is:

[0014]

[0015] In the formula, the state x i Including node power and phase angle,

[0016] S B is the node set in the distributed control model,

[0017] S DG is the set of all distributed motor combinations connected to a node in the distributed control model,

[0018] S T is the set of time periods to be scheduled,

[0019] f i (·) is the active power of the ith node The cost of

[0020] is the available power of the ith node in time period t.

[0021] Preferably, the DC power flow constraints are constraints of the model, including: DC power flow constraints include power balance constraints of internal nodes of the virtual power plant, capacity constraints of transmission lines, reference bus constraints, capacity constraints of distributed motors, distributed motor ramp-up constraints, and distributed motor ramp-down constraints.

[0022] Preferably, the power balance constraint of the nodes inside the virtual power plant is:

[0023]

[0024] In the formula, is the load of the ith node,

[0025] l is S B Different from other nodes in i,

[0026] S B is the set of all nodes in the model,

[0027] B il is the equivalent admittance vector between nodes il in the admittance matrix pre-calculated according to the distributed control model topology,

[0028] is the phase angle of the lth node in time period t;

[0029] The capacity constraint of the transmission line is:

[0030]

[0031] In the formula, X il is the equivalent reactance vector between the grid-connected nodes ij corresponding to the virtual power plant pre-calculated according to the distributed control model topology,

[0032] is the maximum power flow of the transmission line between nodes il;

[0033] The reference bus constraints are:

[0034] Default S ref , S ref The initial phase angle of each node i in is

[0035] The capacity constraint of the distributed motor is:

[0036]

[0037] In the formula, g is the distributed motor number, and g∈S DG-1 , S DG-1is the set of distributed motors in the distributed control model;

[0038] The distributed motor ramp-up constraint is:

[0039]

[0040] In the formula, is the maximum ramp-up power of the distributed motor in time period t, and

[0041] The distributed motor ramp-down constraint is:

[0042]

[0043] In the formula, is the maximum ramp-down power of the distributed motor in time period t, and

[0044] Preferably, solving the distributed control model based on the alternating direction multiplier method includes: taking the internal node power balance constraint of the virtual power plant and the reference bus constraint as the equality constraint, and constructing the equality constraint of the alternating direction multiplier method as follows:

[0045]

[0046] {0} is the central processing node.

[0047] Taking the capacity constraint of the transmission line, the capacity constraint of the distributed generator, the ramp-up constraint of the distributed generator, and the ramp-down constraint of the distributed generator as inequality constraints, the inequality constraints of the alternating multiplier method are constructed as follows:

[0048]

[0049] Based on the alternating direction multiplier method, the augmented Lagrangian form L(x,λ,μ) is obtained as follows:

[0050]

[0051] In the formula, X i is the state x of the i-th node i The value range set of

[0052] is the model node set,

[0053] λ ′ and μ ′ are the augmented constraint coefficients in the alternating direction multiplier method, and the parameters respond to the control received in the previous iteration. Control requests received in this iteration The iterative augmentation method is:

[0054]

[0055] In the formula, and Generate or receive a control request Then, we use L(x,λ,μ) to solve the constraint coefficients before augmentation in the alternating direction multiplier method.

[0056] and Received control response Then, L(x,λ,μ) is used to solve the constraint coefficients before augmentation in the alternating direction multiplier method.

[0057] Preferably, the first local variable of the virtual power plant, the second local variable of the virtual power plant and the global variable are introduced, including: the first local variable of the current virtual power plant j is:

[0058]

[0059] In one embodiment, λ ′ k-i and μ ′ k-i They are the matrices corresponding to node i in the virtual power plant. Elements in

[0060] The second local variable of the current virtual power plant j is:

[0061]

[0062] The global variables are:

[0063]

[0064] In the formula, and To introduce variables after review mechanism judgment and k+1 ,

[0065] k is the number of iterations of the alternating direction multiplier method,

[0066] z j is the variable name corresponding to the first local variable of the jth virtual power plant to be calculated,

[0067] L j (·) is the augmented Lagrangian form of the jth virtual power plant,

[0068] n is the number of virtual power plants in the model.

