Static var generator planning method considering comprehensive construction cost in extreme scene

Abstract

The invention relates to the technical field of power grid planning, and provides a static var generator planning method considering comprehensive construction cost in an extreme scene, which comprises the following steps: establishing a power distribution network power flow model based on second-order cone relaxation, and performing optimization control on an operation mode of a photovoltaic grid-connected converter in a power distribution network based on the power distribution network power flow model. Switching between a constant power factor mode and a power grid voltage support mode, and creating a primary optimization model; adding a static var generator at part of nodes of the power distribution network, and establishing an optimization model with the minimum construction cost of the static var generator; the comprehensive cost of the static var generator construction schemes in different extreme scenes is analyzed, and the construction cost and the operation loss are analyzed; and determining an optimal static var generator construction scheme by adopting a net present value method. According to the method, the static var generators are additionally arranged at part of nodes of the power distribution network, so that the power distribution network can normally operate in all extreme scenes, and the comprehensive cost of constructing the static var generators is comprehensively considered.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid planning, and in particular to a static VAR generator planning method considering comprehensive construction costs under extreme scenarios. Background Art

[0002] SVG (Static Var Generator), or static var generator, is a typical power electronic device, consisting of three basic functional modules: detection module, control operation module and compensation output module. SVG static var generator uses a self-commutated bridge circuit composed of turn-off power electronic devices (IGBT), which is connected to the power grid in parallel through a reactor, and properly adjusts the amplitude and phase of the output voltage on the AC side of the bridge circuit, or directly controls the current on its AC side. Rapidly absorb or emit the required reactive power to achieve the purpose of rapid dynamic reactive adjustment.

[0003] In extreme scenarios (including high load levels, extreme weather scenarios such as solar eclipses), in distribution networks containing distributed photovoltaics, since photovoltaic systems often operate in constant power factor mode, when the active power provided by the photovoltaic system is insufficient, the reactive power it provides is limited, resulting in undervoltage problems at the end nodes of the grid. One solution is to switch the mode of the photovoltaic grid-connected converter so that the photovoltaic system can operate in the grid voltage support mode to provide more reactive power, but the photovoltaic operation benefits are reduced due to the reduction in photovoltaic active output, and it cannot cope with more extreme scenarios.

[0004] The undervoltage problem of the terminal nodes in the distribution network with high photovoltaic penetration in extreme scenarios is analyzed, and it is found that even if the operation mode of the photovoltaic grid-connected converter is optimized and controlled, the undervoltage problem cannot be completely solved. Therefore, the present invention proposes a static VAR generator planning method considering the comprehensive construction cost in extreme scenarios. Summary of the invention

[0005] The present invention aims to solve the undervoltage problem existing in the prior art at the terminal nodes of the distribution network, and the technical defects that when the photovoltaic grid-connected converter mode is switched, the photovoltaic operation income is reduced due to the reduction of photovoltaic active output, and the inability to cope with more extreme scenarios. A static VAR generator planning method taking into account the comprehensive construction cost under extreme scenarios is provided, aiming to solve the existing undervoltage problem, build static VAR generators at some nodes of the distribution network to provide more reactive power support, achieve the optimal static VAR generator construction plan, and ensure that the distribution network voltage can meet the safe operation requirements under extreme scenarios.

[0006] A static VAR generator planning method considering comprehensive construction costs under extreme scenarios, the method comprising the following steps:

[0007] Step 1: Establish a distribution network power flow model based on second-order cone relaxation;

[0008] Step 2: Based on the distribution network power flow model, the operation mode of the photovoltaic grid-connected converter in the distribution network is optimized and controlled, switching between the constant power factor mode and the grid voltage support mode to create an optimization model;

[0009] Step 3: Install static VAR generators at some nodes of the distribution network and establish an optimization model with the minimum construction cost of static VAR generators;

[0010] Step 4: Analyze the comprehensive cost of the static VAR generator construction plan under different extreme scenarios, and analyze the construction cost and operation loss;

[0011] Step 5: Use the net present value method to determine the optimal static VAR generator construction plan.

