Distributed Photovoltaic Participating in Regulation of Distribution Network Voltage Optimization Control Method and Device

Abstract

The present invention relates to a method and device for optimizing and controlling the voltage of a distribution network with distributed photovoltaic (PV) participating in regulation. The method includes: First, obtaining the data of the distribution network with distributed PV, and linearizing the power flow model of the distribution network according to the distribution network data to obtain a linear power flow model of the distribution network. Then, taking the minimum voltage deviation of the PV nodes as the optimization objective, determining the objective function and constraint conditions for optimizing the voltage of the distribution network, and establishing a voltage optimization control model for the distribution network. Finally, based on the accelerated dual ascent algorithm, updating the Lagrange multipliers by using the PV node voltages and PV reactive powers at the previous two moments, and then exchanging the Lagrange multiplier information with adjacent PV inverters to calculate the reactive power at the current moment. In the present invention, the PV inverters only need to exchange data with adjacent PV inverters to achieve distributed online calculation of reactive power, with a fast convergence speed, realizing fast and accurate control of the voltage of the distribution network.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network operation control, and particularly to a method and device for optimizing voltage control of a distribution network with distributed photovoltaic (PV) participation in regulation. Background Art

[0002] Large-scale development of distributed PV is mostly carried out in rural areas, while the power load is distributed in urban areas, resulting in unbalanced geographical distribution of power sources and loads. During the day, PV usually generates a large amount of power at noon, and the load often shows double peaks during the day and at night, resulting in mismatched time distribution of power sources and loads. In addition, due to the high R / X ratio of the distribution line, the strong volatility of PV output will cause rapid voltage fluctuations, which may lead to voltage violation problems such as over / under voltage. Capacitors and traditional voltage regulators are difficult to handle rapid voltage fluctuations, while PV inverters have the ability to support reactive power and voltage regulation.

[0003] The voltage regulation methods of PV inverters mainly include local control, centralized control, and distributed control. In local control, PV only adjusts the reactive power injection depending on the local voltage measurement value, without a centralized controller and with a relatively fast control speed, but it may not be able to ensure a feasible voltage. A large amount of research has been carried out on centralized voltage control of distribution networks, which solves the power flow problem based on all system information and has an excessive computational burden. At the same time, due to the limited and low-quality communication infrastructure in the current distribution network, it is not applicable to distribution networks with high PV penetration. Summary of the Invention

[0004] In view of this, it is necessary to provide a method for optimizing voltage control of a distribution network with distributed PV participation in regulation to solve the above-mentioned defects of the prior art.

[0005] To solve the above problems, in the first aspect, an embodiment of the present invention provides a method for optimizing voltage control of a distribution network with distributed PV participation in regulation, including:

[0006] Step S1, obtaining distribution network data containing distributed PV;

[0007] Step S2, linearizing the power flow model of the distribution network according to the distribution network data to obtain a linear power flow model of the distribution network; considering the voltage control of PV nodes equipped with PV inverters, determining the relationship between the PV node voltage and the reactive power of the PV inverter;

[0008] Step S3, based on the relationship between the PV node voltage and the reactive power of the PV inverter, with the minimum PV node voltage deviation as the optimization goal, determining the objective function and constraint conditions for optimizing the distribution network voltage, and establishing a distribution network voltage optimization control model;

[0009] Step S4: Based on the accelerated dual ascent algorithm, solve the voltage optimization control model of the distribution network to obtain the reactive power output of the photovoltaic inverter, and send the reactive power scheduling instruction to the photovoltaic inverter controller to adjust the voltage of the photovoltaic nodes through the reactive power generated by the photovoltaic inverter.

[0010] Preferably, the distribution network data includes the voltage measurement data and reactive power data of each photovoltaic node at the previous two moments, the upper and lower limits of the reactive power of the photovoltaic inverter, and the upper and lower limit constraints of the voltage of each photovoltaic node.

[0011] Preferably, in step S2, the expression of the distribution network power flow model is:

[0012]

[0013] In the formula, P ij , Q ij represent the active and reactive powers flowing from node i to node j, p j , q j are the active and reactive powers output by node j, V i is the voltage value of node i, r ij , x ij are the line resistance and line reactance between node i and node j.

[0014] Preferably, in step S2, the linearization of the distribution network power flow model to obtain the linear power flow model of the distribution network specifically includes:

[0015] Ignoring the active and reactive line losses and assuming that the voltage of each node is close to the reference voltage, the linearization of the distribution network power flow model is as follows:

[0016]

[0017] V i -V j =r ij P ij +x ij Q ij (6)

[0018] The linear power flow model of the distribution network can be expressed in the following form:

[0019] v=1+Rp+Xq (7)

[0020] Among them, v represents the column vector composed of node voltages, p represents the column vector composed of node active power injections, q represents the column vector composed of node reactive power injections, R is the resistance matrix, and X is the reactance matrix;

[0021] In the above formula, 1 is the unit column vector, and R and X are expressed in the following forms:

[0022]

[0023] In the above formula, L i(j) represents the path from node 0 to node i (j); each element of R and X is only related to the network topology and line impedance.

