Method and device for determining distributed photovoltaic openable capacity of power distribution network

Abstract

The invention provides a method and device for determining distributed photovoltaic openable capacity of a power distribution network, and belongs to the field of power distribution networks. The method comprises the following steps: acquiring operation data of a target power distribution network and distributed photovoltaic planning distribution data; determining distributed photovoltaic planning distribution characteristics; establishing a target function by taking the maximum distributed photovoltaic openable capacity in the target power distribution network as a target; establishing a distributed photovoltaic planning distribution characteristic constraint of the target function according to the planning distribution characteristic and the planning distribution data, and establishing an operation constraint of the target function according to the operation data; and obtaining a distributed photovoltaic openable capacity scheme of the target power distribution network based on the planning distribution characteristic constraint, the operation constraint and the target function. According to the invention, the accuracy of determining the distributed photovoltaic openable capacity of the power distribution network can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network, and in particular to a method and device for determining the openable capacity of distributed photovoltaic power generation in a distribution network. Background Art

[0002] Distributed photovoltaic access to the distribution network is an important way to reduce emissions from the power system. Distributed photovoltaics have the advantages of being close to users, serving as backup for traditional power grids, and improving the safety of power grid operation. However, after large-scale distributed photovoltaics are connected to the distribution network, they also have many negative impacts on the power grid, such as: node voltage exceeding the limit, voltage fluctuation, line power reverse overload, power supply reliability reduction, and short-circuit current exceeding the standard. These factors limit the further access of distributed photovoltaics to the distribution network. Therefore, it is necessary to accurately and objectively determine the distributed photovoltaic capacity that the distribution network can absorb.

[0003] Here, the distributed photovoltaic available capacity (PV available capacity, PAC) of the distribution network refers to the maximum distributed photovoltaic capacity that can be newly connected to the distribution network based on the existing load and photovoltaic distribution while meeting the system's safe operation requirements.

[0004] In the related art, the method for determining the open capacity of distributed photovoltaics is relatively simple, which mainly calculates the maximum open capacity of distributed photovoltaics in the distribution network by considering the operation of the distribution network. However, the accuracy of the open capacity of distributed photovoltaics calculated in this way is not high. Summary of the invention

[0005] The embodiments of the present invention provide a method and device for determining the openable capacity of distributed photovoltaic power generation in a distribution network, so as to improve the accuracy of the openable capacity of distributed photovoltaic power generation in the distribution network.

[0006] In a first aspect, an embodiment of the present invention provides a method for determining the openable capacity of distributed photovoltaic power generation in a distribution network, comprising:

[0007] Obtain the operating data of the target distribution network and the planning and distribution data of distributed photovoltaics;

[0008] Determining the planning distribution characteristics of the distributed photovoltaics;

[0009] Establishing an objective function with the goal of maximizing the open capacity of distributed photovoltaics in the target distribution network;

[0010] Establishing a planning distribution characteristic constraint of distributed photovoltaics of the objective function according to the planning distribution characteristic and the planning distribution data, and establishing an operation constraint of the objective function according to the operation data;

[0011] Based on the objective function, the planning distribution characteristic constraint and the operation constraint, an openable capacity plan of distributed photovoltaics of the target distribution network is obtained.

[0012] In a possible implementation, the planning distribution characteristics include quantity distribution, location distribution and dispersion;

[0013] Determining the planning distribution characteristics of the distributed photovoltaic system, including:

[0014] Establishing a quantity distribution model of the distributed photovoltaic system according to the planned number of nodes of the distributed photovoltaic system and the number of accessible nodes in the target distribution network that can be connected to the distributed photovoltaic system;

[0015] Establishing a location distribution model of the distributed photovoltaic system according to the planned installation nodes of the distributed photovoltaic system and the distances between the distributed photovoltaic system and the source nodes of the target power distribution network;

[0016] A dispersion model of the distributed photovoltaic is established according to the planned access capacity of the distributed photovoltaic.

[0017] In a possible implementation, based on the objective function, the planning distribution characteristic constraint and the operation constraint, obtaining an openable capacity solution of distributed photovoltaics of the target distribution network includes:

[0018] Performing a linear transformation on the operation constraint to obtain a transformed linear operation constraint;

[0019] Using auxiliary variables, transforming the absolute value parameters in the planning distribution characteristic constraint to obtain a transformed linear distribution characteristic constraint;

[0020] Based on the linear operation constraints and the linear distribution characteristic constraints, the objective function is solved to obtain an open capacity solution for distributed photovoltaics in the target distribution network.

[0021] In a possible implementation, the operation constraints include distribution network power flow constraints, voltage deviation constraints, voltage fluctuation constraints, line thermal stability constraints, transformer thermal stability constraints, and photovoltaic inverter control constraints.

[0022] In a possible implementation, establishing a planning distribution characteristic constraint of distributed photovoltaics of the objective function according to the planning distribution characteristic and the planning distribution data includes:

[0023] According to the expression: Establishing planning distribution characteristic constraints of distributed photovoltaics of the objective function;

[0024] Where QDT represents the quantity distribution model of distributed photovoltaics, PDT represents the location distribution model of distributed photovoltaics, DP represents the dispersion model of distributed photovoltaics, and Ω QDT represents the first range corresponding to the quantity distribution degree in the planning distribution characteristic, Ω PDT represents the second range corresponding to the position distribution degree in the planning distribution characteristic, Ω DP Indicates a third range corresponding to the dispersion in the planned distribution characteristic.