[0012] Preferably, the expression of the distribution network power flow model based on second-order cone relaxation is as follows:

[0013] Among them, the expression of the active power balance equation of the distribution network node is:

[0014]

[0015] The expression of the reactive power balance equation of the distribution network node is:

[0016]

[0017] The expression of the distribution network branch voltage equation is:

[0018]

[0019] The constraints of the voltage and current of the distribution network branches are as follows:

[0020]

[0021] in, The constraints are:

[0022]

[0023] The photovoltaic system operates in constant power factor mode, which is expressed by the following formula:

[0024]

[0025] The generator active power injection value at the distribution network node k at time t should meet the upper and lower limits of the generator output. When there is no generator at the k node, the generator active power injection is set to 0. The expression is as follows:

[0026]

[0027] The reactive power injection value of the generator at the distribution network node k at time t should meet the upper and lower limits of the generator output. When there is no generator at the k node, the reactive power injection of the generator is set to 0. The expression is as follows:

[0028]

[0029] The photovoltaic active power injection and reactive power injection of the distribution network node k at time t must meet the photovoltaic capacity constraint. For nodes without photovoltaic installation, the photovoltaic active and reactive power injection are set to 0. The expressions are as follows:

[0030]

[0031] In the above formula, They represent the active power injection of the generator and photovoltaic at node k at time t, They represent the reactive power injection of the generator and photovoltaic at node k at time t, P jk,t , Q jk,t They represent the active power and reactive power flow of branch jk at time t, r jk 、x jk They represent the resistance and reactance of branch jk respectively, l jk,t represents the square of the current in branch jk at time t, They represent the active load and reactive load of node k at time t, w is the load expansion rate, u k,t is the square of the node voltage at node k at time t, represents the capacity of the photovoltaic system at node k, η PV The photovoltaic penetration rate of the entire photovoltaic system, represents the maximum active output value of the photovoltaic system at node k at time t, tanθ k Represents the power factor of the photovoltaic system at node k, Ω E is the set of all nodes in the distribution network, Ω B is the set of all branches of the distribution network, Ω PV is the set of all nodes equipped with photovoltaic systems, Ω gen is the set of all nodes equipped with generators, δ(k) and σ(k) are the parent nodes and child nodes of node k, respectively, T is the set of all moments, u k,t Represents the square of the node voltage of the entire system, U min , U max They represent the lower and upper limits of the node voltage of the entire system, respectively. ik,t represents the active power flow of branch ik at time t, Q ik,trepresents the reactive power flow of branch ik at time t, Indicates the upper limit of the current on branch jk, P k gen,min , P k gen,max They represent the lower and upper limits of the active output of the generator at node k, Q k gen,min , Q k gen,max They represent the lower and upper limits of reactive power output of the generator at node k respectively.

[0032] Preferably, in step 2, based on the distribution network power flow model, the operation mode of the photovoltaic grid-connected converter in the distribution network is optimized and controlled, and switched between the constant power factor mode and the grid voltage support mode. The expression of the grid voltage support mode is as follows:

[0033] The operation mode of the photovoltaic grid-connected converter in the distribution network is optimized and controlled so that the operation mode of the photovoltaic grid-connected converter in the distribution network is switched between a constant power factor mode and a grid voltage support mode.

[0034] Preferably, the process of creating an optimization model is as follows:

[0035] The big M method is used to write the photovoltaic system operating in constant power factor mode and in grid voltage support mode together, and the expression is as follows:

[0036]

[0037] Where M is an infinite positive number, m k,t The value of determines the operation mode of the photovoltaic system, m k,t = 0, the photovoltaic system is in constant power factor mode, m k,t =1 when the photovoltaic system is in the grid voltage support mode;

[0038] The expression of an optimization model is:

[0039]

[0040] Preferably, establishing an optimization model for minimizing the construction cost of a static VAR generator includes the following contents:

[0041] The related constraint expressions of static VAR generator are:

[0042]

[0043] in, is the reactive power output of the static VAR generator at node k at time t, is the minimum reactive power output of the static VAR generator at node k, is the maximum reactive power output of the static VAR generator at node k, Ω SVG is the set of all nodes equipped with static VAR generators;

[0044] The active power balance equation and reactive power balance equation of the distribution network node are transformed into:

[0045]

[0046] In the above formula, P k,t represents the active power flow of node k at time t, Q ki,t represents the reactive power flow of branch ki at time t; the optimization model with the minimum construction cost of static VAR generator is expressed as:

[0047]

[0048] Preferably, the comprehensive cost of the static VAR generator construction scheme under different extreme scenarios is analyzed, and the construction cost and operation loss are analyzed, and the following formula is used to express it:

[0049]

[0050] in, is the difference between the power outage loss and the PV active power increase under scenario y, i.e., the operating loss. is the power outage loss in scenario y; is the increase in total photovoltaic active output in scenario y; C P,loss,0 is the total active power loss; is the total photovoltaic active power loss of the coordinated optimization of the static VAR generator and photovoltaic operation mode under scenario y; Ω Y is the set of all scenarios that require the installation of static VAR generators; R(y) is the set of extreme power outage scenarios corresponding to each extreme scenario y; c is the power outage loss coefficient; w y is the load expansion rate corresponding to scenario y; p r is the probability of power outage scenario r occurring.

[0051] Preferably, the optimal static VAR generator construction scheme determined by the net present value method includes:

[0052] All future operating losses are converted to the present through the net present value method, and then added to the initial static VAR generator construction cost to obtain the net present value cost of each plan. The optimal construction plan is determined by comparing the net present value costs. The net present value method formula is:

[0053]

[0054] Where NPV is the net present value, CF ist is the operating loss in period t, r is the discount rate, n is the life cycle of the static VAR generator SVG, t is time, and C0 is the initial static VAR generator construction cost.

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

[0056] The present invention analyzes the undervoltage problem of the terminal nodes in the distribution network with high photovoltaic penetration rate under extreme scenarios, optimizes and controls the operation mode of the grid-connected converter of the photovoltaic system, and constructs static VAR generators at some nodes of the distribution network to provide more reactive power support, so that the distribution network can operate normally under all extreme scenarios; the net present value method is adopted and the three costs of the construction cost of the static VAR generator, the switching of the photovoltaic system operation mode and the loss caused by power outage are comprehensively considered to obtain the optimal planning and construction plan. It makes up for the technical defects of the difficulty in coping with extreme scenarios due to the reduction of photovoltaic active output and the reduction of photovoltaic operation income when the photovoltaic grid-connected converter mode is switched due to the undervoltage problem of the terminal node of the distribution network, and the difficulty in coping with the technical defects of extreme scenarios, and provides a scientific and effective theoretical basis for power operation planning and management. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0058] Figure 1 is a schematic flow chart of a method in an embodiment of the present invention;

[0059] Figure 2 is a topological diagram of an IEEE 33-node distribution network in an embodiment of the present invention;

[0060] Figure 3 is a load curve and a photovoltaic curve diagram in an embodiment of the present invention;

[0061] Figure 4 is a node voltage diagram under an extreme scenario in an embodiment of the present invention;

[0062] Figure 5 is a node voltage diagram of a photovoltaic penetration rate of 0.3 and a load expansion rate of 1.4 in an embodiment of the present invention;

[0063] Figure 6 It is a node voltage diagram with a photovoltaic penetration rate of 0.3 and a load expansion rate of 1.8 in an embodiment of the present invention;

[0064] Figure 7It is a comprehensive cost comparison chart of scenarios 0-11 in an embodiment of the present invention. DETAILED DESCRIPTION