[0024] Preferably, in step S2, considering the photovoltaic node voltage control with a photovoltaic inverter, determine the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter, including:

[0025] Assume that the photovoltaic node voltage is measured and the reactive power injected into the distribution network is adjusted only through the photovoltaic inverter, and consider the photovoltaic node voltage control with a photovoltaic inverter; in order to distinguish the voltage of the photovoltaic node from the voltage of the load node, the node voltage amplitude vector is decomposed as follows:

[0026]

[0027] In the above formula, v G is the voltage amplitude of the photovoltaic node, v L is the voltage amplitude of the load node; the resistance matrix R and the reactance matrix X are decomposed as follows:

[0028]

[0029] Substitute equations (10), (11) and (12) into equation (7) to obtain the voltage amplitude of the photovoltaic node:

[0030] v G = 1 + R GG p G + R GL p L + X GG q G + X GL q L (13)

[0031] In the formula, p G , q G represent the active power and reactive power injected by the photovoltaic node into the distribution network, p L , q L represent the active power and reactive power injected by the load; R GG is the sensitivity matrix of the photovoltaic node voltage to the photovoltaic active power fluctuation, R GL is the sensitivity matrix of the photovoltaic node voltage to the load active power fluctuation, X GG is the sensitivity matrix of the photovoltaic node voltage to the photovoltaic reactive power fluctuation, X GL is the sensitivity matrix of the photovoltaic node voltage to the load reactive power fluctuation;

[0032] Assume p G and p L and q L are constants. If the voltage of the PV node is regulated only by the reactive power generated by the PV inverter, then Equation (13) is simplified to obtain the relationship between the voltage of the PV node and the reactive power of the PV inverter as follows:

[0033]

[0034] In the formula, is the voltage curve of the PV node without recovery power compensation.

[0035] Preferably, in step S3, based on the relationship between the voltage of the PV node and the reactive power of the PV inverter, with the minimum voltage deviation of the PV node as the optimization goal, the objective function and constraint conditions for the voltage optimization of the distribution network are determined, and a voltage optimization control model for the distribution network is established, which specifically includes:

[0036] Based on Equation (14), with the minimum voltage deviation of the PV node as the optimization goal, the objective function of the voltage optimization model for the distribution network is established as:

[0037]

[0038] In the formula, minF(q G ) indicates that the optimization goal is to minimize the deviation of the node voltage from the rated voltage;

[0039] The voltage constraint expression for the node where the distributed PV is located is:

[0040] v min ≤v G ≤v max (17)

[0041] In the above formula, v min and v max are the upper and lower limits of the voltage of the node where the distributed PV is located, respectively;

[0042] The reactive power constraint expression for the distributed PV is:

[0043] q min ≤q G ≤q max (18)

[0044] In the above formula, q min and q max are the upper and lower limits of the PV reactive power output, respectively;

[0045] Equations (16), (17) and (18) constitute the voltage optimization control model for the distribution network.

[0046] Preferably, in step S4, solving the optimal control variables of the Lagrangian function:

[0047] Construct the Lagrangian function based on the optimal control variables of the distribution network voltage optimization control model as follows:

[0048]

[0049] In the above formula, the vectors λ 、 μ 、 are Lagrange multipliers related to the inequality constraints q min ≤q G 、q G ≤q max 、v min ≤v G 、v G ≤v max Define the vector a as containing all Lagrange multipliers,

[0050]

[0051] Solve the optimal control variables of the Lagrangian function:

[0052]

[0053] Substitute q G in formula (17) into formula (16) to obtain the Lagrangian dual function:

[0054]

[0055] In the above formula, B is the coefficient matrix and b is the coefficient vector, and the expressions are:

[0056]

[0057] Update the dual variables using the accelerated projected gradient method:

[0058]

[0059] In the above formula, is the acceleration variable obtained by the linear combination of the two most recent moments of the dual variables:

[0060] c t+1 = a t +β t+1 (a t - a t-1 ) (25)

[0061] In the above formula, βt+1 The expression is:

[0062]

[0063] In the above formula, θ t+1 The iterative expression is:

[0064]

[0065] The local update form of the Lagrangian operator is expressed as follows:

[0066]

[0067]

[0068] In the formula, λ i,t+1 , λ i,t and λ i,t-1 are the Lagrangian operators of the photovoltaic node i at times t + 1, t, and t - 1 respectively λ , q i,t and q i,t-1 are the photovoltaic reactive powers of the photovoltaic node i at times t and t - 1 respectively, and are the Lagrangian operators of the photovoltaic node i at times t + 1, t, and t - 1 respectively μ i,t+1 , μ i,t and μ i,t-1 are the Lagrangian operators of the photovoltaic node i at times t + 1, t, and t - 1 respectively μ , v i,t and v i,t-1 are the voltages of the photovoltaic - energy - storage node at times t and t - 1 respectively, and are the Lagrangian operators of the photovoltaic node i at times t + 1, t, and t - 1 respectively q i,min is the maximum reactive power absorbed by the photovoltaic node i, q i,max is the maximum reactive power of the photovoltaic node i, v i,min is the voltage upper limit of the photovoltaic node i, v i,min is the voltage lower limit of the photovoltaic node i.

[0069] Among them, the matrix is a sparse matrix, and the value of each element is only related to the reactance between nodes i and j; Calculate the reactive power output injected by the photovoltaic inverter into the distribution network:

[0070]

[0071] Wherein, q i，t+1 represents the reactive power injected by the photovoltaic inverter into the photovoltaic node i at the moment t+1, is a matrix related only to the photovoltaic nodes i and j element, N(i) is the set of photovoltaic nodes of the photovoltaic node i, is the voltage value of the photovoltaic node j before control, λ j,t+1 is the Lagrangian operator of the photovoltaic node j at the moment t+1 λ , is the Lagrangian operator of the photovoltaic node j at the moment t+1 μ j,t+1 is the Lagrangian operator of the photovoltaic node j at the moment t+1 μ , is the Lagrangian operator of the photovoltaic node j at the moment t+1.