[0025] In a possible implementation, a quantity distribution model of the distributed photovoltaic is established according to the number of planned nodes of the distributed photovoltaic and the number of accessible nodes in the target power distribution network that can be connected to the distributed photovoltaic, including:

[0026] According to the expression: Establishing a quantity distribution model of the distributed photovoltaics;

[0027] Wherein, QDT represents the quantity distribution model of the distributed photovoltaic, n represents the number of planned nodes of distributed photovoltaic, and N represents the number of accessible nodes that can be connected to the distributed photovoltaic.

[0028] In a possible implementation, a location distribution model of the distributed photovoltaic is established according to the planned installation node of the distributed photovoltaic and the distance between the node and the source node of the target power distribution network, including:

[0029] According to the expression: Establishing a location distribution model of the distributed photovoltaics;

[0030] In the formula, PDT represents the location distribution model of the distributed photovoltaic system, n represents the number of planned nodes of distributed photovoltaic system, R m Represents the sum of the longest line resistance in the target distribution network, R i represents the equivalent resistance of the i-th distributed photovoltaic installation node from the source node, and i represents the i-th distributed photovoltaic installation node.

[0031] In a possible implementation, a dispersion model of the distributed photovoltaic is established according to the planned access capacity of the distributed photovoltaic, including:

[0032] According to the expression: Establishing a dispersion model of the distributed photovoltaic system;

[0033] Where DP represents the dispersion model of distributed photovoltaics, P i PV represents the access capacity of distributed photovoltaic at the i-th distributed photovoltaic installation node, avg(P PV) represents the average value of the access capacity of distributed photovoltaics of all nodes in the target distribution network, n represents the number of planned nodes of distributed photovoltaics, and i represents the i-th distributed photovoltaic installation node.

[0034] In a possible implementation, an objective function is established with the goal of maximizing the open capacity of distributed photovoltaic power generation in the target distribution network, including:

[0035] According to the expression: Establish the objective function;

[0036] Where PAC represents the available capacity of distributed photovoltaic in the target distribution network, P i PV represents the photovoltaic access capacity of the i-th distributed photovoltaic installation node, n PV represents all nodes connected to distributed photovoltaic in the target distribution network, and i represents the i-th distributed photovoltaic installation node.

[0037] In a second aspect, an embodiment of the present invention provides a device for determining the openable capacity of distributed photovoltaic power generation in a distribution network, including:

[0038] An acquisition module is used to obtain the operation data of the target distribution network and the planning distribution data of distributed photovoltaics;

[0039] A determination module, used to determine the planning distribution characteristics of the distributed photovoltaic;

[0040] An establishment module is used to establish an objective function with the maximum open capacity of distributed photovoltaic in the target distribution network as the goal; establish the planning distribution characteristic constraints of distributed photovoltaic of the objective function according to the planning distribution characteristics and the planning distribution data, and establish the operation constraints of the objective function according to the operation data;

[0041] A solution module is used to obtain an open capacity solution for distributed photovoltaics of the target distribution network based on the objective function, the planning distribution characteristic constraints and the operation constraints.

[0042] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0043] The embodiment of the present invention establishes an objective function with the maximum openable capacity of distributed photovoltaic in the target distribution network as the goal, and establishes operation constraints and planning distribution characteristic constraints through the operation data of the target distribution network, the planned distribution data of distributed photovoltaic and the planned distribution characteristics of distributed photovoltaic; wherein, the planned distribution characteristics of distributed photovoltaic are first determined, and then the planning distribution characteristic constraints are established through the planning distribution characteristics and the planned distribution data of distributed photovoltaic, which can fully consider the planning situation of distributed photovoltaic; based on the objective function, the planning distribution characteristic constraints and the operation constraints, the openable capacity scheme of distributed photovoltaic of the target distribution network is obtained, which can ensure that the obtained openable capacity of distributed photovoltaic matches the planned distribution data of the target distribution network, and improve the accuracy of determining the openable capacity of distributed photovoltaic. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0045] Figure 1 This is an application scenario diagram of a method for determining the openable capacity of distributed photovoltaic power generation in a distribution network provided by an embodiment of the present invention;

[0046] Figure 2 It is a flow chart of a method for determining the openable capacity of distributed photovoltaic power generation in a distribution network provided by an embodiment of the present invention;

[0047] Figure 3 is a flowchart for determining the distribution characteristics of distributed photovoltaic planning provided by an embodiment of the present invention;

[0048] Figure 4 is a flowchart for implementing a solution for determining the openable capacity of distributed photovoltaics provided by an embodiment of the present invention;

[0049] Figure 5 It is a structural schematic diagram of a device for determining the openable capacity of distributed photovoltaic power generation in a distribution network provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0050] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0051] In order to determine the available capacity of distributed photovoltaics, calculations are usually performed by considering the operation of the distribution network. However, the inventors have found that it is difficult to accurately and reasonably determine the available capacity of distributed photovoltaics by only considering the operation of the distribution network. Therefore, it is necessary to consider a new method for determining the available capacity of distributed photovoltaics.