[0069] Preferably, a communication review mechanism is preset, and the variables are updated during the iteration process and whether the iteration meets the communication requirements is determined according to the communication review mechanism, including: the review mechanism of the first local variable of the virtual power plant is:

[0070]

[0071] The review mechanism of the second local variable of the virtual power plant is:

[0072]

[0073] The review mechanism for global variables is:

[0074]

[0075] Where a1, a2 and a3 are review weights, and b1, b2 and b3 are review attenuations.

[0076] Preferably, a communication review mechanism is preset, and variables are updated during the iteration process and whether the current iteration meets the communication requirements is determined according to the communication review mechanism, including: in the current iteration k, the first local variable of the virtual power plant and the second local variable of the virtual power plant obtained in the previous iteration are used to update the global variable; based on the preset communication review mechanism, it is determined whether the updated global variable meets the communication requirements, and if so, For control requests, the control requests are sent from the central processing node to each virtual power plant; otherwise, the communication process of the control request is suspended.

[0077] Preferably, a communication review mechanism is preset, and the variables are updated during the iteration process and the communication review mechanism is used to determine whether the current iteration meets the communication requirements, including: in the current iteration k, if the virtual power plant j receives a control request, the control request is used to and the second local variable of virtual power plant j obtained in the last iteration Update the first local variable of the virtual power plant Based on the preset communication review mechanism, it is determined whether the first local variable of the updated virtual power plant j meets the communication requirements. If so, the virtual power plant j is updated with As a first control response, a first control response is sent to the central processing node; using the control request and the first local variable of the virtual power plant j after review obtained in this iteration Update the second local variable of the virtual power plant Based on the preset communication review mechanism, it is determined whether the updated second local variable of the updated virtual power plant j meets the communication requirements. If so, the virtual power plant j is The second control response is sent to the central processing node respectively.

[0078] Preferably, the variables meeting the communication requirements are communicated, and the distributed control of the virtual power plant is implemented based on the communication results, including: the central processing node uses the local parameters and remote parameters and The regulation response of virtual power plant j is introduced In the formula, the node Thus, all virtual power plants hosted by the central processing node are regulated.

[0079] The second aspect of the present invention relates to a virtual power plant distributed control system based on communication review; it is implemented by a virtual power plant distributed control method based on communication review in the first aspect of the present invention; the system includes a generation module, a solution module, a review module, and a communication module; wherein the generation module is used to generate a distributed control model of node power within the virtual power plant and between virtual power plants using a DC power flow constraint problem; the solution module is used to solve the distributed control model based on the alternating direction multiplier method, and introduce the first local variable of the virtual power plant, the second local variable of the virtual power plant, and the global variable review module, which is used to preset a communication review mechanism, update the variables during the iteration process, and judge whether this iteration meets the communication requirements according to the communication review mechanism; the communication module is used to implement communication for variables that meet the communication requirements, and implement distributed control of the virtual power plant based on the communication results. The third aspect of the present invention relates to a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method described in the first aspect of the present invention.

[0080] A fourth aspect of the present invention relates to a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect of the present invention.

[0081] The beneficial effect of the present invention is that, compared with the prior art, a distributed control method and system of a virtual power plant based on communication review in the present invention utilizes the DC optimal power flow to obtain the control mode, sets the communication parameters with the parameters of the alternating direction multiplier method to assist in communication review, and solves the optimal control result, thereby minimizing the operating cost and maximizing the economic benefit of the virtual power plant communication dispatching.

[0082] The beneficial effects of the present invention also include:

[0083] Distributed computing can protect against threats to the feasibility of centralized computing, including privacy threats, computing complexity threats, storage threats, etc.

[0084] The introduction of a communication review mechanism improves the communication efficiency of distributed control of virtual power plants and reduces communication costs.

[0085] Compared with the traditional algorithm, the ADMM adopted in the present invention has a faster convergence rate, which is beneficial to improving the overall convergence rate.

