A method for selecting a site and determining the capacity of a static synchronous series compensator and a terminal

Abstract

The present invention discloses a method and a terminal for site selection and sizing of a static synchronous series compensator. In a power system connected to a wind farm, a node power injection model after a static synchronous series compensator SSSC is connected to the power system is first established, thereby generating a power flow calculation model containing the SSSC; then, in site selection, multiple typical wind power scenarios are generated according to the wind speed of the connected wind farm, based on multiple scenarios, with the minimum transmission congestion index as the objective function, an SSSC optimization site selection model is established according to the power flow calculation model, thereby determining the optimal installation position and configuration capacity of the SSSC; finally, in sizing, for a specific scenario, with the minimum active power loss of the power system as the objective function, an SSSC sizing optimization model is established according to the power flow calculation model, thereby determining the control parameters of the SSSC during actual operation, thereby alleviating the transmission congestion problem caused by the connection of large-scale wind power to the power system.

Description

Technical Field

[0001] The present invention relates to the technical field of power electronics, and in particular to a method for selecting a site and determining the capacity of a static synchronous series compensator and a terminal. Background Art

[0002] Offshore wind power has the advantages of not occupying land resources, high wind speed, high wind power utilization hours, and small output fluctuation. However, due to the abundance of offshore wind resources, the output level of wind turbines is high or even full, which makes the transmission congestion problem more significant. This also limits the installed capacity of offshore wind power and restricts the scale of offshore wind power grid connection. Flexible control equipment can alleviate the transmission congestion problem by flexibly controlling the tidal current. Static synchronous series compensator (SSSC) can control the tidal current by adjusting the voltage source amplitude and phase size. In addition, SCCC also has the functions of improving system stability and avoiding resonance. However, the different installation locations of SSSC have different effects on the system. It is crucial to determine the installation line and capacity of SSSC to improve the transmission congestion problem after the access of high-penetration wind power.

[0003] Currently, there are few studies on the site selection and sizing of SSSCs, and they mainly focus on traditional power systems, without considering the impact of the uncertainty of renewable energy output. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method for site selection and capacity determination of a static synchronous series compensator and a terminal for solving the transmission congestion problem caused by large-scale wind power access to a power system.

[0005] In order to solve the above technical problems, a technical solution adopted by the present invention is:

[0006] A method for site selection and capacity determination of a static synchronous series compensator comprises the following steps:

[0007] S1, establishing a node power injection model after the static synchronous series compensator is connected to the power system, and generating a power flow calculation model including the static synchronous series compensator according to the node power injection model;

[0008] S2. Determine multiple typical wind power scenarios according to the wind speed of the wind farm connected to the power system, establish a static synchronous series compensator optimization site selection model according to the power flow calculation model based on the multiple typical wind power scenarios and take the minimum transmission congestion index as the objective function, and determine the optimal configuration line and capacity of the static synchronous series compensator according to the static synchronous series compensator optimization site selection model;

[0009] S3. Based on the wind power scenario where the static synchronous series compensator is located and taking the minimization of active power loss of the power system as the objective function, a static synchronous series compensator sizing optimization model is established according to the power flow calculation model, and the control variables of the static synchronous series compensator during actual operation are determined according to the static synchronous series compensator sizing optimization model.

[0010] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0011] A static synchronous series compensator site selection and capacity determination terminal comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0012] S1, establishing a node power injection model after the static synchronous series compensator is connected to the power system, and generating a power flow calculation model including the static synchronous series compensator according to the node power injection model;

[0013] S2. Determine multiple typical wind power scenarios according to the wind speed of the wind farm connected to the power system, establish a static synchronous series compensator optimization site selection model according to the power flow calculation model based on the multiple typical wind power scenarios and take the minimum transmission congestion index as the objective function, and determine the optimal configuration line and capacity of the static synchronous series compensator according to the static synchronous series compensator optimization site selection model;

[0014] S3. Based on the wind power scenario where the static synchronous series compensator is located and taking the minimization of active power loss of the power system as the objective function, a static synchronous series compensator sizing optimization model is established according to the power flow calculation model, and the control variables of the static synchronous series compensator during actual operation are determined according to the static synchronous series compensator sizing optimization model.