[0052] The inventors found that compared with centralized photovoltaics, distributed photovoltaics have a lower access voltage level, generally in the low-voltage 220 / 380V access area, with small single-unit capacity and scattered access points, and have the characteristics of "dispersion, disorder, and unobservability". When the distributed photovoltaic access location is certain, the total access capacity is different, and the overall voltage and loss of the system are different; when the distributed photovoltaic access capacity is certain, the access location is different, and the voltage changes of each node are different. Therefore, when determining the open capacity of distributed photovoltaics, it is also necessary to consider the distribution characteristics of distributed photovoltaic access capacity and location.

[0053] In order to improve the accuracy of determining the open capacity of distributed photovoltaics, in an embodiment of the present invention, an objective function is established with the maximum open capacity of distributed photovoltaics in the target distribution network as the goal, and a planning distribution characteristic constraint is established through the planning distribution data of distributed photovoltaics. This can fully consider the planning situation of distributed photovoltaics and ensure that the obtained open capacity of distributed photovoltaics matches the planning distribution data of the target distribution network, thereby improving the accuracy of the calculation of the open capacity of distributed photovoltaics.

[0054] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0055] Figure 1 This is an application scenario diagram of the method for determining the open capacity of distributed photovoltaic power distribution network provided by the embodiment of the present invention. Figure 1 As shown, the IEEE 33-node distribution network is taken as an example for explanation.

[0056] Figure 2 The implementation flow chart of the method for determining the openable capacity of distributed photovoltaic power distribution network provided by the embodiment of the present invention is described in detail as follows:

[0057] Step S201, obtaining the operation data of the target distribution network and the planning distribution data of distributed photovoltaics.

[0058] In this embodiment, the operation data may include resistance, reactance, current, active power and reactive power on the lines in the target power distribution network.

[0059] The planning distribution data of distributed photovoltaics can be the relevant data of distributed photovoltaics in the planning of the target distribution network. For example, the quantity distribution degree, location distribution degree and dispersion degree of distributed photovoltaics in the overall planning of the target distribution network. Here, the quantity distribution degree, location distribution degree and dispersion degree in the overall planning of the target distribution network are generally range data, which are used to limit the situation of distributed photovoltaics connected to the target distribution network, where the quantity distribution degree of distributed photovoltaics can correspond to the first range, the location distribution degree can correspond to the second range, and the dispersion degree can correspond to the third range, etc.

[0060] Step S202, determining the planned distribution characteristics of distributed photovoltaics.

[0061] In this embodiment, the planning distribution characteristics can be used to describe the characteristics of distributed photovoltaics in the open capacity scheme of the target distribution network. The planning distribution characteristics can include the quantity distribution degree, location distribution degree and dispersion degree of distributed photovoltaics in the open capacity scheme. Among them, the quantity distribution degree can characterize the access location of distributed photovoltaics, the location distribution degree can characterize the distance between the access location of distributed photovoltaics and the upper transformer, and the dispersion degree can characterize the degree of dispersion of the capacity accessed by distributed photovoltaics.

[0062] Accordingly, the quantity distribution model, location distribution model and dispersion model in the planning distribution characteristics of distributed photovoltaics can be established to accurately describe distributed photovoltaics.

[0063] Step S203, establishing an objective function with the goal of maximizing the available capacity of distributed photovoltaic power generation in the target distribution network.

[0064] In this embodiment, the distributed photovoltaic open capacity of the distribution network refers to the maximum distributed photovoltaic capacity that can be newly connected to the distribution network based on the existing load and photovoltaic distribution while meeting the system safety operation requirements. Therefore, the maximum distributed photovoltaic open capacity in the target distribution network can be set as the goal.

[0065] Optionally, this embodiment establishes an objective function with the goal of maximizing the open capacity of distributed photovoltaics in the target distribution network, which can be based on the expression: Establish the objective function; where PAC represents the open capacity of distributed photovoltaic in the target distribution network, P i PV represents the photovoltaic access capacity of the i-th distributed photovoltaic installation node, n PV represents all nodes connected to distributed photovoltaics in the target distribution network, and i represents the i-th distributed photovoltaic installation node.

[0066] Step S204: establishing planned distribution characteristic constraints of distributed photovoltaics of the objective function according to the planned distribution characteristics and the planned distribution data, and establishing operation constraints of the objective function according to the operation data.

[0067] In this embodiment, the planning distribution characteristic constraints of distributed photovoltaics are established based on the determined planning distribution characteristics and planning distribution data to ensure that the finally obtained open capacity of distributed photovoltaics meets the first obtained planning distribution data of distributed photovoltaics, ensures the matching of distributed photovoltaics with the target distribution network, and ensures the rationality and accuracy of the determination of the open capacity of distributed photovoltaics.

[0068] Optionally, this embodiment establishes the planning distribution characteristic constraint of distributed photovoltaics of the objective function according to the planning distribution characteristic and the planning distribution data, which may be based on the expression: Establish the planning distribution characteristic constraints of distributed photovoltaics of the objective function; where QDT represents the quantity distribution model of distributed photovoltaics, PDT represents the location distribution model of distributed photovoltaics, DP represents the dispersion model of distributed photovoltaics, and Ω QDT represents the first range corresponding to the quantity distribution degree in the planned distribution data, Ω PDT represents the second range corresponding to the position distribution degree in the planned distribution data, Ω DP Indicates the third range corresponding to the dispersion in the planned distribution data.