[0072] In a second aspect, an embodiment of the present invention provides a voltage optimization control device for a distribution network in which distributed photovoltaics participate in regulation, and the device includes:

[0073] An acquisition module, configured to acquire distribution network data including distributed photovoltaics;

[0074] A processing module, configured to linearly process the power flow model of the distribution network according to the distribution network data to obtain a linear power flow model of the distribution network; considering the voltage control of the photovoltaic nodes equipped with photovoltaic inverters, determine the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter;

[0075] A model establishment module, configured to determine an objective function and constraint conditions for distribution network voltage optimization based on the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter, with the minimum deviation of the photovoltaic node voltage as the optimization goal, and establish a distribution network voltage optimization control model;

[0076] A voltage regulation module, configured to solve the distribution network voltage optimization control model based on the accelerated dual ascent algorithm, obtain the reactive power output of the photovoltaic inverter, and send a reactive power scheduling instruction to the photovoltaic inverter controller to adjust the voltage of the photovoltaic node through the reactive power generated by the photovoltaic inverter.

[0077] In a third aspect, the present invention further provides an electronic device, including a memory and a processor, wherein,

[0078] The memory is used to store programs;

[0079] The processor, coupled to the memory, is configured to execute the program stored in the memory to implement the steps in the method for optimizing the control of the distribution network voltage with distributed photovoltaic participation in regulation according to the embodiment of the first aspect of the present invention.

[0080] In a fourth aspect, the present invention further provides a computer-readable storage medium for storing computer-readable programs or instructions, which, when executed by a processor, can implement the steps in the method for optimizing the control of the distribution network voltage with distributed photovoltaic participation in regulation according to the embodiment of the first aspect of the present invention.

[0081] The beneficial effects of adopting the above embodiments are as follows:

[0082] Due to the limited and low-quality communication infrastructure in the current distribution network, which is not applicable to the high-penetration photovoltaic distribution network, the present invention proposes a method and device for optimizing the control of the distribution network voltage with distributed photovoltaic participation in regulation in order to coordinate the active and reactive power output of the photovoltaic. In distributed control, compared with local and centralized control, only communication between photovoltaic inverters is required to achieve the global goal, with less investment cost.

[0083] The existing distributed algorithms have a relatively slow convergence speed. To improve the convergence speed, the present invention is based on the accelerated dual ascent algorithm, uses the photovoltaic node voltage and photovoltaic reactive power of the previous two moments to update the Lagrange multiplier, and then exchanges the Lagrange multiplier information with adjacent photovoltaic inverters to calculate the reactive power output at the current moment; in the present invention, the photovoltaic inverter only needs to exchange data with adjacent photovoltaic inverters to achieve distributed online calculation of reactive power, with a fast convergence speed, realizing fast and accurate control of the distribution network voltage. Description of the Drawings

[0084] Figure 1 It is a flowchart of the method for optimizing the control of the distribution network voltage with distributed photovoltaic participation in regulation provided by the embodiment of the present invention;

[0085] Figure 2 It is a model of a distribution network with high-penetration photovoltaic provided by the embodiment of the present invention;

[0086] Figure 3 It is a topological diagram of the 123-node IEEE distribution network with high-penetration photovoltaic provided by the embodiment of the present invention;

[0087] Figure 4 It is a schematic diagram of the principle of the accelerated dual ascent algorithm provided by the embodiment of the present invention;

[0088] Figure 5 It is a curve diagram of the active power of the photovoltaic provided by the embodiment of the present invention;

[0089] Figure 6 It is a curve diagram of the active power of the load provided by the embodiment of the present invention;

[0090] Figure 7 The curve graph of the photovoltaic node voltage change without control provided by the embodiment of the present invention;

[0091] Figure 8 The curve graph of the distribution network voltage control based on local control, centralized control and accelerated dual ascent algorithm provided by the embodiment of the present invention;

[0092] Figure 9 The curve graph of the photovoltaic reactive power output based on local control, centralized control and accelerated dual ascent algorithm provided by the embodiment of the present invention.

[0093] Figure 10 The structural block diagram of the distribution network voltage optimization control device in which distributed photovoltaics participate in regulation provided by the embodiment of the present invention;

[0094] Figure 11 The structural schematic diagram of the electronic device provided by the embodiment of the present invention. Detailed implementation manners

[0095] The following will specifically describe the preferred embodiments of the present invention with reference to the accompanying drawings. The accompanying drawings form a part of this application and are used together with the embodiments of the present invention to explain the principle of the present invention, rather than to limit the scope of the present invention.

[0096] Referring to "embodiments" in this article means that the specific features, structures or characteristics described in combination with the embodiments may be included in at least one embodiment of this application. The appearance of this phrase in various positions in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0097] Currently, the voltage regulation methods of photovoltaic inverters mainly include local control, centralized control and distributed control. In local control, the photovoltaic adjusts the reactive power injection only depending on the local voltage measurement value, without a centralized controller, and the control speed is relatively fast, but it may not be able to ensure a feasible voltage. A large number of studies have been carried out on the centralized voltage control of the distribution network, solving the power flow problem based on all system information, and its calculation burden is too heavy. At the same time, due to the limited and low-quality communication infrastructure in the current distribution network, it is not applicable to the high-penetration photovoltaic distribution network.

[0098] In view of this, in order to coordinate the active and reactive power output of photovoltaic power, the present invention proposes a method and device for optimizing the voltage control of a distribution network with distributed photovoltaic power participating in regulation. Compared with local and centralized control, in distributed control, the photovoltaic inverter only needs to exchange data with adjacent photovoltaic inverters to realize distributed online calculation of reactive power, with a fast convergence speed, achieving fast and accurate control of the distribution network voltage. The following will be elaborated and introduced through multiple embodiments.

[0099] Figure 1 It is a flowchart of the method for optimizing the voltage control of a distribution network with distributed photovoltaic power participating in regulation provided by the present invention. As Figure 1 shown, the method for optimizing the voltage control of a distribution network with distributed photovoltaic power participating in regulation includes:

[0100] Step S1, obtaining the data of the distribution network with distributed photovoltaic power.