[0015] The beneficial effects of the present invention are as follows: in a power system connected to a wind farm, firstly, a node power injection model is established after a static synchronous series compensator SSSC is connected to the power system, thereby generating a power flow calculation model including the SSSC; then, in terms of site selection, a plurality of typical wind power scenarios are generated according to the wind speed of the connected wind farm, based on multiple scenarios, with the minimum transmission congestion index as the objective function, an SSSC optimization site selection model is established according to the power flow calculation model, thereby determining the optimal installation position and configuration capacity of the SSSC; finally, in terms of sizing, for a specific scenario, with the minimum active power loss of the power system as the objective function, an SSSC sizing optimization model is established according to the power flow calculation model, thereby determining the control parameters of the SSSC during actual operation, thereby alleviating the transmission congestion problem caused by the connection of large-scale wind power to the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A flowchart of the steps of a method for site selection and capacity determination of a static synchronous series compensator according to an embodiment of the present invention;

[0017] Figure 2 It is a structural schematic diagram of a site selection and capacity-fixing terminal of a static synchronous series compensator according to an embodiment of the present invention;

[0018] Figure 3 A schematic diagram of an SSSC equivalent model in a method for site selection and capacity determination of a static synchronous series compensator according to an embodiment of the present invention;

[0019] Figure 4 A schematic diagram of a SSSC node power injection model in a method for site selection and sizing of a static synchronous series compensator according to an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to explain the technical content, achieved objectives and effects of the present invention in detail, the following is an explanation in combination with the implementation modes and the accompanying drawings.

[0021] Please refer to Figure 1 A method for selecting a site and determining the capacity of a static synchronous series compensator comprises the following steps:

[0022] S1, establishing a node power injection model after the static synchronous series compensator is connected to the power system, and generating a power flow calculation model including the static synchronous series compensator according to the node power injection model;

[0023] S2. Determine multiple typical wind power scenarios according to the wind speed of the wind farm connected to the power system, establish a static synchronous series compensator optimization site selection model according to the power flow calculation model based on the multiple typical wind power scenarios and take the minimum transmission congestion index as the objective function, and determine the optimal configuration line and capacity of the static synchronous series compensator according to the static synchronous series compensator optimization site selection model;

[0024] S3. Based on the wind power scenario where the static synchronous series compensator is located and taking the minimization of active power loss of the power system as the objective function, a static synchronous series compensator sizing optimization model is established according to the power flow calculation model, and the control variables of the static synchronous series compensator during actual operation are determined according to the static synchronous series compensator sizing optimization model.

[0025] From the above description, it can be seen that the beneficial effects of the present invention are: in the power system connected to the wind farm, firstly, a node power injection model after the static synchronous series compensator SSSC is connected to the power system is established, thereby generating a power flow calculation model including the SSSC; then, in terms of site selection, multiple typical wind power scenarios are generated according to the wind speed of the connected wind farm, based on multiple scenarios, with the minimum transmission congestion index as the objective function, an SSSC optimization site selection model is established according to the power flow calculation model, thereby determining the optimal installation position and configuration capacity of the SSSC; finally, in terms of sizing, for a specific scenario, with the minimum active power loss of the power system as the objective function, an SSSC sizing optimization model is established according to the power flow calculation model, thereby determining the control parameters of the SSSC during actual operation, thereby alleviating the transmission congestion problem caused by the connection of large-scale wind power to the power system.

[0026] Further, the determining of a plurality of typical wind power scenarios according to the wind speed of the wind farm connected to the power system includes:

[0027] Discretizing the continuous wind speed of the wind farm connected to the power system to obtain multiple typical wind power scenarios;

[0028] Determining the probability of occurrence of each of the plurality of typical wind power scenarios according to the historical data of the wind farm;

[0029] The objective function in step S2 is established according to the probability of occurrence of each wind power scenario in the multiple typical wind power scenarios.