[0069] In this embodiment, the operating data of the target distribution network itself is also considered, and operating constraints are established based on the operating data of the target distribution network to facilitate accurate solution.

[0070] Optionally, the operation constraints of this embodiment include distribution network power flow constraints, voltage deviation constraints, voltage fluctuation constraints, line thermal stability constraints, transformer thermal stability constraints and photovoltaic inverter control constraints.

[0071] Step S205, based on the objective function, planning distribution characteristic constraints and operation constraints, obtain an open capacity solution for distributed photovoltaics in the target distribution network.

[0072] In this embodiment, the obtained distributed photovoltaic open capacity plan of the target distribution network may include whether each node in the target distribution network is connected to distributed photovoltaic, the capacity of distributed photovoltaic connected to each node, and the total capacity of all connected distributed photovoltaic.

[0073] Here, by determining the distributed photovoltaic open capacity plan of the target distribution network, the open capacity of the target distribution network can be obtained on the basis of accurately determining the capacity and location of the distributed photovoltaic access. When the distributed photovoltaic is connected, the safe operation of the target distribution network can be guaranteed, and the maximum open capacity of the target distribution network can be accurately obtained, thereby realizing accurate planning of the target distribution network and reducing the negative impact of distributed photovoltaic access on the target distribution network.

[0074] The embodiment of the present invention establishes an objective function with the maximum openable capacity of distributed photovoltaic in the target distribution network as the goal, and establishes operation constraints and planning distribution characteristic constraints through the operation data of the target distribution network, the planned distribution data of distributed photovoltaic and the planned distribution characteristics of distributed photovoltaic; wherein, the planned distribution characteristics of distributed photovoltaic are first determined, and then the planning distribution characteristic constraints are established through the planning distribution characteristics and the planned distribution data of distributed photovoltaic, which can fully consider the planning situation of distributed photovoltaic; based on the objective function, the planning distribution characteristic constraints and the operation constraints, the openable capacity scheme of distributed photovoltaic of the target distribution network is obtained, which can ensure that the obtained openable capacity of distributed photovoltaic matches the planned distribution data of the target distribution network, and improve the accuracy of determining the openable capacity of distributed photovoltaic.

[0075] In some embodiments, see Figure 3 The implementation flow chart of determining the distributed photovoltaic planning distribution characteristics is shown, and the planning distribution characteristics include quantity distribution, location distribution and dispersion. In this embodiment, the planning distribution characteristics of distributed photovoltaics are determined according to the planning distribution data, which can be:

[0076] Step S301, establishing a quantity distribution model of distributed photovoltaics according to the planned number of distributed photovoltaic nodes and the number of accessible nodes that can be connected to distributed photovoltaics in a target power distribution network.

[0077] In this embodiment, the data distribution degree represents the access position relationship of distributed photovoltaics and describes the extensiveness of the distributed photovoltaics in the target distribution network. The larger the number distribution degree, the more nodes the distributed photovoltaics are connected to and the more extensive the distribution.

[0078] Here, the quantity distribution model can be determined by the number of planned nodes of distributed photovoltaics and the number of accessible nodes that can be connected to distributed photovoltaics.

[0079] Optionally, this embodiment establishes a distributed photovoltaic quantity distribution model according to the number of planned distributed photovoltaic nodes and the number of accessible nodes that can be connected to distributed photovoltaics in the target distribution network, which can be based on the expression: A quantity distribution model of distributed photovoltaics is established; where QDT represents the quantity distribution model of distributed photovoltaics, n represents the number of planned nodes of distributed photovoltaics, and N represents the number of accessible nodes that can be connected to distributed photovoltaics.

[0080] Step S302: establishing a distributed photovoltaic location distribution model according to the planned installation nodes of the distributed photovoltaic and the distances between the nodes and the source nodes of the target power distribution network.

[0081] In this embodiment, the position distribution degree represents the distance between the access location of the distributed photovoltaic and the upper transformer. The larger the position distribution degree, the closer the overall installation location of the distributed photovoltaic is to the end of the distribution network.

[0082] Here, the location distribution model can be determined by the average measurement of the distance between the planned installation nodes of distributed photovoltaics and the source nodes in the target distribution network.

[0083] Optionally, this embodiment establishes a distributed photovoltaic location distribution model according to the planned installation nodes of the distributed photovoltaic and the distance between the distributed photovoltaic and the source node of the target distribution network, which can be based on the expression: Establish a distributed photovoltaic location distribution model; where PDT represents the distributed photovoltaic location distribution model, n represents the number of planned nodes of distributed photovoltaic, R m Represents the sum of the longest line resistance in the target distribution network, R i represents the equivalent resistance of the i-th distributed photovoltaic installation node from the source node, and i represents the i-th distributed photovoltaic installation node.

[0084] Step S303: establishing a distributed photovoltaic dispersion model according to the planned access capacity of distributed photovoltaics.