[0101] Specifically, in this embodiment, the data of the distribution network with high-penetration distributed photovoltaic power is obtained, where the distribution network data at least includes: the voltage measurement data and reactive power data of each photovoltaic node at the previous two moments, the upper and lower limits of the reactive power of the photovoltaic inverter, and the upper and lower limit constraints of the voltage of each photovoltaic node.

[0102] Step S2, linearly processing the power flow model of the distribution network according to the distribution network data to obtain a linear power flow model of the distribution network; considering the voltage control of the photovoltaic nodes equipped with photovoltaic inverters, determining the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter.

[0103] Figure 2 It is a distribution network model with high-penetration photovoltaic power provided by the present invention. Figure 3 It is a topological diagram of the 123-node IEEE distribution network with high-penetration photovoltaic power in the embodiment of the present invention. Figure 2 Among them, Grid refers to the distribution grid, HV / MV substation refers to the high-voltage / medium-voltage substation, Load is the load, and PV refers to photovoltaic. Referring to Figure 2 and Figure 3 , a radial distribution network can be simulated using a tree diagram T = {N, E}. N = {0, 1,..., n} represents the node set. The index of the substation node is n = 0, which is a balanced node. We model the remaining nodes as PQ nodes, mainly including photovoltaic nodes and load nodes. The PQ nodes output the given active power and reactive power and solve for the voltage amplitude of the nodes. P = {1, 2,..., n} represents the PQ nodes. E = {e j = (i, j)|i = p(j), j ∈ N} represents the distribution line, and p(j) represents the node jThe parent node of, that is, the node immediately preceding node j. For each node, let v i be its voltage magnitude, p i be its active power, and q i be its reactive power. For each distribution line segment (i, j) ∈ E, let r ij and x ij be its resistance and reactance, and P ij and Q ij be the active and reactive powers flowing from node i into node j. N j represents the set of buses located after bus j along the radial network. In this embodiment, distributed photovoltaics are connected to each node of the distribution network, and a photovoltaic node refers to the node where the distributed photovoltaics are located in the distribution network.

[0104] In step S2, the expression of the distribution network power flow model is:

[0105]

[0106] where P ij , Q ij represent the active and reactive powers flowing from node i into node j, p j , q j are the active and reactive powers output by node j, V i is the voltage value of node i, r ij , x ij are the line resistance and line reactance between node i and node j.

[0107] In step S2, the power flow model of the distribution network is linearized to obtain the linear power flow model of the distribution network, including: For the convenience of analysis, ignoring the active and reactive line losses, assuming that the voltage of each node is close to the reference voltage, and the angle difference between adjacent photovoltaic nodes is very small, the power flow model of the distribution network is linearized as follows:

[0108]

[0109] V i - V j = r ij P ij + x ij Q ij (6)

[0110] The linear power flow model of the distribution network can be expressed in the following form:

[0111] v = 1 + Rp + Xq (7)

[0112] Among them, \(v\) represents a column vector composed of node voltages, \(p\) represents a column vector composed of node active power injections, \(q\) represents a column vector composed of node reactive power injections, \(R\) is a resistance matrix, and \(X\) is a reactance matrix;

[0113] In the above formula, \(1\) is a unit column vector, and \(R\) and \(X\) are expressed in the following forms:

[0114]

[0115] In the above formula, \(L\) i(j) represents the path from node \(0\) to node \(i(j)\); each element of \(R\) and \(X\) is only related to the network topology and line impedance.

[0116] In step S2, considering the voltage control of photovoltaic nodes equipped with photovoltaic inverters, determine the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter, including:

[0117] Assume that only the photovoltaic node voltage is measured through the photovoltaic inverter and the reactive power injected into the distribution network is adjusted, considering the voltage control of photovoltaic nodes equipped with photovoltaic inverters; the present invention only considers the voltage control of a subset of nodes equipped with photovoltaic inverters. In the present invention, the photovoltaic node set is defined as \(M(|M| = m)\), and the load node set is defined as \(U(|U| = n - m)\). To distinguish the voltage of photovoltaic nodes and the voltage of load nodes, the node voltage amplitude vector is decomposed as follows:

[0118]

[0119] In the above formula, \(v\) G is the voltage amplitude of the photovoltaic node, and \(v\) L is the voltage amplitude of the load node; the resistance matrix \(R\) and the reactance matrix \(X\) are decomposed as follows:

[0120]

[0121] Substitute equations (10), (11) and (12) into equation (7) to obtain the voltage amplitude of the photovoltaic node:

[0122] \(v\) G = 1 + \(R\) GG \(p\) G + \(R\) GL \(p\) L + \(X\) GG \(q\) G + \(X\) GL \(q\) L (13)

[0123] In the formula, \(p\) G and \(q\) G represent the active power and reactive power injected by the photovoltaic node into the distribution network, and \(p\) L and \(q\) LIndicates the active power and reactive power of load injection; R GG Is the sensitivity matrix of the photovoltaic node voltage to the active power fluctuation of the photovoltaic, R GL Is the sensitivity matrix of the photovoltaic node voltage to the active power fluctuation of the load, X GG Is the sensitivity matrix of the photovoltaic node voltage to the reactive power fluctuation of the photovoltaic, X GL Is the sensitivity matrix of the photovoltaic node voltage to the reactive power fluctuation of the load;

[0124] Assume p G 、p L 、q L Are constants, and the voltage of the photovoltaic node is adjusted only by the reactive power generated by the photovoltaic inverter. Then, Equation (13) is simplified to obtain the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter as:

[0125]

[0126] In the formula, Is the voltage curve of the photovoltaic node without recovery power compensation.

[0127] Step S3, based on the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter, with the minimum deviation of the photovoltaic node voltage as the optimization goal, determine the objective function and constraint conditions for the distribution network voltage optimization, and establish a distribution network voltage optimization control model.