[0065] In order to more fully understand the technical content of the present invention, the technical solution of the present invention is further introduced and illustrated in conjunction with specific embodiments below, but is not limited thereto. The technical solution in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0066] refer to Figure 1 , combined with actual application cases, this paper introduces the static VAR generator planning method considering the comprehensive construction cost in extreme scenarios, including: firstly, establishing a distribution network flow model based on second-order cone relaxation, analyzing the undervoltage problem of the terminal node in the distribution network with high photovoltaic penetration in extreme scenarios, and finding that even if the operation mode of the photovoltaic grid-connected converter is optimized and controlled, there is still a probability of voltage problems. Therefore, in order to expand the scope of normal operation of the distribution network in extreme scenarios, the present invention considers installing static VAR generators SVG at some nodes of the distribution network, comprehensively comparing the planning and construction costs and operating losses of different construction plans, and using the present value method to obtain the optimal construction plan.

[0067] The specific steps of the static VAR generator planning method considering the comprehensive construction cost under extreme scenarios are:

[0068] Step 1: Establish a distribution network power flow model based on second-order cone relaxation;

[0069] The expression of the distribution network power flow model is as follows:

[0070] Among them, the expression of the active power balance equation of the distribution network node is:

[0071]

[0072] The expression of the reactive power balance equation of the distribution network node is:

[0073]

[0074] The expression of the distribution network branch voltage equation is:

[0075]

[0076] The constraints of the voltage and current of the distribution network branches are as follows:

[0077]

[0078] in, The constraints are:

[0079]

[0080] The photovoltaic system operates in constant power factor mode, which is expressed by the following formula:

[0081]

[0082] The generator active power injection value at the distribution network node k at time t should meet the upper and lower limits of the generator output. When there is no generator at the k node, the generator active power injection is set to 0. The expression is as follows:

[0083]

[0084] The reactive power injection value of the generator at the distribution network node k at time t should meet the upper and lower limits of the generator output. When there is no generator at the k node, the reactive power injection of the generator is set to 0. The expression is as follows:

[0085]

[0086] The photovoltaic active power injection and reactive power injection of the distribution network node k at time t must meet the photovoltaic capacity constraint. For nodes without photovoltaic installation, the photovoltaic active and reactive power injection are set to 0. The expressions are as follows:

[0087]

[0088] in, The active power injection of the generator and PV at node k at time t, respectively, They represent the reactive power injection of the generator and photovoltaic at node k at time t, P jk,t , Q jk,t They represent the active power and reactive power flow of branch jk at time t, r jk 、x jk They represent the resistance and reactance of branch jk respectively, l jk,t represents the square of the current in branch jk at time t, They represent the active load and reactive load of node k at time t, w is the load expansion rate, u k,t is the square of the node voltage at node k at time t, represents the capacity of the photovoltaic system at node k, η PV The photovoltaic penetration rate of the entire photovoltaic system, represents the maximum active output value of the photovoltaic system at node k at time t, tanθ k Represents the power factor of the photovoltaic system at node k, ΩE is the set of all nodes, Ω B is the set of all branches, Ω PV is the set of all nodes equipped with photovoltaic systems, Ω gen is the set of all nodes equipped with generators, δ(k) and σ(k) are the parent nodes and child nodes of node k, respectively, T is the set of all moments, u k,t Represents the square of the node voltage of the entire system, U min , U max They represent the lower and upper limits of the node voltage of the entire system, respectively. ik,t represents the active power flow of branch ik at time t, Q ik,t represents the reactive power flow of branch ik at time t, Indicates the upper limit of the current on branch jk, P k gen,min , P k gen,max They represent the lower and upper limits of the active output of the generator at node k, Q k gen,min , Q k gen,max They represent the lower and upper limits of reactive power output of the generator at node k respectively.

[0089] Step 2: Based on the distribution network power flow model, the operation mode of the photovoltaic grid-connected converter in the distribution network is optimized and controlled, switching between the constant power factor mode and the grid voltage support mode to create an optimization model.