[0085] In this embodiment, the dispersion represents the uniformity of the capacity of the distributed photovoltaics connected to each distributed photovoltaic installation node in the target distribution network. A low dispersion indicates that the capacity difference of the distributed photovoltaics at each distributed photovoltaic installation node in the target distribution network is small.

[0086] Here, the dispersion model can be determined by the average measurement of the distance between the planned installation nodes of distributed photovoltaics and the source nodes in the target distribution network.

[0087] Optionally, this embodiment establishes a distributed photovoltaic dispersion model according to the planned access capacity of distributed photovoltaics, which may be based on the expression: Establish a distributed photovoltaic dispersion model; where DP represents the distributed photovoltaic dispersion model, P i PV represents the access capacity of distributed photovoltaic at the i-th distributed photovoltaic installation node, avg(P PV ) represents the average access capacity of distributed photovoltaics of all nodes in the target distribution network, n represents the number of planned nodes of distributed photovoltaics, and i represents the i-th distributed photovoltaic installation node.

[0088] The above introduces the process of determining the distributed photovoltaic planning distribution characteristics in the planning distribution characteristic constraints of the objective function. The following will continue to introduce the relevant information of the operation constraints of the objective function.

[0089] In some embodiments, the expression of the power flow constraint of the distribution network in the operation constraint may be:

[0090]

[0091] In the formula, Ω a(i) represents the set of nodes at the beginning of the line with node i as the end node, Ω b(i) represents the set of end nodes of the line with node i as the first node, P ki represents the active power on line ki, P ij represents the active power on line ij, P i load represents the active power of the load on node i, P i PV represents the photovoltaic active power injected into node i, R ki represents the resistance of the injection node line ki, R ij represents the resistance of the line out of node ij, Q ki represents the reactive power on line ki, Q ij represents the reactive power on line ij, represents the reactive power of the load on node i, represents the photovoltaic reactive power injected into node i, U i represents the voltage of the first node i on line ij, U j The voltage at the end node j of line ij, X ki represents the reactance injected into node line ki, X ij represents the reactance of the line outflowing from node ij, S ij Represents the apparent power flowing through line ij, I ij represents the current flowing through line ij, k represents the head node number of line ki injected into node i, i represents the node number of the distribution network, and j represents the terminal node number of line ij flowing out of node i.

[0092] The expression of voltage deviation constraint can be:

[0093] U N (1-ε1)≤U i ≤U N (1-ε2);

[0094] Where U N represents the nominal voltage, ε1 represents the upper limit of the voltage deviation rate, and ε2 represents the lower limit of the voltage deviation rate.

[0095] The expression of voltage fluctuation constraint can be:

[0096]

[0097] Where, d PV,i represents the voltage fluctuation rate of node i, λ pvIt indicates the ratio of the instantaneous power change of distributed photovoltaic power source caused by factors such as light and temperature to its rated output power. a represents the resistance between node a and node a+1, d max It represents the maximum voltage fluctuation rate allowed by the national standard, i, a and b represent the node numbers of the distribution network, where a=1 represents the first node in the distribution network, and n represents the number of planned nodes of distributed photovoltaic.

[0098] The expression of circuit thermal stability constraint can be:

[0099] S ij ≤S ij,max ;

[0100] In the formula, S ij,max Represents the maximum value of the apparent power flowing through line ij.

[0101] The thermal stability constraint of the transformer can be expressed as:

[0102]

[0103] In the formula, λ represents the reverse load rate, S e Indicates the actual operating limit of the transformer or line, λ max Indicates the maximum reverse load rate.

[0104] The expression of the control constraint of the photovoltaic inverter can be:

[0105]

[0106]

[0107] In the formula, Indicates the actual active power of the photovoltaic nodes connected to distributed photovoltaics in the open capacity solution. Indicates the actual photovoltaic reactive power of the node where distributed photovoltaic is installed. represents the maximum value of the power factor of the photovoltaic inverter at node i, represents the minimum value of the power factor of the photovoltaic inverter at node i, P i cap represents the installed capacity of distributed photovoltaics at node i, β i represents the photovoltaic output ratio coefficient at node i, which is related to the light intensity of node i. PAC represents the open capacity of distributed photovoltaic in the target distribution network. Z i Indicates whether photovoltaic is installed, Z i =1 means that distributed photovoltaic is installed on node i, Z i =0 means that no distributed photovoltaic is installed on node i.

[0108] So far, the constraints of the objective function have been introduced. The following will continue to introduce the process of obtaining the open capacity plan of distributed photovoltaics in the target distribution network.

[0109] In some embodiments, the model and constraints established in the above steps are nonlinear non-convex mixed integer models, which can be converted into linear mixed integer models and then solved, thereby reducing the difficulty of solution and improving the accuracy of the obtained distributed photovoltaic open capacity solution.

[0110] See also Figure 4 The implementation flow chart of determining the open capacity scheme of distributed photovoltaics shown in the figure can obtain the open capacity scheme of distributed photovoltaics of the target distribution network based on the objective function, planning distribution characteristic constraints and operation constraints, which can be:

[0111] Step S401, performing a linear transformation on the operation constraint to obtain a transformed linear operation constraint.

[0112] In this embodiment, the operation constraints may be linearly transformed by using square term replacement, second-order cone relaxation, and large-M linearization.