[0086] The distributed control algorithm of virtual power plants based on communication review has significant economic and social benefits, and can promote the further development of distributed control of virtual power plants. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1 A schematic diagram of the internal topology of a VPP in a distributed control method of a virtual power plant based on communication review of the present invention;

[0088] Figure 2 A schematic diagram of the networking topology of multiple VPPs in a distributed control method of a virtual power plant based on communication review of the present invention;

[0089] Figure 3 It is a schematic diagram of the original residual convergence effect of the algorithm after adding the communication review mechanism to the distributed control method of a virtual power plant based on communication review of the present invention;

[0090] Figure 4 It is a schematic diagram of the communication situation of selecting various parameters under the action of the communication review mechanism in a distributed control method of a virtual power plant based on communication review of the present invention;

[0091] Figure 5 A schematic diagram of the algorithm accuracy convergence effect in a distributed control method of a virtual power plant based on communication review of the present invention;

[0092] Figure 6 This is a schematic diagram of the variation of algorithm convergence accuracy with communication cost in a distributed control method of a virtual power plant based on communication review in the present invention. DETAILED DESCRIPTION

[0093] In order to make the purpose, technical solution and advantages of the present invention clearer and more accurate, the technical solution of the present invention is described in detail through multiple specific implementations below. The embodiments adopted by the present invention are only used to explain the present invention and are not used to limit the content of the present invention.

[0094] This paper proposes a virtual power plant distributed control algorithm based on communication review, which aims at the DC optimal power flow problem of virtual power plants with distributed generation (DG), aiming to maximize economic benefits, that is, minimize operating costs. The alternating direction multiplier method is used to solve the dual problem of the DC optimal power flow problem, update the original variables and the dual variables, and add a communication review mechanism to reduce communication costs and improve communication efficiency.

[0095] A first aspect of the present invention relates to a distributed control method for a virtual power plant based on communication review, the method comprising steps 1 to 4.

[0096] Step 1: Generate a distributed control model of node power within a virtual power plant and between virtual power plants using the DC power flow constraint problem.

[0097] The DC power flow constraint problem is used to generate a distributed control model of node power within a virtual power plant and between virtual power plants, including: taking the distributed motor grid-connected bus as the node to obtain the topology of the distributed control model of the virtual power plant; taking the minimum sum of node scheduling costs as the model's goal and the DC power flow constraint as the model's constraint to generate a distributed control model.

[0098] Figure 1 This is a schematic diagram of the internal topology of a VPP in a distributed control method of a virtual power plant based on communication review in the present invention. Figure 2 This is a schematic diagram of the networking topology of multiple VPPs in a distributed control method of a virtual power plant based on communication review in the present invention.

[0099] like Figure 1 , 2 , the distributed generation and DC optimal power flow problems in the virtual power plant are modeled as follows:

[0100]

[0101]

[0102] The goal of the model is to minimize the sum of node scheduling costs, including: the i-th node in state x i The scheduling cost under is:

[0103]

[0104] In the formula, the state x i Including node power and phase angle x i =[P i θ i ],and

[0105] S B It is the node set in the distributed control model, that is, the grid connection point of all distributed motors. One grid connection point can be connected to multiple distributed motors through the bus.

[0106] S DG is the set of all distributed motor combinations connected to a node in the distributed control model,

[0107] S Tis the set of time periods to be scheduled, the time periods to be scheduled are from 1 to T,

[0108] f i (·) is the active power of the ith node The cost of

[0109] is the available power of the ith node in time period t.

[0110] The formula means that if there are distributed motors on the bus, the dispatch cost is determined by the state of the distributed motor combination. If there are no distributed motors on the bus, no cost is calculated.

[0111] The DC power flow constraints are constraints of the model, including: the DC power flow constraints include power balance constraints of internal nodes of the virtual power plant, capacity constraints of transmission lines, reference bus constraints, capacity constraints of distributed motors, distributed motor ramp-up constraints, and distributed motor ramp-down constraints.