[0030] From the above description, it can be seen that multiple typical wind power scenarios are determined according to the wind speed of the wind farm connected to the power system, and the probability of each typical wind power scenario is determined according to the historical data of the wind farm. When determining the objective function, the probability of occurrence of each wind power scenario is considered, which further improves the accuracy of the determined objective function, thereby ensuring the accuracy of the determined SSSC site selection.

[0031] Furthermore, the objective function in step S2 is:

[0032]

[0033] In the formula, represents the active power transmitted by the i-th line in scenario s, represents the maximum active power allowed to be transmitted by line i, NL and Senses represent the number of lines and the number of scenarios in the power system respectively, s represents the probability of scene s appearing;

[0034] The constraint conditions corresponding to the objective function include power system flow constraints, generator constraints, safety constraints and static synchronous series compensator constraints.

[0035] From the above description, it can be seen that the objective function takes into account the active power and maximum active power of each line and each scenario in the power system, and also takes into account the probability of occurrence of each scenario, thereby constructing the power system transmission line congestion index, and also sets the constraints corresponding to the objective function, including power system flow, generators, safety and SSSC, to ensure the rationality and reliability of the set objective function, and to more accurately determine the optimal configuration line and capacity of SCCC.

[0036] Furthermore, the objective function in step S3 is:

[0037]

[0038] Where f(x,u) is the active network loss function with respect to variables x and u, NL represents the number of power lines in the power system, and P ij represents the active power flow on the i side of line ij, P ji represents the active power flow on the j side of the Pji line ij, G ij Expressed as the conductance of line ij, U i and U j are the voltage amplitudes of nodes i and j respectively, θ ij represents the voltage phase angle difference between nodes i and j;

[0039] The constraint conditions corresponding to the objective function include that the transmission line does not get blocked, the voltage does not exceed the limit, and all operating variables do not exceed the limit.

[0040] From the above description, it can be seen that the objective function takes into account the active power loss of each line in the power system, and also sets constraints corresponding to the objective function, including that the transmission line does not get blocked, the voltage does not exceed the limit, and all operating variables do not exceed the limit, thereby ensuring the rationality and reliability of the set objective function and being able to more accurately determine the control variables during the actual operation of the SCCC.

[0041] Furthermore, the static synchronous series compensator optimal site selection model and the static synchronous series compensator constant capacity optimization model are both solved by using a particle swarm optimization algorithm.

[0042] From the above description, it can be seen that when solving the SSSC optimal site selection model and the SSSC constant capacity optimization model, the particle swarm optimization algorithm is used to solve them. With the help of the particle swarm optimization algorithm, the SSSC can be sited and capacity determined efficiently and accurately.

[0043] Please refer to Figure 2, a static synchronous series compensator site selection and capacity determination terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0044] S1, establishing a node power injection model after the static synchronous series compensator is connected to the power system, and generating a power flow calculation model including the static synchronous series compensator according to the node power injection model;

[0045] S2. Determine multiple typical wind power scenarios according to the wind speed of the wind farm connected to the power system, establish a static synchronous series compensator optimization site selection model according to the power flow calculation model based on the multiple typical wind power scenarios and take the minimum transmission congestion index as the objective function, and determine the optimal configuration line and capacity of the static synchronous series compensator according to the static synchronous series compensator optimization site selection model;

[0046] S3. Based on the wind power scenario where the static synchronous series compensator is located and taking the minimization of active power loss of the power system as the objective function, a static synchronous series compensator sizing optimization model is established according to the power flow calculation model, and the control variables of the static synchronous series compensator during actual operation are determined according to the static synchronous series compensator sizing optimization model.

[0047] Further, the determining of a plurality of typical wind power scenarios according to the wind speed of the wind farm connected to the power system includes:

[0048] Discretizing the continuous wind speed of the wind farm connected to the power system to obtain multiple typical wind power scenarios;

[0049] Determining the probability of occurrence of each of the plurality of typical wind power scenarios according to the historical data of the wind farm;

[0050] The objective function in step S2 is established according to the probability of occurrence of each wind power scenario in the multiple typical wind power scenarios.