[0113] Optionally, the distribution network power flow constraint of the operation constraint contains a square term, which can be transformed by replacing the square term first and introducing an auxiliary variable and By removing the square term, we can get the following expression:

[0114]

[0115]

[0116] In the formula,

[0117] After the auxiliary variables are introduced in the above formula, it is still non-convex and nonlinear. On this basis, the second-order cone relaxation can be used to convert it into a second-order cone convex constraint, as shown in the following formula:

[0118]

[0119] In addition, the 0-1 variable representing the photovoltaic installation location is introduced into the control constraint of the photovoltaic inverter with operation constraints, which leads to the nonlinearity of the product of integer variables and continuous variables. Therefore, the big M method can be used for relaxation to convert it into a linear constraint, and the following expression can be obtained:

[0120]

[0121] In the formula, M represents a value with an absolute value of infinity.

[0122] Therefore, through the above transformation, the operation constraint is transformed into a linear operation constraint.

[0123] Step S402: using auxiliary variables, transform the absolute value parameters in the planning distribution characteristic constraint to obtain a transformed linear distribution characteristic constraint.

[0124] In this embodiment, for the dispersion model in the planning distribution characteristic constraint, which contains nonlinearity of the absolute value and the quotient of continuous variables, the denominator variable can be moved to the other side of the equation for the quotient of the continuous variable, as shown in the following expression:

[0125]

[0126] Where n represents the number of planned nodes of distributed photovoltaics, and DP represents the dispersion model of distributed photovoltaics.

[0127] For the absolute value expression in the above formula, it can be linearized by introducing auxiliary variables S1 and S2. Let the absolute value expression equal to Y, then it can be expressed as: Y = |P i PV -avg(P PV )|. The corresponding linearization can be expressed as:

[0128]

[0129] Thus, through the above transformation, the planning distribution characteristic constraint is transformed into a linear distribution characteristic constraint.

[0130] Step S403, based on the linear operation constraints and the linear distribution characteristic constraints, solve the objective function to obtain the open capacity solution of the distributed photovoltaic of the target distribution network.

[0131] In this embodiment, after the transformation of step S401 and step S402, a linear mixed integer model can be obtained through the objective function, the linear operation constraint and the linear distribution characteristic constraint, so that the solution can be directly performed.

[0132] Optionally, the solver Cplex may be used to solve the problem, thereby obtaining an open capacity solution for distributed photovoltaics in the target distribution network.

[0133] In addition, after obtaining the open capacity plan, the penetration rate of distributed photovoltaics in the plan can also be calculated. The penetration rate can characterize the total access capacity of distributed photovoltaics. Specifically, it can be determined by the ratio of the installed capacity of distributed photovoltaics to the active power of the maximum load, and its expression is as follows:

[0134]

[0135] Where PR represents the permeability, represents the actual installed capacity of distributed photovoltaic equipment at node p during period t, in MW. represents the maximum daily active power of the load of node g in period t, in MW, p represents the node p connected to the distributed photovoltaic device, t represents period t, g represents the load node g, Ω PV Represents all nodes connected to distributed photovoltaic equipment, Ω T Indicates all time periods, Ω G Represents the set of all load nodes.

[0136] The embodiment of the present invention establishes an objective function with the maximum openable capacity of distributed photovoltaics in the target distribution network as the goal, and establishes operation constraints and planning distribution characteristic constraints through the operation data of the target distribution network, the planned distribution data of distributed photovoltaics and the planned distribution characteristics of distributed photovoltaics; wherein, the planned distribution characteristics of distributed photovoltaics are first determined, and then the planning distribution characteristic constraints are established through the planning distribution characteristics and the planned distribution data of distributed photovoltaics, which can fully consider the planning situation of distributed photovoltaics; based on the objective function, the planning distribution characteristic constraints and the operation constraints, the openable capacity scheme of distributed photovoltaics in the target distribution network is obtained, which can ensure that the obtained openable capacity of distributed photovoltaics matches the planned distribution data of the target distribution network, and improve the accuracy of determining the openable capacity of distributed photovoltaics.

[0137] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0138] The following is an embodiment of the device of the present invention. For details not described in detail therein, reference may be made to the corresponding method embodiment described above.

[0139] Figure 5 The structure diagram of the device for determining the openable capacity of distributed photovoltaic power distribution network provided by the embodiment of the present invention is shown. For the convenience of explanation, only the part related to the embodiment of the present invention is shown, which is described in detail as follows:

[0140] like Figure 5 As shown, the device 50 for determining the openable capacity of distributed photovoltaic power distribution network includes:

[0141] An acquisition module 51 is used to acquire the operation data of the target distribution network and the planning distribution data of distributed photovoltaics;

[0142] A determination module 52 is used to determine the planning distribution characteristics of distributed photovoltaics;

[0143] Establishing module 53, used to establish an objective function with the maximum open capacity of distributed photovoltaic in the target distribution network as the goal; establishing the planning distribution characteristic constraints of distributed photovoltaic of the objective function according to the planning distribution characteristics and planning distribution data, and establishing the operation constraints of the objective function according to the operation data;

[0144] The solution module 54 is used to obtain an open capacity solution for distributed photovoltaics in the target distribution network based on the objective function, planning distribution characteristic constraints and operation constraints.