[0128] Specifically, after determining the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter, that is, Equation (14), based on Equation (14), with the minimum deviation of the photovoltaic node voltage as the optimization goal, the objective function of the distribution network voltage optimization model is established as:

[0129]

[0130] In the formula, minF(q G ) indicates that the optimization goal is to minimize the deviation of the node voltage from the rated voltage value;

[0131] The constraint conditions of the distribution network voltage optimization control model include the distribution network power flow constraint, the photovoltaic node voltage constraint, and the reactive power output constraint of the photovoltaic inverter. The power flow constraint of the distribution network is considered in the linear power flow model of the distribution network. Therefore, only the voltage constraint and the reactive power constraint need to be listed in the distribution network voltage optimization control model of the present invention.

[0132] The voltage constraint expression of the photovoltaic node is:

[0133] v min ≤v G ≤v max (17)

[0134] In the above formula, vmin and v max are the upper and lower limits of the voltage at the node where the distributed PV is located, respectively;

[0135] The reactive power constraint expression of the PV inverter is:

[0136] q min ≤q G ≤q max (18)

[0137] In the above formula, q min and q max are the upper and lower limits of the PV reactive power output, respectively;

[0138] Equations (16), (17) and (18) constitute the distribution network voltage optimization control model.

[0139] Step S4, based on the accelerated dual ascent algorithm, solve the distribution network voltage optimization control model to obtain the reactive power output of the PV inverter, and send the reactive power scheduling instruction to the PV inverter controller, and adjust the voltage of the PV node through the reactive power generated by the PV inverter.

[0140] Figure 4 is the schematic diagram of the accelerated dual ascent algorithm provided by the embodiment of the present invention. The accelerated dual ascent algorithm can be used to solve (16)-(18), which is a quadratic programming problem with box constraints. This is a distributed online algorithm, which provides a generalized solution to the constrained optimization problem. Specifically, we use the accelerated projected gradient algorithm to solve the dual problem, and the optimal solution of the primal problem can be obtained from the dual optimal. It has a faster convergence speed compared with the traditional dual ascent method, and can be implemented distributively, thus reducing the complexity of the communication network.

[0141] Based on the distribution network voltage optimization control model constituted by equations (16), (17) and (18), construct the Lagrangian function as follows:

[0142]

[0143] In the above formula, the vector λ , μ , are the Lagrange multipliers related to the inequality constraints q min ≤q G , q G ≤q max , v min ≤v G , v G ≤v max Define the vector a as containing all the Lagrange multipliers,

[0144]

[0145] Solve for the optimal control variables of the Lagrangian function:

[0146]

[0147] Substitute q in Equation (17) G into Equation (16) to obtain the Lagrangian dual function:

[0148]

[0149] In the above equation, B is the coefficient matrix and b is the coefficient vector, and the expressions are:

[0150]

[0151] Update the dual variables using the accelerated projected gradient method:

[0152]

[0153] In the above equation, is the acceleration variable obtained by the linear combination of the two most recent moments of the dual variables:

[0154] c t+1 = a t + β t+1 (a t - a t-1 ) (25)

[0155] In the above equation, the expression of β t+1 is:

[0156]

[0157] In the above equation, the iterative expression of θ t+1 is:

[0158]

[0159] The local update form of the Lagrangian operator is expressed as follows:

[0160]

[0161] In the equation, λ i,t+1 , λ i,t and λ i,t-1 are the Lagrangian operators of the photovoltaic node i at times t+1, t, and t-1 respectively λ , q i,t and q i,t-1are the PV reactive powers of PV node i at time t and t - 1 respectively, and are the Lagrange multipliers of PV node i at times t + 1, t, and t - 1 respectively μ i,t+1 、 μ i,t and μ i,t-1 are the Lagrange multipliers of PV node i at times t + 1, t, and t - 1 respectively μ , v i,t and v i,t-1 are the voltages of the PV - storage node at times t and t - 1 respectively, and are the Lagrange multipliers of PV node i at times t + 1, t, and t - 1 respectively q i,min is the maximum reactive power absorbed by PV node i, q i,max is the maximum reactive power of PV node i, v i,min is the upper voltage limit of PV node i, v i,min is the lower voltage limit of PV node i.

[0162] Among them, the matrix is a sparse matrix, and the value of each element is only related to the reactance between nodes i and j; calculate the reactive power output injected by the PV inverter into the distribution network:

[0163]

[0164] In the formula, q i，t+1 represents the reactive power injected by the PV inverter into PV node i at time t + 1, is the matrix element only related to PV nodes i and j , N(i) is the set of PV nodes of PV node i, is the voltage value of PV node j before control, λ j,t+1 is the Lagrange multiplier of PV node j at time t + 1 λ , is the Lagrange multiplier of PV node j at time t + 1 μ j,t+1 is the Lagrange multiplier of PV node j at time t + 1 μ , is the Lagrange multiplier of PV node j at time t + 1.

[0165] Figure 5 is the PV active power curve diagram provided by the embodiment of the present invention; asFigure 5 As shown, the IEEE123 bus feeder with a relatively high photovoltaic penetration rate is used to numerically evaluate the proposed voltage optimization control method for a distribution network with distributed photovoltaic participation in regulation. Among them, the rated voltage value is 4.16 kV, and the acceptable range is set to ±5% of the rated value; in addition, the capacity of the photovoltaic inverter is set to 720 kVA, and the reactive power limit is set to 200 kVA; the total time span is 24 hours, and the time resolution is 15 minutes. Figure 6 This is the active power curve graph of the load provided by the embodiment of the present invention; Figure 7 This is the curve graph of the voltage change of the photovoltaic node without control provided by the embodiment of the present invention.

