Distributed phase modifier locating and sizing method considering voltage stability constraint

Abstract

The invention belongs to the technical field of voltage stabilization of a new energy sending-end system, and provides a distributed phase modifier addressing and sizing method considering voltage stability constraints, which guides phase modifier addressing by evaluating system static voltage stability index distribution, and further plans the capacity of a phase modifier by taking the minimum investment cost and the reliability of system operation as targets. Comprising the following steps: 1) constructing a model of the new energy power system containing the phase modifier; and 2) constructing a voltage stability index based on a power flow equation solution theory. According to the distributed phase modifier addressing and sizing method considering the voltage stability constraint, the static voltage stability index distribution of the system is evaluated to guide phase modifier addressing, and then the capacity of the phase modifier is planned with the minimum investment cost and the reliability of system operation as targets. Example analysis shows that the method can obviously improve the voltage support strength of the high-proportion new energy system and improve the voltage safety of the system during operation by configuring fewer phase modifiers.

Description

Technical Field

[0001] This invention belongs to the field of voltage stabilization technology for new energy transmission systems. It proposes a method for optimizing the configuration of distributed synchronous condensers by first screening candidate nodes using voltage stability indicators and then solving the optimization model. Background Technology

[0002] With the advancement of energy transition, the proportion of new energy power generation such as wind power and photovoltaics, as well as high-voltage direct current transmission, in the power system is increasing year by year, and the power grid is evolving into a new form containing a high proportion of renewable energy and a high proportion of power electronic equipment. Under this form, the power grid exhibits a low short-circuit ratio, and the voltage support capacity of the power grid is relatively weakened, posing a great challenge to the safe and stable operation of the power system. Therefore, for high-proportion renewable energy power systems, reactive power compensation devices are usually required to improve the voltage stability of the power system and enhance the grid strength. In particular, distributed synchronous condensers, which have become a research hotspot in recent years, have advantages over traditional large-scale synchronous condensers, such as high integration, system stability, short construction period, low unit capacity cost, and good regulation performance. They also have better transient, subtransient, and steady-state performance, which can significantly improve the renewable energy transmission capacity. However, since synchronous condensers are rotating equipment, the investment and maintenance costs are high, and site selection is relatively difficult. Therefore, under the premise of effectively improving the transient voltage stability of the system, it is necessary to study the synchronous condenser layout scheme.

[0003] This paper considers the practical engineering requirements of voltage stability in sending-end systems and proposes an optimized configuration method for distributed synchronous condensers (SCPs) in high-proportion renewable energy sending-end systems to improve grid strength and stability margin. First, the transient voltage propagation characteristics of high-proportion renewable energy sending-end systems are analyzed. Second, a voltage stability index is constructed based on the theory that power flow equations have solutions. Then, an optimized configuration model for SCPs considering the overall equipment configuration cost and the severity of system transient voltage rise is built, and the Grey Wolf algorithm is used to solve the model to obtain the optimized configuration scheme. Finally, simulation experiments are conducted to verify the effectiveness and reliability of the proposed SCP configuration method. Summary of the Invention

[0004] The technical problem this invention aims to solve is that the proportion of new energy power generation such as wind power and photovoltaic power, as well as high-voltage direct current transmission, in the power system is increasing year by year. This leads to a low short-circuit ratio in the power grid, resulting in a relatively weakened voltage support capacity and posing a significant challenge to the safe and stable operation of the power system. Considering the practical engineering requirements for voltage stability in the sending-end system and improving the grid strength and stability margin of large-scale new energy systems, this paper proposes an optimized configuration method for distributed synchronous condensers in high-proportion new energy sending-end systems. The method guides the selection of synchronous condenser locations by evaluating the distribution of static voltage stability indicators of the system, and then plans the synchronous condenser capacity with the goal of minimizing investment costs and maximizing system operational reliability. It includes the following steps, performed sequentially:

[0005] 1) Model construction of new energy power system including synchronous condenser

[0006] Step 1: For a multi-infeed system, the reactance between its grid connection point and collection point is expressed by the short-circuit capacity as follows:

[0007]

[0008] The current injected into the system from the collection point is the sum of the currents injected at each grid connection point:

[0009]

[0010] The relationship between the voltage at grid connection point i and the scale of new energy sources and the short-circuit capacity of the system in the fault steady-state voltage security problem of multi-infeed systems is as follows:

[0011]

[0012] Further analysis of the relationship between voltage and power at each grid connection point reveals that the ratio of the horizontal voltage components between grid connection points i and j and the collection point is:

[0013]

[0014] Based on the above formula, an active power influence factor describing the power relationship between grid connection point j and grid connection point i is proposed:

[0015]

[0016] In the formula K P,ji The active power influence factor of grid connection point j on grid connection point i can be calculated using reactance and voltage. When i = j, K P,ii =1. K P,ij Substituting into the following equation, and expressing the power at other points in terms of the power at grid connection point i, and taking into account the above equation, we obtain the voltage security analysis model for the multi-infeed system as follows:

[0017]

[0018] In multi-infeed systems, the main influencing factors on steady-state voltage safety after a fault are the same as those in single-infeed systems, which are affected by the scale of new energy sources and short-circuit capacity.

[0019] Step 2: After the synchronous condenser is connected to a node in the AC system, it is equivalent to adding a ground branch to the AC system. Therefore, the influence of the synchronous condenser branch must be considered in every element of the impedance matrix. Assuming the target AC system to which the synchronous condenser is connected has n nodes, the impedance matrix Z before the synchronous condenser is connected can be expressed as:

[0020]

[0021] In the formula: Z pq This represents the impedance between any two nodes.