[0145] In a possible implementation, the planning distribution characteristics include quantity distribution, location distribution and dispersion:

[0146] The determination module 52 is specifically used for:

[0147] According to the number of planned distributed photovoltaic nodes and the number of accessible nodes that can be connected to distributed photovoltaics in the target distribution network, a quantitative distribution model of distributed photovoltaics is established;

[0148] According to the planned installation nodes of distributed photovoltaics and their distances from the source nodes of the target distribution network, a location distribution model of distributed photovoltaics is established;

[0149] According to the planned access capacity of distributed photovoltaics, a dispersion model of distributed photovoltaics is established.

[0150] In a possible implementation, the solution module 54 is specifically used to:

[0151] Performing a linear transformation on the operation constraint to obtain a transformed linear operation constraint;

[0152] By using auxiliary variables, the absolute value parameters in the planning distribution characteristic constraints are transformed to obtain the transformed linear distribution characteristic constraints;

[0153] Based on the linear operation constraints and linear distribution characteristic constraints, the objective function is solved and the open capacity plan of distributed photovoltaics in the target distribution network is obtained.

[0154] In a possible implementation, the operation constraints include distribution network power flow constraints, voltage deviation constraints, voltage fluctuation constraints, line thermal stability constraints, transformer thermal stability constraints, and photovoltaic inverter control constraints.

[0155] In a possible implementation, the establishing module 53 is specifically used for:

[0156] According to the expression: Establish planning distribution characteristic constraints of distributed photovoltaics based on objective functions;

[0157] Where QDT represents the quantity distribution model of distributed photovoltaics, PDT represents the location distribution model of distributed photovoltaics, DP represents the dispersion model of distributed photovoltaics, and Ω QDT represents the first range corresponding to the number distribution degree in the planning distribution characteristics, Ω PDT represents the second range corresponding to the position distribution degree in the planning distribution characteristic, Ω DP Indicates the third range corresponding to the dispersion in the planning distribution characteristics.

[0158] In a possible implementation, the determination module 52 is specifically configured to:

[0159] According to the expression: Establish a quantitative distribution model of distributed photovoltaics;

[0160] Where QDT represents the quantity distribution model of distributed photovoltaics, n represents the number of planned nodes of distributed photovoltaics, and N represents the number of accessible nodes that can be connected to distributed photovoltaics.

[0161] In a possible implementation, the determination module 52 is specifically configured to:

[0162] According to the expression: Establish the location distribution model in the distribution characteristics of distributed photovoltaic planning;

[0163] In the formula, PDT represents the location distribution model of distributed photovoltaics, n represents the number of planned nodes of distributed photovoltaics, and R m Represents the sum of the longest line resistance in the target distribution network, R i represents the equivalent resistance of the i-th distributed photovoltaic installation node from the source node, and i represents the i-th distributed photovoltaic installation node.

[0164] In a possible implementation, the determination module 52 is specifically configured to:

[0165] According to the expression: Establish a dispersion model for distributed photovoltaics;

[0166] Where DP represents the dispersion model of distributed photovoltaics, P i PV represents the access capacity of distributed photovoltaic at the i-th distributed photovoltaic installation node, avg(P PV ) represents the average access capacity of distributed photovoltaics of all nodes in the target distribution network, n represents the number of planned nodes of distributed photovoltaics, and i represents the i-th distributed photovoltaic installation node.

[0167] In a possible implementation, the establishing module 53 is specifically used for:

[0168] According to the expression: Establish the objective function;

[0169] Where PAC represents the available capacity of distributed photovoltaic in the target distribution network, P i PV represents the photovoltaic access capacity of the i-th distributed photovoltaic installation node, n PV represents all nodes connected to distributed photovoltaics in the target distribution network, and i represents the i-th distributed photovoltaic installation node.

[0170] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0171] Those of ordinary skill in the art will appreciate that the templates, units, and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0172] If the module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. Computer-readable media may include: any entity or device that can carry computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0173] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A method for determining the open capacity of distributed photovoltaic power generation in a distribution network, characterized in that: include: Obtain the operating data of the target distribution network and the planning and distribution data of distributed photovoltaics; Determining the planning distribution characteristics of the distributed photovoltaics; Establishing an objective function with the goal of maximizing the open capacity of distributed photovoltaics in the target distribution network; Establishing a planning distribution characteristic constraint of distributed photovoltaics of the objective function according to the planning distribution characteristic and the planning distribution data, and establishing an operation constraint of the objective function according to the operation data; Based on the objective function, the planning distribution characteristic constraint and the operation constraint, an openable capacity plan of distributed photovoltaics of the target distribution network is obtained.

2. The method for determining the openable capacity of distributed photovoltaic power generation in a distribution network according to claim 1, characterized in that: The planning distribution characteristics include quantity distribution, location distribution and dispersion; Determining the planning distribution characteristics of the distributed photovoltaic system, including: Establishing a quantity distribution model of the distributed photovoltaic system according to the planned number of nodes of the distributed photovoltaic system and the number of accessible nodes in the target distribution network that can be connected to the distributed photovoltaic system; Establishing a location distribution model of the distributed photovoltaic system according to the planned installation nodes of the distributed photovoltaic system and the distances between the distributed photovoltaic system and the source nodes of the target power distribution network; A dispersion model of the distributed photovoltaic is established according to the planned access capacity of the distributed photovoltaic.