[0112] The power balance constraint of nodes inside the virtual power plant is:

[0113]

[0114] In the formula, is the load of the ith node,

[0115] l is S B Different from other nodes in i,

[0116] S B is the set of all nodes in the model,

[0117] B il is the equivalent admittance vector between nodes il in the admittance matrix pre-calculated according to the distributed control model topology,

[0118] is the phase angle of the lth node in time period t;

[0119] The capacity constraint of the transmission line is:

[0120]

[0121] In the formula, X il is the equivalent reactance vector between the grid-connected nodes ij corresponding to the virtual power plant pre-calculated according to the distributed control model topology,

[0122] is the maximum power flow of the transmission line between nodes il;

[0123] The reference bus constraints are:

[0124] Default Sref , S ref The initial phase angle of each node i in is

[0125] The capacity constraint of the distributed motor is:

[0126]

[0127] In the formula, g is the distributed motor number, and g∈S Dg-1 , S DG-1 is the set of distributed motors in the distributed control model;

[0128] The distributed motor ramp-up constraint is:

[0129]

[0130] In the formula, is the maximum ramp-up power of the distributed motor in time period t, and

[0131] The distributed motor ramp-down constraint is:

[0132]

[0133] In the formula, is the maximum ramp-down power of the distributed motor in time period t, and

[0134] Step 2, solving the distributed control model based on the alternating direction multiplier method, and introducing the first local variable of the virtual power plant, the second local variable of the virtual power plant and the global variable.

[0135] Solving the distributed control model based on the alternating direction multiplier method includes: taking the internal node power balance constraint of the virtual power plant and the reference bus constraint as the equality constraint, and constructing the equality constraint of the alternating direction multiplier method as follows:

[0136]

[0137] {0} is the central processing node.

[0138] As mentioned above, let C i =[0,B i1 I;…;0,B 2i I;…;I,B ii I;…;0,B iN I], the power balance constraint of the internal nodes of the virtual power plant can be rewritten as:

[0139]

[0140] In the formula, Ci is the matrix used to calculate the equality constraints of the Lagrange multiplier method,

[0141] B iN is the equivalent admittance vector between node i and node N, B ii =0, there is B iN =[b iN- ,b iN-2 ,…,b iN- ,…],b iN-s is the equivalent admittance of the sth feasible path between node i and node N, I is the unit matrix, 0 is the matrix of all zeros, x i =[p i ,θ i ];

[0142] Similarly, the capacity limit of the transmission line can be rewritten as:

[0143]

[0144] in, but,

[0145] A i (x i )=C i x i -D i

[0146] Q i (x i )=H i x i -M i

[0147] For the constraints on other single nodes, each node is independent of each other and does not include the coupling relationship. Then,

[0148] χ i ={c i |Independent constraints,i∈S B}

[0149] The independent constraints include bus constraints, capacity constraints of distributed motors, distributed motor ramp-up constraints, and distributed motor ramp-down constraints.

[0150] Taking the capacity constraint of the transmission line, the capacity constraint of the distributed generator, the ramp-up constraint of the distributed generator, and the ramp-down constraint of the distributed generator as inequality constraints, the inequality constraints of the alternating multiplier method are constructed as follows:

[0151]

[0152] Based on the alternating direction multiplier method, the augmented Lagrangian form L(x,λ,μ) is obtained as follows:

[0153]

[0154] The central processing node calculates L(x,λ,μ) of all nodes. On the virtual power plant side, only L of all nodes in the virtual power plant is calculated. j (x,λ,L).

[0155] The above formula can also be expressed as:

[0156]

[0157] In the formula, χ i is the state x of the i-th node i The value range set of

[0158] is the model node set,

[0159] λ ′ and μ ′ are the augmented constraint coefficients in the alternating direction multiplier method, and the parameters respond to the control received in the previous iteration. Control requests received in this iteration The iterative augmentation method is:

[0160]

[0161] In the formula, and Generate or receive a control request Then use l(x,λ,μ) to solve the constraint coefficients before augmentation in the alternating direction multiplier method.

[0162] and Received control response Then, the constraint coefficients before augmentation in the alternating direction multiplier method are solved by L(x, λ, μ). Thus, the first local variable of the virtual power plant, the second local variable of the virtual power plant and the global variable are introduced, including: the first local variable of the current virtual power plant j is:

[0163]

[0164] In one embodiment, λ ′ k-i and μ ′ k-i They are the matrices corresponding to node i in the virtual power plant. Elements in

[0165] The second local variable of the current virtual power plant j is:

[0166]

[0167] The global variables are:

[0168]

[0169] In the formula, and To introduce variables after review mechanism judgment and k+1 ,

[0170] k is the number of iterations of the alternating direction multiplier method,

[0171] z j is the variable name corresponding to the local variable of the jth virtual power plant to be calculated,

[0172] L j (·) is the augmented Lagrangian form of the jth virtual power plant,

[0173] n is the number of virtual power plants in the model.