[0166] Figure 8 This is the voltage curve graph of the distribution network voltage control based on local control (local control), centralized control, and accelerated dual ascent algorithm provided by the embodiment of the present invention. It can be seen from Figure 8 that when the load is very small and the power generation of the photovoltaic inverter is very large, the highest voltage of some nodes reaches 1.08 p.u. When the distribution bus supplies power to a large load, the photovoltaic power generation cannot be used at this time, and the lowest voltage is lower than the allowable voltage value. Due to its stability and optimality problems, local control performs poorly in eliminating overvoltage violations. Both centralized voltage control and voltage control based on the accelerated dual ascent algorithm can improve the voltage. The voltage control based on the accelerated dual ascent algorithm even has a better effect than the centralized strategy. At the same time, the voltage control based on the accelerated dual ascent algorithm has a faster response speed for regulating voltage fluctuations.

[0167] Figure 9 This is the reactive power curve graph of the photovoltaic node of the voltage control based on local control, centralized control, and accelerated dual ascent algorithm provided by the embodiment of the present invention. Referring to Figure 8 and Figure 9 , when the node voltage exceeds the upper limit, the reactive power absorbed by the photovoltaic inverter reaches the lower limit of reactive power; when the node voltage exceeds the lower limit between 18-20h, the reactive power compensation supported by the photovoltaic inverter reaches the upper limit of reactive power.

[0168] It can be understood that due to the limited and low-quality communication infrastructure in the current distribution network, it is not applicable to the high-penetration photovoltaic distribution network. In order to coordinate the active and reactive power output of the photovoltaic, the present invention proposes a voltage optimization control method and device for a distribution network with distributed photovoltaic participation in regulation. Compared with local and centralized control, in distributed control, only communication between photovoltaic inverters is required to achieve the global goal, with less investment cost.

[0169] The existing distributed algorithms have a relatively slow convergence rate. To improve the convergence rate, the present invention is based on the accelerated dual ascent algorithm, uses the photovoltaic node voltages and photovoltaic reactive powers at the previous two moments to update the Lagrange multipliers, and then exchanges the Lagrange multiplier information with adjacent photovoltaic inverters to calculate the reactive power output at the current moment. In the present invention, the photovoltaic inverter only needs to exchange data with adjacent photovoltaic inverters to achieve distributed online calculation of reactive power, with a fast convergence rate, and realizes fast and accurate control of the distribution network voltage.

[0170] Figure 10 It is a structural block diagram of a distribution network voltage optimization control device in which distributed photovoltaics participate in regulation. Referring to Figure 10 Figure, the distribution network voltage optimization control device 1000 in which distributed photovoltaics participate in regulation includes:

[0171] An acquisition module 1001, configured to acquire distribution network data containing distributed photovoltaics;

[0172] A processing module 1002, configured to linearly process the power flow model of the distribution network according to the distribution network data to obtain a linear power flow model of the distribution network; considering the voltage control of photovoltaic nodes equipped with photovoltaic inverters, determine the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter;

[0173] A model establishment module 1003, configured to determine the objective function and constraint conditions for distribution network voltage optimization based on the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter, with the minimum deviation of the photovoltaic node voltage as the optimization goal, and establish a distribution network voltage optimization control model;

[0174] A voltage regulation module 1004, configured to solve the distribution network voltage optimization control model based on the accelerated dual ascent algorithm, obtain the reactive power output of the photovoltaic inverter, and send a reactive power scheduling instruction to the photovoltaic inverter controller to adjust the voltage of the photovoltaic node through the reactive power generated by the photovoltaic inverter.

[0175] The distribution network voltage optimization control device provided by the present invention uses the above modules to optimize and control the distribution network voltage. Since the distribution network voltage optimization control method in which distributed photovoltaics participate in regulation has been described in detail in the above method embodiments, this embodiment will not be elaborated here.

[0176] Figure 11 It is a structural block diagram of an electronic device provided by the present invention, as shown in Figure 11As shown in the figure, the present invention also provides an electronic device. The electronic device 1100 may be a computing device such as a mobile terminal, a desktop computer, a notebook, a palm computer, and a server. The electronic device 1100 includes a processor 1101 and a memory 1102. Among them, a distributed photovoltaic participation-regulated distribution network voltage optimization control program 1103 is stored on the memory 1102.

[0177] In some embodiments, the memory 1102 may be an internal storage unit of the computer device, such as the hard disk or memory of the computer device. In other embodiments, the memory 1102 may also be an external storage device of the computer device, such as a plug-in hard disk equipped on the computer device, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. Further, the memory 1102 may also include both the internal storage unit and the external storage device of the computer device. The memory 1102 is used to store the application software installed on the computer device and various types of data, such as the program code installed on the computer device. The memory 1102 may also be used to temporarily store the data that has been output or will be output. In one embodiment, when the distributed photovoltaic participation-regulated distribution network voltage optimization control program 1103 is executed by the processor 1101, the following steps are implemented:

[0178] Step S1: Obtain the distribution network data containing distributed photovoltaics;

[0179] Step S2: Linearize the power flow model of the distribution network according to the distribution network data to obtain a linear power flow model of the distribution network; consider the photovoltaic node voltage control equipped with a photovoltaic inverter, and determine the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter;

[0180] Step S3: Based on the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter, with the minimum photovoltaic node voltage deviation as the optimization goal, determine the objective function and constraints of the distribution network voltage optimization, and establish a distribution network voltage optimization control model;

[0181] Step S4: Based on the accelerated dual ascent algorithm, solve the distribution network voltage optimization control model to obtain the reactive power output of the photovoltaic inverter, and send the reactive power scheduling instruction to the photovoltaic inverter controller to adjust the voltage of the photovoltaic node through the reactive power generated by the photovoltaic inverter.

[0182] In some embodiments, the processor 1101 may be a central processing unit (CPU), a microprocessor, or other data processing chips, which is used to run the program code stored in the memory 1102 or process data, such as executing the voltage optimization control program for a distribution network with distributed photovoltaics participating in regulation, etc.