[0051] Furthermore, the objective function in step S2 is:

[0052]

[0053] In the formula, represents the active power transmitted by the i-th line in scenario s, represents the maximum active power allowed to be transmitted by line i, NL and Senses represent the number of lines and the number of scenarios in the power system respectively, s represents the probability of scene s appearing;

[0054] The constraint conditions corresponding to the objective function include power system flow constraints, generator constraints, safety constraints and static synchronous series compensator constraints.

[0055] Furthermore, the objective function in step S3 is:

[0056]

[0057] Where f(x,u) is the active network loss function with respect to variables x and u, NL represents the number of power lines in the power system, and P ij represents the active power flow on the i side of line ij, P ji represents the active power flow on the j side of the Pji line ij, G ij Expressed as the conductance of line ij, U i and U j are the voltage amplitudes of nodes i and j respectively, θ ij represents the voltage phase angle difference between nodes i and j;

[0058] The constraint conditions corresponding to the objective function include that the transmission line does not get blocked, the voltage does not exceed the limit, and all operating variables do not exceed the limit.

[0059] Furthermore, the static synchronous series compensator optimal site selection model and the static synchronous series compensator constant capacity optimization model are both solved by using a particle swarm optimization algorithm.

[0060] The above-mentioned static synchronous series compensator site selection and capacity determination method and terminal of the present application can be applied to the application scenario of wind power access to the power system, and the following is an explanation through specific implementation methods:

[0061] Embodiment 1

[0062] Please refer to Figure 1 A method for site selection and capacity determination of a static synchronous series compensator is applicable to a power system including a wind farm, the power system including but not limited to offshore wind power, thermal power units, loads and transmission channels between them, the method comprising the steps of:

[0063] S1, establishing a node power injection model after the static synchronous series compensator is connected to the power system, and generating a power flow calculation model including the static synchronous series compensator according to the node power injection model;

[0064] Specifically, according to the Norton principle, the impact of SSSC on the power system is converted into node injection power, and the SSSC equivalent model is established, such as Figure 3 As shown, the corresponding SSSC node power injection model is as follows Figure 4 As shown;

[0065] according to Figure 4As shown in Figure 2, the additional injected power caused by the SSSC being connected to the power system is:

[0066] P i(inj) =-V i V se [g ij cos(θ i -θ se )+b ij sin(θ i -θ se )]

[0067] Q i(inj) =-V i V se [g ij sin(θ i -θ se )-b ij cos(θ i -θ se )]

[0068] P j(inj) =V j V se [g ij cos(θ j -θ se )+b ij sin(θ j -θ se )]

[0069] Q j(inj) =V j V se [g ij sin(θ j -θ se )-b ij cos(θ j -θ se )]

[0070] Where V i represents the voltage amplitude of node i, θ i represents the voltage phase angle of node i; V j represents the voltage amplitude at node j, θ j represents the voltage phase angle at node j, V se represents the voltage amplitude of the equivalent voltage source of the SSSC connected in series in the circuit, θ se It represents the voltage phase angle of the equivalent voltage source of the SSSC connected in series in the line, g ij +jb ij represents the equivalent line admittance of the SSSC connected in series in the line; P i(ing) , Q i(ing) , P j(ing), Q j(ing) It represents the additional injected power caused by the SSSC being connected to the power system;

[0071] When the voltage source amplitude V se When the value of and the SSSC voltage compensation direction are known, the SSSC additional node injection power can be calculated from the node voltage value of the previous iteration. In an optional implementation, the initial voltage amplitude of the node can be set to 1;

[0072] S2. Determine multiple typical wind power scenarios according to the wind speed of the wind farm connected to the power system, establish a static synchronous series compensator optimization site selection model according to the power flow calculation model based on the multiple typical wind power scenarios and take the minimum transmission congestion index as the objective function, and determine the optimal configuration line and capacity of the static synchronous series compensator according to the static synchronous series compensator optimization site selection model;

[0073] The determining of a plurality of typical wind power scenarios according to the wind speed of the wind farm connected to the power system includes:

[0074] Discretizing the continuous wind speed of the wind farm connected to the power system to obtain multiple typical wind power scenarios;

[0075] The unit output is proportional to the cube of the wind speed, and the expression is as follows:

[0076]

[0077] Where P W is the active power output of the wind turbine, v is the wind speed, and v co is the cut-out speed, v ci is the cutting speed, v rate is the rated speed, P rate is the rated active output of the unit;

[0078] After a plurality of typical wind power scenarios are determined, the probability of occurrence of each wind power scenario in the plurality of typical wind power scenarios is determined according to historical data of the wind farm;

[0079] The objective function in step S2 is established according to the probability of occurrence of each wind power scenario in the multiple typical wind power scenarios;

[0080] By using multiple scenarios in randomized optimization, the optimal installation route and installation capacity of SSSC considering the uncertainty of wind power output are obtained, which is more robust.

[0081] S3. Based on the wind power scenario where the static synchronous series compensator is located and taking the minimization of active power loss of the power system as the objective function, a static synchronous series compensator sizing optimization model is established according to the power flow calculation model, and the control variables of the static synchronous series compensator during actual operation are determined according to the static synchronous series compensator sizing optimization model.

[0082] Embodiment 2

[0083] This embodiment further defines how to determine the objective function, specifically:

[0084] After the SSSC optimization site selection model is established in step S2, the optimal installation line and configuration capacity of the SSSC can be obtained from the optimization site selection model. The model objective function is to minimize the blocking index of the power system transmission line under multiple scenarios. The constraints include power system flow constraints, generator constraints, safety constraints and SSSC constraints. The control variables are the SSSC installation location and the equivalent voltage amplitude of the SSSC.

[0085] The objective function is:

[0086]

[0087] In the formula, represents the active power transmitted by the i-th line in scenario s, represents the maximum active power allowed to be transmitted by line i, NL and Senses represent the number of lines and the number of scenarios in the power system respectively, s represents the probability of scene s appearing;

[0088] The power system flow constraints are:

[0089]

[0090]

[0091] In the formula, and are the input active power and output active power of node i in scenario s respectively; and are the input reactive power and output reactive power of node i in scenario s respectively; V i,s is the voltage amplitude of node i in scenario s, V j,s is the voltage amplitude of node j in scenario s, G ij and B ij are the conductance and susceptance between nodes i and j, respectively, δ ij,s is the voltage phase angle difference between nodes i and j in scenario s, and N is the number of nodes;

[0092] The generator constraints are:

[0093]

[0094]

[0095]

[0096] In the formula, They represent the lower and upper limits of the voltage amplitude at the generator terminals, respectively. Respectively represent the lower and upper limits of active power output, They represent the lower and upper limits of reactive power output respectively; NG represents the number of generator nodes;

[0097] The safety constraints are:

[0098]

[0099]

[0100]

[0101] In the formula, Respectively represent the lower and upper limits of the voltage amplitude of node i, Indicates the upper limit of the actual transmission capacity of the branch. Indicates the upper limit of the active power of the branch, NL indicates the number of circuits in the power system, and NB indicates the number of PQ nodes;

[0102] The static synchronous series compensator SSSC constraint is:

[0103]

[0104] Indicates the upper limit of the voltage amplitude of the SSSC equivalent voltage source;

[0105] When establishing the SSSC constant capacity optimization model in step S3, for a specific scenario, the objective function is to minimize the active power loss of the power system, the inequality constraints are that the transmission line does not get blocked, the voltage does not exceed the limit, and all operating variables do not exceed the limit, the power flow equation is the equality constraint, and the control variables are the transformer ratio, the generator reactive power output and the SSSC compensation capacity;

[0106] The objective function is:

[0107]

[0108] Where f(x,u) is the active network loss function with respect to variables x and u, NL represents the number of power lines in the power system, and P ij represents the active power flow on the i side of line ij, P jirepresents the active power flow on the j side of the Pji line ij, G ij Expressed as the conductance of line ij, U i and U j are the voltage amplitudes of nodes i and j respectively, θ ij represents the voltage phase angle difference between nodes i and j;