3. The method for determining the openable capacity of distributed photovoltaic power generation in a distribution network according to claim 1, characterized in that: Based on the objective function, the planning distribution characteristic constraint and the operation constraint, an open capacity solution of distributed photovoltaics of the target distribution network is obtained, including: Performing a linear transformation on the operation constraint to obtain a transformed linear operation constraint; Using auxiliary variables, transforming the absolute value parameters in the planning distribution characteristic constraint to obtain a transformed linear distribution characteristic constraint; Based on the linear operation constraints and the linear distribution characteristic constraints, the objective function is solved to obtain an open capacity solution for distributed photovoltaics in the target distribution network.

4. The method for determining the openable capacity of distributed photovoltaic power generation in a distribution network according to claim 1, characterized in that: The operation constraints include distribution network power flow constraints, voltage deviation constraints, voltage fluctuation constraints, line thermal stability constraints, transformer thermal stability constraints and photovoltaic inverter control constraints.

5. The method for determining the openable capacity of distributed photovoltaic power generation in a distribution network according to claim 2, characterized in that: According to the planned distribution characteristics and the planned distribution data, a planned distribution characteristic constraint of distributed photovoltaics of the objective function is established, including: According to the expression: Establishing planning distribution characteristic constraints of distributed photovoltaics of the objective function; Where QDT represents the quantity distribution model of distributed photovoltaics, PDT represents the location distribution model of distributed photovoltaics, DP represents the dispersion model of distributed photovoltaics, and Ω QDT represents the first range corresponding to the quantity distribution degree in the planned distribution data, Ω PDT represents the second range corresponding to the position distribution degree in the planned distribution data, Ω DP Indicates a third range corresponding to the dispersion in the planned distribution data.

6. The method for determining the openable capacity of distributed photovoltaic power generation in a distribution network according to claim 2, characterized in that: According to the planned number of nodes of the distributed photovoltaic system and the number of accessible nodes in the target power distribution network that can be connected to the distributed photovoltaic system, a quantity distribution model of the distributed photovoltaic system is established, including: According to the expression: Establishing a quantity distribution model of the distributed photovoltaics; Wherein, QDT represents the quantity distribution model of the distributed photovoltaic, n represents the number of planned nodes of distributed photovoltaic, and N represents the number of accessible nodes that can be connected to the distributed photovoltaic.

7. The method for determining the openable capacity of distributed photovoltaic power generation in a distribution network according to claim 2, characterized in that: According to the planned installation nodes of the distributed photovoltaics and the distances between the nodes and the source nodes of the target power distribution network, a location distribution model of the distributed photovoltaics is established, including: According to the expression: Establishing a location distribution model of the distributed photovoltaics; In the formula, PDT represents the location distribution model of the distributed photovoltaic system, n represents the number of planned nodes of distributed photovoltaic system, R m Represents the sum of the longest line resistance in the target distribution network, R i represents the equivalent resistance of the i-th distributed photovoltaic installation node from the source node, and i represents the i-th distributed photovoltaic installation node.

8. The method for determining the openable capacity of distributed photovoltaic power generation in a distribution network according to claim 2, characterized in that: According to the planned access capacity of the distributed photovoltaic, a dispersion model of the distributed photovoltaic is established, including: According to the expression: Establishing a dispersion model of the distributed photovoltaic system; Where DP represents the dispersion model of distributed photovoltaics, P i PV represents the access capacity of distributed photovoltaic at the i-th distributed photovoltaic installation node, avg(P PV ) represents the average value of the access capacity of distributed photovoltaics of all nodes in the target distribution network, n represents the number of planned nodes of distributed photovoltaics, and i represents the i-th distributed photovoltaic installation node.

9. The method for determining the openable capacity of distributed photovoltaic power generation in a distribution network according to any one of claims 1 to 8, characterized in that: The objective function is established with the goal of maximizing the open capacity of distributed photovoltaics in the target distribution network, including: According to the expression: Establish the objective function; Where PAC represents the available capacity of distributed photovoltaic in the target distribution network, P i PV represents the photovoltaic access capacity of the i-th distributed photovoltaic installation node, n PV represents all nodes connected to distributed photovoltaic in the target distribution network, and i represents the i-th distributed photovoltaic installation node.

10. A device for determining the openable capacity of distributed photovoltaic power generation in a distribution network, characterized in that: include: An acquisition module is used to obtain the operation data of the target distribution network and the planning distribution data of distributed photovoltaics; A determination module, used to determine the planning distribution characteristics of the distributed photovoltaic; An establishment module is used to establish an objective function with the maximum open capacity of distributed photovoltaic in the target distribution network as the goal; establish the planning distribution characteristic constraints of distributed photovoltaic of the objective function according to the planning distribution characteristics and the planning distribution data, and establish the operation constraints of the objective function according to the operation data; A solution module is used to obtain an open capacity solution for distributed photovoltaics of the target distribution network based on the objective function, the planning distribution characteristic constraints and the operation constraints.

Images