[0174] Step 3: preset a communication review mechanism, update the variables during the iteration process, and determine whether the iteration meets the communication requirements based on the communication review mechanism.

[0175] Initialize the local Lagrange multiplier corresponding to the virtual power plant Intermediate variables of local Lagrange multipliers corresponding to virtual power plants for communication review Lagrange Multipliers for the Dual Problem Intermediate variables of Lagrange multipliers for the dual problem of communication censorship m iteration is the maximum number of iterations, ε pri and ε dual Represent the thresholds of the primal residual and the dual residual, respectively, based on which the algorithm termination condition will be set.

[0176] A communication review mechanism is preset, and variables are updated during the iteration process and whether the iteration meets the communication requirements is determined according to the communication review mechanism, including: the review mechanism of the first local variable of the virtual power plant is:

[0177]

[0178] The review mechanism of the second local variable of the virtual power plant is:

[0179]

[0180] The review mechanism of the global variables is:

[0181]

[0182] In the formula, a1, a2, and a3 are the review weights respectively, and b1, b2, and b3 are the review attenuations respectively.

[0183] The thresholds a1b1 for the communication review involved k , a2b2 k , a3b3 k . Where a1 > 0, a2 > 0, a3 > 0; 0 < b1 < 1, 0 < b2 < 1, 0 < b3 < 1; k represents the number of iterations.

[0184] A preset communication review mechanism updates variables during the iteration process and determines whether the current iteration meets the communication requirements according to the communication review mechanism, including: in the current iteration k, the global variables are updated using the local variables of the virtual power plant and the local intermediate variables of the virtual power plant obtained in the previous iteration; based on the preset communication review mechanism, it is determined whether the updated global variables meet the communication requirements. If they meet, is used as the regulation request, and the regulation request is sent from the central processing node to each virtual power plant; otherwise, the communication process of the regulation request is suspended.

[0185] A preset communication review mechanism updates variables during the iteration process and determines whether the current iteration meets the communication requirements according to the communication review mechanism, including: in the current iteration k, if virtual power plant j receives a regulation request, then the regulation request and the second local variable of virtual power plant j obtained in the previous iteration are used to update the first local variable of the virtual power plant Based on the preset communication review mechanism, it is determined whether the updated first local variable of virtual power plant j meets the communication requirements. If it meets, virtual power plant j uses as the first regulation response and sends the first regulation response to the central processing node; the regulation request and the reviewed first local variable of virtual power plant j obtained in this iteration are used to update the second local variable of the virtual power plant Based on the preset communication review mechanism, it is determined whether the updated second local variable of virtual power plant j meets the communication requirements. If it meets, virtual power plant j uses as the second regulation response and sends the second regulation response to the central processing node respectively.

[0186] Judge the iteration update gap of the above variables, and communication is carried out only when it is large enough.

[0187] Step 4, implement communication for the variables that meet the communication requirements, and implement distributed regulation of the virtual power plant based on the communication results.

[0188] Implement communication for variables that meet the communication requirements, and implement distributed control of the virtual power plant based on the communication results, including: the central processing node uses local parameters and remote parameters and The regulation response of virtual power plant j is introduced In the formula, the node Thus, all virtual power plants hosted by the central processing node are regulated.

[0189] As mentioned above, the optimal control method is:

[0190]

[0191] Solve to get the optimal control quantity

[0192]

[0193] The solution results include the optimal active power and phase angle.

[0194] In the embodiment of the present invention, there is a 6-node system with 2 distributed motors and 3 loads, VPP0 represents the central processing unit, VPP1 = {1, 6}, VPP2 = {2, 3, 4, 5}, M iteration =600,ρ>0,ε pri =1e-6,ε dual =1e-6.