[0090] Firstly, based on the established distribution network power flow model, the undervoltage problem occurring at the terminal nodes of the distribution network under extreme scenarios is analyzed;

[0091] refer to Figures 2 to 4 , where nodes #6, #12, #16, #18, #19, #22, #25, #28 and #33 are all equipped with photovoltaic systems and all photovoltaic systems are operating in constant power factor mode, the photovoltaic penetration rate and load expansion rate of the photovoltaic system are 0.3 and 1.4 respectively; nodes #13-#18 and nodes #30-#33 have undervoltage problems, and are all distributed at the end of the distribution network. In order to solve the voltage problem at the end nodes of the distribution network in extreme scenarios, we first consider optimizing the operation mode of the photovoltaic grid-connected converter in the distribution network, changing the operation mode of the photovoltaic system, and changing the photovoltaic system to switch between the constant power factor mode and the grid voltage support mode, and analyzing its improvement effect on the voltage problem of the end nodes.

[0092] Formula (1-8) does not consider the switching of the operating mode of the photovoltaic system. The default operation is in the constant power factor mode (m k,t=0). In this mode, the reactive power and active power output of photovoltaic are in a certain ratio. When the active power output of photovoltaic is insufficient, photovoltaic cannot provide enough reactive power support, resulting in voltage problems at the end nodes of the distribution network. When the photovoltaic system operates in the grid voltage support mode (m k,t =1), the power equation of the grid voltage support mode is:

[0093]

[0094] u k,t The value of is obtained by the solver. When the PV system operates in the grid voltage support mode, the reactive power and active power output by the PV system only need to meet the capacity constraint. When the PV active output is low, more reactive power can be output to support the voltage stability of the system. To avoid if-then constraints, the Big-M method can be used to write the two operating modes together. The expression is as follows:

[0095]

[0096] Where M is an infinite positive number, m k,t The value of determines the operation mode of the photovoltaic system, m k,t = 0, the photovoltaic system is in constant power factor mode, m k,t =1 when the photovoltaic system is in the grid voltage support mode;

[0097] The expression of an optimization model is:

[0098]

[0099] The primary optimization model is set up in this way to minimize the active power loss caused by the photovoltaic system switching to the grid voltage support mode in order to provide more reactive power. When the photovoltaic system operates in the constant power factor mode, the active power loss of the photovoltaic system is 0. The improvement effect of the voltage operation mode switching on the undervoltage problem of the distribution network is analyzed according to formula (1-16).

[0100] refer to Figure 5 to Figure 6 When the PV penetration rate and the load expansion rate are 0.3 and 1.4 respectively, the node voltage of the distribution network is obtained. At this time, all node voltages can meet the requirements of safe operation; however, considering a more extreme scenario, when the PV penetration rate and the load expansion rate are 0.3 and 1.8 respectively, the node voltage of the distribution network is obtained, and undervoltage problems will still occur.

[0101] In order to ensure that the voltage at the distribution network nodes can meet the requirements of safe operation in all possible extreme scenarios, it is considered to install static VAR generators at some nodes of the distribution network to provide more reactive power support.

[0102] Step 3: Install static VAR generators at some nodes of the distribution network to enable the distribution network to operate normally under all extreme scenarios, establish an optimization model with the minimum construction cost of the static VAR generator, and obtain the static VAR generator construction plan under all extreme scenarios.

[0103] The primary optimization model can improve the voltage problem, but it still cannot meet the requirements for more extreme situations, so the installation of SVG is considered. The method of establishing the optimization model with the lowest construction cost of static VAR generator is as follows:

[0104] First, establish the SVG related constraints:

[0105]

[0106] in, is the reactive power output of the static VAR generator at node k at time t, is the minimum reactive power output of the static VAR generator at node k, is the maximum reactive power output of the static VAR generator at node k, Ω SVG is the set of all nodes equipped with static VAR generators.

[0107] Then, the balance equation of active power and reactive power at the distribution network node is changed to:

[0108]

[0109] In the above formula, P k,t represents the active power flow of node k at time t, Q ki,t Represents the reactive power flow in branch ki at time t.