[0109] The power flow equation is:

[0110]

[0111] Where P i and Q i are the injected active power and reactive power of node i, V i and V j Represent the voltage amplitude of nodes i and j respectively, N represents the number of nodes, G ij and B ij are the conductance and susceptance between nodes i and j, respectively, θ ij represents the voltage phase angle difference between nodes i and j;

[0112] The constraints are:

[0113]

[0114]

[0115] V i lower ≤V i ≤V i upper ,i=1,...,N

[0116]

[0117]

[0118] T i lower ≤T i ≤T i upper ,i=1,...,NT

[0119]

[0120] In the formula, Respectively represent the lower and upper limits of active power output, Respectively represent the lower and upper limits of reactive power output, V i lower 、V i upper Respectively represent the lower and upper limits of the node voltage amplitude; They represent the lower and upper limits of the actual transmission capacity of the branch, respectively. They represent the lower and upper limits of the active power of the branch, respectively. They represent the lower and upper limits of the voltage amplitude of the SSSC equivalent voltage source, NL represents the number of branches in the power system, and T i lower , T i upper They respectively represent the lower limit and upper limit of the transformation ratio of the i-th transformer branch, and NT represents the number of transformer branches.

[0121] Wherein, the static synchronous series compensator optimal site selection model and the static synchronous series compensator constant capacity optimization model are both solved by using a particle swarm optimization algorithm;

[0122] The penalty function is used to process the inequality constraints. The objective function considering the penalty function is:

[0123]

[0124] Where f(x,u) is the objective function, P BF , Q F 、V F , P F , S F They are respectively the balanced generator active output, generator reactive output, PQ node voltage amplitude, line active power flow, and line apparent power penalty function terms. η Q , η V , η P , η S are the corresponding penalty factors. BF For example, the specific expression is:

[0125]

[0126] In the formula, They are the active power output of the generator and the upper and lower limits of the active power output respectively.

[0127] Embodiment 3

[0128] Please refer to Figure 2 A site selection and sizing terminal for a static synchronous series compensator includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, each step of a site selection and sizing method for a static synchronous series compensator described in Embodiment 1 or Embodiment 2 is implemented.

[0129] In summary, the present invention provides a method and terminal for site selection and sizing of a static synchronous series compensator. In a power system connected to a wind farm, a node power injection model is first established after the static synchronous series compensator SSSC is connected to the power system, thereby generating a power flow calculation model including the SSSC; then, in site selection, multiple typical wind power scenarios are generated according to the wind speed of the connected wind farm, based on multiple scenarios, the transmission congestion index is minimized as the objective function, the objective function is established according to the probability of occurrence of each wind power scenario in the multiple typical wind power scenarios, and an SSSC optimization site selection model is established according to the power flow calculation model, thereby determining the optimal installation position and configuration capacity of the SSSC, fully considering the uncertainty of the output of new energy, and improving the robustness of the connected SSSC; finally, in sizing, for a specific scenario, the power system active loss is minimized as the objective function, and an SSSC sizing optimization model is established according to the power flow calculation model, thereby determining the control parameters of the SSSC during actual operation, thereby alleviating the transmission congestion problem caused by the connection of large-scale wind power to the power system.