[0195] The thresholds for communication review are a1b1 respectively. k =33×0.95 k , a2b2 k =56×0.95 k , a3b3 k =7×0.929 k , n = 2. As the number of iterations increases, the threshold of communication review tends to decrease. The iteration value will get closer and closer to the optimal value, and the decrease of the communication review threshold can effectively ensure accuracy.

[0196] The embodiment of the present invention adopts the algorithm of the present invention to perform calculations, and the comparative example adopts a distributed control algorithm without communication review that has been disclosed in the prior art to perform calculations.

[0197] Figure 3 This is a schematic diagram of the original residual convergence effect of the algorithm after adding the communication review mechanism to the distributed control method of a virtual power plant based on communication review in the present invention. Figure 3 As shown in the figure, the y, z1, z2, p1 and p2 in the vertical axis labels are the information exchange y between the virtual power plant and the central processor. k+1 , z jk+1 and p j k+1 , where the subscripts 1 and 2 refer to VPP1 and VPP2. It can be seen that after adding communication review, as the number of iterations increases, the original residual can reach the termination condition preset by the algorithm.

[0198] Figure 4 This is a schematic diagram of the communication status of the selection of various parameters under the action of the communication review mechanism in a virtual power plant distributed control method based on communication review of the present invention. Figure 4 As shown in the figure, after adding the communication review mechanism, the communication status of the virtual power plant system, the black grid represents communication in this iteration, and the white grid represents no communication in this iteration. Adding communication review can effectively reduce unnecessary communication and achieve the goal of efficient communication.

[0199] Figure 5 It is a schematic diagram of the algorithm accuracy convergence effect in the distributed control method of a virtual power plant based on communication review of the present invention. Figure 6 This is a schematic diagram of the change of algorithm convergence accuracy with communication cost in a distributed control method of a virtual power plant with communication review in the present invention. Figure 5 , 6 As shown in Figure 2, when the communication review is added and converged to the same accuracy, although the number of iterations increases, the communication cost is reduced.

[0200] In summary, it is verified that the algorithm proposed in the present invention has high communication efficiency in the distributed control of virtual power plants. In view of the reality that there is a large amount of communication in virtual power plants, a communication review mechanism is added, which can avoid unnecessary communication and information exchange.

[0201] The present invention establishes a model of distributed generation and DC optimal power flow problems in a virtual power plant, initializes corresponding variables and parameters, calculates global variables using the proposed distributed dual consistency ADMM method based on communication review, and calculates local variables and original variables using the proposed distributed dual consistency ADMM method based on communication review to achieve distributed control of the virtual power plant and obtain a global optimal solution.

[0202] In this algorithm, communication and information exchange will only be performed when the difference between two iterative updates is greater than a preset threshold, which can significantly reduce the number of communications to achieve efficient communication. At the same time, the threshold mentioned above changes with the number of iterations. Because as the number of iterations increases, the calculated update iteration value will be closer to the optimal value. If the threshold is a fixed value, the accuracy of the algorithm cannot be guaranteed. This algorithm can effectively improve communication efficiency and fully consider the core concept of "communication" in virtual power plants.

[0203] The second aspect of the present invention relates to a distributed control system of a virtual power plant based on communication review; it is implemented using a distributed control method of a virtual power plant based on communication review in the first aspect of the present invention; the system includes a generation module, a solution module, a review module, and a communication module; wherein the generation module is used to generate a distributed control model of node power within a virtual power plant and between virtual power plants using a DC power flow constraint problem; the solution module is used to solve the distributed control model based on the alternating direction multiplier method, and introduce local variables of the virtual power plant, local intermediate variables of the virtual power plant, and global variables; the review module is used to preset a communication review mechanism, update variables during the iteration process, and determine whether this iteration meets the communication requirements based on the communication review mechanism; the communication module is used to implement communication for variables that meet the communication requirements, and implement distributed control of the virtual power plant based on the communication results.

[0204] A third aspect of the present invention relates to a terminal, comprising a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method described in the first aspect of the present invention.

[0205] A fourth aspect of the present invention relates to a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect of the present invention.