[0183] This embodiment also provides a computer-readable storage medium, on which a voltage optimization control program for a distribution network with distributed photovoltaics participating in regulation is stored. When the voltage optimization control program for a distribution network with distributed photovoltaics participating in regulation is executed by a processor, the following steps are implemented:

[0184] Step S1: Obtain the distribution network data containing distributed photovoltaics;

[0185] Step S2: Linearize the power flow model of the distribution network according to the distribution network data to obtain a linear power flow model of the distribution network; consider the voltage control of photovoltaic nodes equipped with photovoltaic inverters, and determine the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter;

[0186] Step S3: Based on the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter, with the minimum photovoltaic node voltage deviation as the optimization objective, determine the objective function and constraint conditions for the distribution network voltage optimization, and establish a distribution network voltage optimization control model;

[0187] Step S4: Based on the accelerated dual ascent algorithm, solve the distribution network voltage optimization control model to obtain the reactive power output of the photovoltaic inverter, and send the reactive power scheduling instruction to the photovoltaic inverter controller, and adjust the voltage of the photovoltaic node through the reactive power generated by the photovoltaic inverter.

[0188] The above-described embodiments merely represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the present invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention patent should be subject to the appended claims.

[0189] 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 has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for optimizing the voltage control of a distribution network with distributed photovoltaics participating in regulation, characterized in that, Including: Step S1: Obtain the distribution network data containing distributed photovoltaic power. Step S2: Linearize the power flow model of the distribution network according to the distribution network data to obtain a linear power flow model of the distribution network; considering the voltage control of photovoltaic nodes equipped with photovoltaic inverters, determine the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter. Step S3: Based on the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter, with the minimum photovoltaic node voltage deviation as the optimization goal, determine the objective function and constraint conditions for distribution network voltage optimization, and establish a distribution network voltage optimization control model. Step S4: Based on the accelerated dual ascent algorithm, solve the distribution network voltage optimization control model to obtain the reactive power output of the photovoltaic inverter, and send the reactive power scheduling instruction to the photovoltaic inverter controller to adjust the voltage of the photovoltaic node through the reactive power generated by the photovoltaic inverter. In step S4, the process of solving the distribution network voltage optimization control model based on the accelerated dual ascent algorithm to obtain the reactive power output of the photovoltaic inverter includes: Based on the distribution network voltage optimization control model, construct the Lagrangian function as follows: In the above formula, X GG is the sensitivity matrix of the PV node voltage to the PV reactive power fluctuation, q G represents the reactive power injected by the PV node into the distribution network, and the vectors λ, μ, are the Lagrange multipliers related to the inequality constraints q min ≤q G , q G ≤q max , v min ≤v G , v G ≤v max Define the vector a as containing all the Lagrange multipliers, The superscript T represents the transpose of the vector; is the voltage curve of the PV node without restoration power compensation, v min and v max are the upper and lower limits of the voltage of the node where the distributed PV is located respectively; q min and q max are the upper and lower limits of the reactive power output of the distributed PV respectively; Solve the optimal control variables of the Lagrangian function: Substitute \(q\) in Equation (20) G into Equation (19) to obtain the Lagrangian dual function: In the above formula, B is the coefficient matrix, b is the coefficient vector, and the expressions are: Use the accelerated projection gradient method to update the dual variables: In the above formula, a t+1 is the dual variable at time t + 1, is the acceleration variable obtained by the linear combination of the dual variables at the two most recent times, α is the step size of the accelerated projected gradient method, is the derivative of the function g(c t+1 ) with respect to the vector c t+1 , and [] + denotes the projection onto the feasible region with non - negative constraints; c t+1 = a t + β t+1 (a t - a t-1 ) (25) In the above formula, β t+1 has the following expression: In the above formula, θ t+1 The iterative expression is: where β t and β t+1 are the auxiliary variables β at times t and t + 1 respectively, and θ t and θ t+1 are the auxiliary variables θ at times t and t + 1 respectively; The local update form of the Lagrangian operator is expressed as follows: Wherein, λ i,t+1 、 λ i,t and λ i,t-1 are the Lagrangian operators of the photovoltaic node i at times t+1, t, and t-1 respectively λ , q i,t and q i,t-1 are the photovoltaic reactive powers of the photovoltaic node i at times t and t-1 respectively, and are the Lagrangian operators of the photovoltaic node i at times t+1, t, and t-1 respectively μ i,t+1 , μ i,t and μ i,t-1 are the Lagrangian operator μ of the photovoltaic node i at times t+1, t, and t-1 respectively, v i,t and v i,t-1 are the voltages of the photovoltaic and energy storage node at times t and t-1 respectively, and are the Lagrangian operators of the photovoltaic node i at times t+1, t, and t-1 respectively q i,min is the maximum reactive power absorption of the photovoltaic node i, q i,max is the maximum reactive power of the photovoltaic node i, v i,min is the upper voltage limit of the photovoltaic node i, v i,min is the lower voltage limit of the photovoltaic node i; Matrix is a sparse matrix, and the value of each element is only related to the reactance between nodes i and j; calculate the reactive power output injected by the PV inverter into the distribution network: where q i，t+1 represents the reactive power injected by the PV inverter into the PV node i at the moment t+1, is a matrix related only to the PV nodes i and j element, N(i) is the set of PV nodes of the PV node i, is the voltage value of the PV node j before control, λ j,t+1 is the Lagrange operator of the PV node j at the moment t+1 λ , is the Lagrange operator of the PV node j at the moment t+1 μ j,t+1 is the Lagrange operator of the PV node j at the moment t+1 μ , is the Lagrange operator of the PV node j at the moment t+1.