[0130] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for site selection and capacity determination of static synchronous series compensator. It is characterized in that Includes steps: S1, establishing a node power injection model after the static synchronous series compensator is connected to the power system, and generating a power flow calculation model including the static synchronous series compensator according to the node power injection model; S2. Determine multiple typical wind power scenarios according to the wind speed of the wind farm connected to the power system, establish a static synchronous series compensator optimization site selection model according to the power flow calculation model based on the multiple typical wind power scenarios and take the minimum transmission congestion index as the objective function, and determine the optimal configuration line and capacity of the static synchronous series compensator according to the static synchronous series compensator optimization site selection model; S3. Based on the wind power scenario where the static synchronous series compensator is located, taking the minimum active power loss of the power system as the objective function, a static synchronous series compensator constant capacity optimization model is established according to the power flow calculation model, and the control variables of the static synchronous series compensator during actual operation are determined according to the static synchronous series compensator constant capacity optimization model; Determining a plurality of typical wind power scenarios according to the wind speed of the wind farm connected to the power system includes: Discretizing the continuous wind speed of the wind farm connected to the power system to obtain multiple typical wind power scenarios; Determining the probability of occurrence of each of the plurality of typical wind power scenarios according to the historical data of the wind farm; The objective function in step S2 is established according to the probability of occurrence of each wind power scenario in the multiple typical wind power scenarios; The objective function in step S2 is: In the formula, represents the active power transmitted by the i-th line in scenario s, represents the maximum active power allowed to be transmitted by line i, NL and Senses represent the number of lines and the number of scenarios in the power system respectively, s represents the probability of scene s appearing; The constraints corresponding to the objective function include power system flow constraints, generator constraints, safety constraints and static synchronous series compensator constraints; The objective function in step S3 is: Where f(x,u) is the active network loss function with respect to variables x and u, NL represents the number of power lines in the power system, and P ij represents the active power flow on the i side of line ij, P ji represents the active power flow on the j side of line ij, G ij Expressed as the conductance of line ij, U i and U j are the voltage amplitudes of nodes i and j respectively, θ ij represents the voltage phase angle difference between nodes i and j; The constraint conditions corresponding to the objective function include that the transmission line does not get blocked, the voltage does not exceed the limit, and all operating variables do not exceed the limit.

2. A static synchronous series compensator site selection and capacity determination terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the computer program, the following steps are implemented: S1, establishing a node power injection model after the static synchronous series compensator is connected to the power system, and generating a power flow calculation model including the static synchronous series compensator according to the node power injection model; S2. Determine multiple typical wind power scenarios according to the wind speed of the wind farm connected to the power system, establish a static synchronous series compensator optimization site selection model according to the power flow calculation model based on the multiple typical wind power scenarios and take the minimum transmission congestion index as the objective function, and determine the optimal configuration line and capacity of the static synchronous series compensator according to the static synchronous series compensator optimization site selection model; S3. Based on the wind power scenario where the static synchronous series compensator is located, taking the minimum active power loss of the power system as the objective function, a static synchronous series compensator constant capacity optimization model is established according to the power flow calculation model, and the control variables of the static synchronous series compensator during actual operation are determined according to the static synchronous series compensator constant capacity optimization model; Determining a plurality of typical wind power scenarios according to the wind speed of the wind farm connected to the power system includes: Discretizing the continuous wind speed of the wind farm connected to the power system to obtain multiple typical wind power scenarios; Determining the probability of occurrence of each of the plurality of typical wind power scenarios according to the historical data of the wind farm; The objective function in step S2 is established according to the probability of occurrence of each wind power scenario in the multiple typical wind power scenarios; The objective function in step S2 is: In the formula, represents the active power transmitted by the i-th line in scenario s, represents the maximum active power allowed to be transmitted by line i, NL and Senses represent the number of lines and the number of scenarios in the power system respectively, s represents the probability of scene s appearing; The constraints corresponding to the objective function include power system flow constraints, generator constraints, safety constraints and static synchronous series compensator constraints; The objective function in step S3 is: Where f(x,u) is the active network loss function with respect to variables x and u, NL represents the number of power lines in the power system, and P ij represents the active power flow on the i side of line ij, P ji represents the active power flow on the j side of line ij, G ij Expressed as the conductance of line ij, U i and U j are the voltage amplitudes of nodes i and j respectively, θ ij represents the voltage phase angle difference between nodes i and j; The constraint conditions corresponding to the objective function include that the transmission line does not get blocked, the voltage does not exceed the limit, and all operating variables do not exceed the limit; The static synchronous series compensator optimal site selection model and the static synchronous series compensator constant capacity optimization model are both solved by using a particle swarm optimization algorithm.

3. According to the static synchronous series compensator described in claim 2, It is characterized in that The static synchronous series compensator optimal site selection model and the static synchronous series compensator constant capacity optimization model are both solved by using a particle swarm optimization algorithm.

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