[0206] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit them. Although the present invention is described in detail with reference to the above embodiments, it should be understood by those skilled in the art that the technical solutions of the present invention still include contents that can modify or replace the specific embodiments of the present invention. Any modification or replacement that does not depart from the spirit and scope of the present invention shall be included in the protection scope of the claims of the present invention.

Claims

1. A distributed control method for a virtual power plant based on communication review, characterized in that: The method comprises the following steps: Step 1, using the DC power flow constraint problem to generate a distributed control model of node power within the virtual power plant and between virtual power plants; Step 2, solving the distributed control model based on the alternating direction multiplier method, and introducing local variables of the virtual power plant, local intermediate variables of the virtual power plant and global variables; Step 3: preset a communication review mechanism, update the variables during the iteration process, and determine whether the current iteration meets the communication requirements according to the communication review mechanism; Step 4: Implement communication for variables that meet the communication requirements, and implement distributed control of the virtual power plant based on the communication results.

2. According to claim 1, a distributed control method for a virtual power plant based on communication review is characterized in that: The method of using the DC power flow constraint problem to generate a distributed control model for node power within a virtual power plant and between virtual power plants includes: Taking the distributed motor grid-connected bus as the node, the topology of the distributed control model of the virtual power plant is obtained; A distributed control model is generated with the minimum sum of node scheduling costs as the model objective and DC power flow constraints as the model constraints.

3. According to claim 2, a distributed control method of a virtual power plant based on communication review is characterized in that: The goal of the model based on minimizing the sum of node scheduling costs includes: The i-th node is in state x i The scheduling cost under is: In the formula, the state x i Including node power and phase angle, S B is the node set in the distributed control model, S DG is the set of all distributed motor combinations connected to a node in the distributed control model, S T is the set of time periods to be scheduled, f i (·) is the active power of the ith node The cost of is the active power of the i-th node in time period t.

4. According to claim 3, a distributed control method for a virtual power plant based on communication review is characterized in that: The DC power flow constraints are constraints of the model, including: The DC power flow constraints include power balance constraints of nodes inside the virtual power plant, capacity constraints of transmission lines, reference bus constraints, capacity constraints of distributed motors, distributed motor ramp-up constraints, and distributed motor ramp-down constraints.

5. According to claim 4, a distributed control method for a virtual power plant based on communication review is characterized in that: The power balance constraint of nodes inside the virtual power plant is: In the formula, is the load of the ith node, l is S B Different from other nodes in i, S B is the set of all nodes in the model, B il is the equivalent admittance vector between nodes il in the admittance matrix pre-calculated according to the distributed control model topology, is the phase angle of the lth node in time period t; The capacity constraint of the transmission line is: Where, X il is the equivalent reactance vector between the grid-connected nodes ij corresponding to the virtual power plant pre-calculated according to the distributed control model topology, is the maximum power flow of the transmission line between nodes il; The reference bus constraints are: Default S ref , S ref The initial phase angle of each node i in is The capacity constraint of the distributed motor is: In the formula, g is the distributed motor number, and g∈S DG-1 , S DG- is the set of distributed motors in the distributed control model; The distributed motor ramp-up constraint is: In the formula, is the maximum ramp-up power of the distributed motor in time period t, and The distributed motor ramp-down constraint is: In the formula, is the maximum ramp-down power of the distributed motor in time period t, and 6. A distributed control method for a virtual power plant based on communication review according to claim 5, characterized in that: The method of solving the distributed control model based on the alternating direction multiplier method includes: Taking the internal node power balance constraint of the virtual power plant and the reference bus constraint as the equality constraint, the equality constraint of the alternating direction multiplier method is constructed as follows: {0} is the central processing node. Taking the capacity constraint of the transmission line, the capacity constraint of the distributed generator, the ramp-up constraint of the distributed generator, and the ramp-down constraint of the distributed generator as inequality constraints, the inequality constraints of the alternating multiplier method are constructed as follows: Based on the alternating direction multiplier method, the augmented Lagrangian form L(x,λ,μ) is obtained as follows: In the formula, χ i is the state x of the i-th node i The value range set of is the model node set, λ ′ and μ ′ are the augmented constraint coefficients in the alternating direction multiplier method, and the parameters respond to the control received in the previous iteration. Control requests received in this iteration The iterative augmentation method is: In the formula, and Generate or receive a control request Then, we use L(x,λ,μ) to solve the constraint coefficients before augmentation in the alternating direction multiplier method. and Received control response Then, L(x,λ,μ) is used to solve the constraint coefficients before augmentation in the alternating direction multiplier method.