[0110] The optimization model for minimizing the construction cost of static VAR generator can be expressed as:

[0111]

[0112] Among them, the constraint condition expression (1-20) satisfies all constraints of equations (1-1) to (1-7), equations (1-9) to (1-11), equations (1-13) to (1-15), and equations (1-17) to (1-19).

[0113] Only the optimal control of the switching of the photovoltaic system operation mode is considered, and 6 photovoltaic penetration rates (0.3-0.8) and 10 load expansion rates (1.1-2.0) are considered. There are 12 extreme scenarios in the 10 scenarios that cannot meet the voltage safety requirements. According to the optimization model formula (1-20) with the minimum construction cost of the static VAR generator, the installation location and capacity of the static VAR generator under all extreme scenarios are determined, so that the photovoltaic system can meet the voltage safety constraints even in more extreme cases, as shown in Table 1.

[0114] Table 11 SVG configuration solutions for 12 extreme scenarios

[0115]

[0116] According to the installed capacity of the static VAR generator, the 12 extreme scenarios are named Scenario 0 to Scenario 11 from high to low. The static VAR generator and the photovoltaic system operation mode switching are used for collaborative optimization, and there is an optimal collaborative optimization configuration scheme for each extreme scenario. For the 12 extreme scenarios, the voltage safety requirements can be met after the static VAR generator is installed.

[0117] Step 4: Analyze and calculate the comprehensive cost caused by planning and constructing static VAR generators according to different extreme scenarios, and analyze the construction cost and operation loss, including:

[0118] In the actual planning process, it is necessary to comprehensively consider the cost of each solution in Table 1 under all scenarios to determine the optimal construction plan. Therefore, it is necessary to conduct an economic comparative analysis of the coordinated voltage support scheme of the static VAR generator and the photovoltaic system operation mode. The costs considered mainly include the construction cost of the static VAR generator, the photovoltaic active power loss, and the power outage loss caused by the failure to meet the voltage requirements in extreme scenarios. Specifically, the photovoltaic active power loss is obtained by applying a static VAR generator configuration scheme to all scenarios and optimizing the photovoltaic operation mode to obtain the total active power loss. This loss is compared with the total active power loss calculated by formula (1-16) and subtracted to obtain the increase in photovoltaic active power output. The difference between the power outage loss and the photovoltaic active power increase It is called operating loss.

[0119]

[0120] in, is the difference between the power outage loss and the PV active power increase under scenario y, i.e., the operating loss. is the power outage loss in scenario y; is the increase in total photovoltaic active output in scenario y; C P,loss,0 is the total active power loss calculated by formula (1-16); is the total photovoltaic active power loss under the optimal control of the operation mode of the static VAR generator and the photovoltaic grid-connected converter in scenario y; Ω Y is the set of all scenarios that require the installation of static VAR generators; R(y) is the set of extreme power outage scenarios corresponding to each extreme scenario y c is the power outage loss coefficient, which is taken as 1 here; w y is the load expansion rate corresponding to scenario y; p r is the probability of the power outage scenario r. For 60 scenarios consisting of 6 PV penetration rates and 10 load expansion rates, assuming that the probability of each scenario is 1 / 60, the comprehensive cost of the static VAR generator SVG is shown in Table 2. The construction cost and operation loss of the static VAR generator SVG for each scenario are shown in Table 2. Figure 7 shown.

[0121] Table 2 Comparison of comprehensive costs of SVG construction

[0122]

[0123] refer to Figure 7 , from scenario 0 to scenario 11, as the configuration capacity of the static VAR generator SVG decreases, the operating loss gradually increases. This is because the reactive power provided by the static VAR generator SVG is not enough to meet the voltage safety requirements of the photovoltaic system, resulting in an increase in the probability of power outages and power outage losses. In addition, since the photovoltaic system needs to provide more reactive voltage support, its active power loss also increases. These two factors together lead to an increase in total operating losses.