2. The voltage optimization control method for a distribution network with distributed PV participating in regulation according to claim 1, characterized in that, The distribution network data includes the voltage measurement data and reactive power data of each photovoltaic node at the previous two moments, the upper and lower limits of the reactive power of the photovoltaic inverter, and the upper and lower limit constraints of the voltage of each photovoltaic node.

3. The voltage optimization control method for a distribution network with distributed photovoltaics participating in regulation according to claim 1, characterized in that, In step S2, the expression of the distribution network power flow model is: Wherein, P ij , Q ij represent the active and reactive power flowing from node i to node j, p j , q j are the active and reactive power output by node j, V i is the voltage value of node i, r ij , x ij are the line resistance and line reactance between node i and node j.

4. The method for optimizing and controlling the voltage of a distribution network with distributed photovoltaics participating in regulation according to claim 3, characterized in that, In step S2, the process of linearizing the power flow model of the distribution network to obtain a linear power flow model of the distribution network specifically includes: Ignoring the active and reactive line losses and assuming that the voltage of each photovoltaic node is close to the reference voltage, the power flow model of the distribution network is linearized as follows: V i -V j = r ij P ij + x ij Q ij (6) The linear power flow model of the distribution network can be expressed in the following form: v = 1 + Rp + Xq (7) Where, v represents the column vector composed of node voltages, p represents the column vector composed of node active power injections, q represents the column vector composed of node reactive power injections, R is the resistance matrix, and X is the reactance matrix; In the above formula, 1 is the unit column vector, and R and X are expressed in the following form: In the above formula, L i(j) represents the path from node 0 to node i(j); each element of R and X is only related to the network topology and line impedance.

5. The voltage optimization control method for a distribution network with distributed photovoltaics participating in regulation according to claim 4, wherein In step S2, considering the voltage control of photovoltaic nodes equipped with photovoltaic inverters, determining the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter includes: Assume that only the photovoltaic node voltage is measured by the photovoltaic inverter and the reactive power injected into the distribution network is adjusted, considering the voltage control of photovoltaic nodes equipped with photovoltaic inverters; in order to distinguish the voltage of photovoltaic nodes from that of load nodes, the node voltage amplitude vector is decomposed as follows: In the above formula, v G is the voltage magnitude of the photovoltaic node, and v L is the voltage magnitude of the load node; the resistance matrix R and the reactance matrix X are decomposed as follows: Substitute equations (10), (11) and (12) into equation (7) to obtain the voltage amplitude of the photovoltaic node: v G = 1 + R GG p G + R GL p L + X GG q G + X GL q L (13) where p G , q G represent the active power and reactive power injected by the photovoltaic nodes into the distribution network, and p L , q L represent the active power and reactive power injected by the load; R GG is the sensitivity matrix of the photovoltaic node voltage to the photovoltaic active power fluctuation, and R GL is the sensitivity matrix of the photovoltaic node voltage to the load active power fluctuation, X GG is the sensitivity matrix of the photovoltaic node voltage to the photovoltaic reactive power fluctuation, and X GL is the sensitivity matrix of the photovoltaic node voltage to the load reactive power fluctuation; Assume p G 、p L 、q L are constants. If the voltage of the photovoltaic node is regulated only by the reactive power generated by the photovoltaic inverter, then Equation (13) is simplified to obtain the relationship between the voltage of the photovoltaic node and the reactive power of the photovoltaic inverter as follows:

6. The method for optimizing the voltage control of a distribution network with distributed photovoltaics participating in regulation according to claim 5, wherein In step S3, based on the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter, with the minimum photovoltaic node voltage deviation as the optimization goal, determining the objective function and constraint conditions for distribution network voltage optimization, and establishing a distribution network voltage optimization control model specifically includes: Based on Equation (14), the objective function of the distribution network voltage optimization model is established as follows: where minF(q G ) represents the optimization objective of minimizing the deviation of the node voltage from the rated voltage value; The voltage constraint of the node where the distributed photovoltaic is located is: v min ≤ v G ≤ v max (17) The reactive power constraint of the distributed photovoltaic is: q min ≤q G ≤q max (18) Equations (16), (17) and (18) constitute the distribution network voltage optimization control model.

7. A distribution network voltage optimization control device for the distribution network voltage optimization control method in which the distributed photovoltaics described in any one of claims 1-6 participate in regulation, characterized in that, Including: An acquisition module, configured to acquire the distribution network data containing distributed photovoltaics; A processing module, configured to linearize the power flow model of the distribution network according to the distribution network data to obtain a linear power flow model of the distribution network; considering the voltage control of the photovoltaic nodes equipped with photovoltaic inverters, determine the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter; A model establishment module, configured to determine the objective function and constraint conditions of the distribution network voltage optimization based on the relationship between the photovoltaic node voltage and the reactive power of the photovoltaic inverter, with the minimum deviation of the photovoltaic node voltage as the optimization objective, and establish a distribution network voltage optimization control model; A voltage regulation module, configured to solve the distribution network voltage optimization control model based on the accelerated dual ascent algorithm to obtain the reactive power output of the photovoltaic inverter, and send a reactive power scheduling instruction to the photovoltaic inverter controller to regulate the voltage of the photovoltaic node through the reactive power generated by the photovoltaic inverter.

8. An electronic device, characterized in that, Including a memory and a processor, wherein, The memory is configured to store programs; The processor is coupled to the memory and is configured to execute the program stored in the memory to implement the steps in the distribution network voltage optimization control method for distributed photovoltaic participation in regulation according to any one of the above claims 1 to 6.

9. A computer-readable storage medium, characterized in that, For storing computer-readable programs or instructions, the programs or instructions can implement the steps in the distribution network voltage optimization control method for distributed photovoltaic participation in regulation according to any one of the above claims 1 to 6 when executed by a processor.

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