7. A distributed control method for a virtual power plant based on communication review according to claim 6, characterized in that: The first local variable introduced into the virtual power plant, the second local variable of the virtual power plant and the global variable include: The first local variable of the current virtual power plant j is: The second local variable of the current virtual power plant j is: The global variables are: In the formula, and To introduce variables after review mechanism judgment and k+1 , k is the number of iterations of the alternating direction multiplier method, z j is the variable name corresponding to the first local variable of the jth virtual power plant to be calculated, L j (·) is the augmented Lagrangian form of the jth virtual power plant, n is the number of virtual power plants in the model.

8. A distributed control method for a virtual power plant based on communication review according to claim 7, characterized in that: The preset communication review mechanism updates variables during the iteration process and determines whether the current iteration meets the communication requirements according to the communication review mechanism, including: The review mechanism of the first local variable of the virtual power plant is: The review mechanism of the second local variable of the virtual power plant is: The review mechanism of the global variables is: Where a1, a2 and a3 are review weights, and b1, b2 and b3 are review attenuations.

9. A distributed control method for a virtual power plant based on communication review according to claim 8, characterized in that: The preset communication review mechanism updates variables during the iteration process and determines whether the current iteration meets the communication requirements according to the communication review mechanism, including: In the current iteration k, the first local variable of the virtual power plant and the second local variable of the virtual power plant obtained in the previous iteration are used to update the global variable; Based on the preset communication review mechanism, it is determined whether the updated global variables meet the communication requirements. If they meet the requirements, For control requests, the control requests are sent from the central processing node to each virtual power plant; Otherwise, the communication process of the control request is suspended.

10. A distributed control method for a virtual power plant based on communication review according to claim 9, characterized in that: The preset communication review mechanism updates variables during the iteration process and determines whether the current iteration meets the communication requirements according to the communication review mechanism, including: In the current iteration k, if virtual power plant j receives a control request, it uses the control request and the second local variable of virtual power plant j obtained in the last iteration Update the first local variable of the virtual power plant Based on the preset communication review mechanism, it is determined whether the first local variable of the updated virtual power plant j meets the communication requirements. If so, the virtual power plant j is updated with The first control response is sent to the central processing node; Leveraging Control Requests and the first local variable of the virtual power plant j after review obtained in this iteration Update the second local variable of the virtual power plant Based on the preset communication review mechanism, it is determined whether the updated second local variable of the updated virtual power plant j meets the communication requirements. If so, the virtual power plant j is The second control response is sent to the central processing node respectively.

11. A distributed control method for a virtual power plant based on communication review according to claim 10, characterized in that: The implementing of communication on the variables meeting the communication requirements and implementing the distributed control of the virtual power plant based on the communication results includes: The central processing node uses local parameters and remote parameters and The regulation response of virtual power plant j is introduced In the formula, the node Thus, all virtual power plants hosted by the central processing node are regulated.

12. A virtual power plant distributed control system based on communication review; characterized in that: The method is implemented by utilizing a distributed control method of a virtual power plant based on communication review as described in any one of claims 1 to 11; The system includes a generation module, a solution module, a review module, and a communication module; wherein, The generation module is used to generate a distributed control model of node power within a virtual power plant and between virtual power plants by using a DC power flow constraint problem; The solution module is used to solve the distributed control model based on the alternating direction multiplier method, and introduce the first local variable of the virtual power plant, the second local variable of the virtual power plant and the global variable; The review module is used to preset a communication review mechanism, update variables during the iteration process, and determine whether the current iteration meets the communication requirements according to the communication review mechanism; The communication module is used to implement communication on variables that meet communication requirements, and implement distributed control of the virtual power plant based on the communication results.

13. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1-11.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 11 are implemented.

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