[0124] Step 5: Use the net present value method to determine the optimal static VAR generator construction plan, including:

[0125] In the actual planning process, it is necessary to comprehensively consider the configuration capacity and operating losses of the static VAR generator SVG. Although a higher configuration capacity of the static VAR generator SVG will increase the construction cost, it can reduce the operating losses. The net present value method can be used to convert all future operating losses to the present, and then add them to the construction cost of the static VAR generator to obtain the net present value cost of each plan, so as to determine the optimal static VAR generator construction plan.

[0126] The formula for the net present value method is:

[0127]

[0128] Where NPV is the net present value, CF is t is the operating loss in period t, r is the discount rate, n is the life cycle of the static VAR generator SVG, t is time, and C0 is the initial static VAR generator construction cost.

[0129] Table 3 Comparison of SVG construction net present value costs

[0130]

[0131] As shown in Table 3, the net present value cost of planning and constructing SVG according to scenario 1 is the lowest, that is, installing SVG with a total capacity of 0.92MVA at #14, #15, #17, #31, and #32. This method comprehensively considers the three costs of SVG construction cost, PV system operation mode switching, and power outage losses to obtain the optimal planning and construction plan.

[0132] The embodiments described above are only part of the embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any ordinary technician in the field can make equivalent replacements or changes according to the technical solutions and inventive concepts of the present invention within the technical scope disclosed by the present invention, and they should be covered by the protection scope of the present invention.

Claims

1. A static VAR generator planning method considering comprehensive construction costs under extreme scenarios, characterized in that: The method comprises the following steps: Step 1: Establish a distribution network power flow model based on second-order cone relaxation; Step 2: Based on the distribution network power flow model, the operation mode of the photovoltaic grid-connected converter in the distribution network is optimized and controlled, switching between the constant power factor mode and the grid voltage support mode to create an optimization model; Step 3: Install static VAR generators at some nodes of the distribution network and establish an optimization model with the minimum construction cost of static VAR generators; Step 4: Analyze the comprehensive cost of the static VAR generator construction plan under different extreme scenarios, and analyze the construction cost and operation loss; Step 5: Use the net present value method to determine the optimal static VAR generator construction plan.

2. The static VAR generator planning method considering the comprehensive construction cost under extreme scenarios as claimed in claim 1 is characterized in that: The expression of the distribution network power flow model based on second-order cone relaxation is as follows: Among them, the expression of the active power balance equation of the distribution network node is: The expression of the reactive power balance equation of the distribution network node is: The expression of the distribution network branch voltage equation is: The constraints of the voltage and current of the distribution network branches are as follows: in, The constraints are: The photovoltaic system operates in constant power factor mode, which is expressed by the following formula: The generator active power injection value at the distribution network node k at time t should meet the upper and lower limits of the generator output. When there is no generator at the k node, the generator active power injection is set to 0. The expression is as follows: The reactive power injection value of the generator at the distribution network node k at time t should meet the upper and lower limits of the generator output. When there is no generator at the k node, the reactive power injection of the generator is set to 0. The expression is as follows: The photovoltaic active power injection and reactive power injection of the distribution network node k at time t must meet the photovoltaic capacity constraint. For nodes without photovoltaic installation, the photovoltaic active and reactive power injection are set to 0. The expressions are as follows: In the above formula, They represent the active power injection of the generator and photovoltaic at node k at time t, They represent the reactive power injection of the generator and photovoltaic at node k at time t, P jk,t , Q jk,t They represent the active power and reactive power flow of branch jk at time t, r jk 、x jk They represent the resistance and reactance of branch jk respectively, l jk,t represents the square of the current in branch jk at time t, They represent the active load and reactive load of node k at time t, w is the load expansion rate, u k,t is the square of the node voltage at node k at time t, represents the capacity of the photovoltaic system at node k, η PV The photovoltaic penetration rate of the entire photovoltaic system, represents the maximum active output value of the photovoltaic system at node k at time t, tanθ k Represents the power factor of the photovoltaic system at node k, Ω E is the set of all nodes in the distribution network, Ω B is the set of all branches of the distribution network, Ω PV is the set of all nodes equipped with photovoltaic systems, Ω gen is the set of all nodes equipped with generators, δ(k) and σ(k) are the parent nodes and child nodes of node k, respectively, T is the set of all moments, u k,t Represents the square of the node voltage of the entire system, U min , U max They represent the lower and upper limits of the node voltage of the entire system, respectively. ik,t represents the active power flow of branch ik at time t, Q ik,t represents the reactive power flow of branch ik at time t, Indicates the upper limit of the current on branch jk, P k gen,min , P k gen,max They represent the lower and upper limits of the active output of the generator at node k, Q k gen,min , Q k gen,max They represent the lower and upper limits of reactive power output of the generator at node k respectively.

3. The static VAR generator planning method considering the comprehensive construction cost under extreme scenarios as claimed in claim 2 is characterized in that: In step 2, based on the distribution network power flow model, the operation mode of the photovoltaic grid-connected converter in the distribution network is optimized and controlled, switching between the constant power factor mode and the grid voltage support mode. The expression of the grid voltage support mode is as follows: The operation mode of the photovoltaic grid-connected converter in the distribution network is optimized and controlled so that the operation mode of the photovoltaic grid-connected converter in the distribution network is switched between a constant power factor mode and a grid voltage support mode.

4. The static VAR generator planning method considering comprehensive construction costs under extreme scenarios as described in claim 3 is characterized in that: The process of creating an optimization model is as follows: The big M method is used to write the photovoltaic system operating in constant power factor mode and in grid voltage support mode together, and the expression is as follows: Where M is an infinite positive number, m k,t The value of determines the operation mode of the photovoltaic system, m k,t = 0, the photovoltaic system is in constant power factor mode, m k,t =1 when the photovoltaic system is in the grid voltage support mode; The expression of an optimization model is:

5. The static VAR generator planning method considering comprehensive construction costs under extreme scenarios as claimed in claim 1, characterized in that: The optimization model for establishing the minimum construction cost of static VAR generator includes the following contents: The related constraint expressions of static VAR generator are: in, is the reactive power output of the static VAR generator at node k at time t, is the minimum reactive power output of the static VAR generator at node k, is the maximum reactive power output of the static VAR generator at node k, Ω SVG is the set of all nodes equipped with static VAR generators; The active power balance equation and reactive power balance equation of the distribution network node are transformed into: In the above formula, P k,t represents the active power flow of node k at time t, Q ki,t represents the reactive power flow of branch ki at time t; the optimization model with the minimum construction cost of static VAR generator is expressed as:

6. The static VAR generator planning method considering comprehensive construction costs under extreme scenarios as claimed in claim 1, characterized in that: The comprehensive cost of the static VAR generator construction scheme under different extreme scenarios is analyzed, and the construction cost and operation loss are analyzed, and the following formula is used to express it: in, is the difference between the power outage loss and the PV active power increase under scenario y, i.e., the operating loss. is the power outage loss in scenario y; is the increase in total photovoltaic active output in scenario y; C P,loss,0 is the total active power loss; is the total photovoltaic active power loss of the coordinated optimization of the static VAR generator and photovoltaic operation mode under scenario y; Ω Y is the set of all scenarios that require the installation of static VAR generators; R(y) is the set of extreme power outage scenarios corresponding to each extreme scenario y; c is the power outage loss coefficient; w y is the load expansion rate corresponding to scenario y; p r is the probability of power outage scenario r occurring.

7. The static VAR generator planning method considering comprehensive construction costs under extreme scenarios as claimed in claim 1, characterized in that: The optimal static VAR generator construction plan determined by the net present value method includes: All future operating losses are converted to the present through the net present value method, and then added to the initial static VAR generator construction cost to obtain the net present value cost of each plan. The optimal construction plan is determined by comparing the net present value costs. The net present value method formula is: Where NPV is the net present value, CF is t is the operating loss in period t, r is the discount rate, n is the life cycle of the STATCOM, t is the time, and C0 is the initial STATCOM construction cost.

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