[0022] After the synchronous condenser is connected, node b gains a ground-to-ground branch. According to the method of adding branches, the impedance between nodes p and q can be expressed as:

[0023]

[0024] In the formula: Z bb Z is the self-impedance of node b. pb Z represents the mutual impedance between node b and node p. qb Let be the mutual impedance between node b and node q.

[0025] Combining the above two equations, we can obtain the multi-infeed short-circuit ratio of the i-th DC line after the synchronous condenser is connected:

[0026]

[0027] The above formula is quite complex and difficult to analyze, so we will simplify it further:

[0028]

[0029] In summary, the addition of a synchronous condenser branch to the system reduces the number of arbitrary elements in the impedance matrix, increases the multi-infeed short-circuit ratio, and enhances the system's voltage support capability for the converter bus. The short-circuit ratio is used to characterize the strength of the grid voltage support; a high short-circuit ratio indicates a strong network, meaning that switching loads or parallel filters will not cause large changes in voltage amplitude. Conversely, a low short-circuit ratio indicates a weak network and system instability. Therefore, in the event of a system fault, activating the synchronous condenser can increase the system's short-circuit ratio, thereby improving system stability.

[0030] Step 3: In the new energy grid-connected system, the new energy input power from each grid-connected point is collected at the collection point and transmitted through the collection line. The short-circuit ratio at the collection point is:

[0031]

[0032] Where: SCR POI S is the short-circuit ratio at the convergence point; ∑ To inject total power into each grid connection point.

[0033] Installing a synchronous condenser at the collection point can effectively improve the system voltage support strength and mitigate the problem of excessively low voltage that may occur after fault clearance in the renewable energy grid-connected system, thereby enhancing the system's ability to accommodate renewable energy. The mathematical analysis model for post-fault steady-state voltage safety is derived. After power balancing, the relationship between the short-circuit capacity provided by the AC system at the collection point, active power, and the voltage at grid connection point i is as follows:

[0034]

[0035] The system short-circuit capacity is differentiated with respect to the grid connection point voltage, and the correlation between the two is analyzed:

[0036]

[0037] When the grid connection point voltage is between 0.9 pu and 1.0 pu, the above formula is greater than 0. The higher the voltage that the grid connection point needs to maintain, the greater the short-circuit capacity required by the system at the convergence point. When the required grid connection point voltage is above 0.9 pu, the minimum short-circuit capacity that the AC system needs to provide is:

[0038]

[0039] 2) Construct voltage stability indices based on the theory that power flow equations have solutions.

[0040] This paper analyzes the impact of synchronous condenser access on power system voltage stability and constructs a voltage stability index based on the theory of power flow solutions. From a mathematical point of view, voltage stability is indicated by the existence of solutions in the power flow equations or power flow extension equations, while voltage instability is indicated by the absence of feasible solutions.

[0041] P j Q represents the sum of the active power of node j itself, the active power of all load nodes after node j, and the active power losses of all branches after node j; j Q represents the sum of the reactive power of node j itself, the reactive power of all load nodes after node j, and the reactive power losses of all branches after node j; D This indicates the capacity of the synchronous condenser configured at node i. The static voltage stability index L, constructed based on the power flow solution theory, is as follows:

[0042]

[0043] Q c =Q D +Q j

[0044] In the formula: U i X represents the node voltage of node i in the system; ij R represents the reactance between nodes i and j; ij This represents the resistance between nodes i and j.

[0045] It can be seen that only nodes whose voltages are stable when L > 0 can be considered stable. The magnitude of L indicates the level of voltage stability; the smaller L is, the closer it is to 0, indicating a lower level of voltage stability at that point. The point with the smallest L is the point where voltage collapse is most likely to occur. Based on this, we calculate the L value for each node using the method described above and take corresponding measures for nodes with smaller L values ​​to prevent voltage collapse.

[0046] 3) Construct a distributed synchronous condenser optimization configuration model that considers the overall equipment configuration cost and the severity of system transient voltage rise.

[0047] Generally, synchronous condensers in power grids can be divided into two types: centralized and distributed. Centralized synchronous condensers refer to large-capacity synchronous condensers centrally configured in UHVDC converter stations, typically located on the AC bus of the converter station. Distributed synchronous condensers, on the other hand, refer to small synchronous condensers dispersedly on the low-voltage side of the renewable energy aggregation station or grid connection point in renewable energy aggregation substations. In HHDC transmission scenarios, large centralized synchronous condensers can be considered for configuration at converter stations. However, this article focuses on the voltage stability problem of power systems with renewable energy grid connection and does not consider the scenario of UHVDC transmission; therefore, it only needs to discuss the configuration of small distributed synchronous condensers.

[0048] Further optimization of the installed capacity of synchronous condensers is needed. To improve the voltage stability of the renewable energy power system, it is necessary to maximize the system voltage level and minimize network losses. Synchronous condensers are not only dynamic reactive power sources that can compensate for the reactive power required by the grid, but also provide rotational inertia to improve the system's inertia level as rotating equipment. However, their construction and maintenance costs are relatively high. Therefore, from an economic perspective, it is necessary to maximize the effect of synchronous condenser configuration while minimizing its cost, achieving optimal economic efficiency. Thus, the optimal configuration objective for synchronous condensers can be derived as follows:

[0049] min F=S+P loss +dU

[0050] In the formula: S represents the total capacity of the camera converter configuration; S i n represents the capacity of the synchronous condensers configured at the renewable energy power stations; n represents the number of renewable energy power stations in the system.

[0051] This paper employs the Grey Wolf optimization algorithm to seek the optimal configuration capacity of distributed synchronous condensers. With the optimization objective of achieving a comprehensive balance between configuration capacity, power loss, and voltage stability margin, and constrained by critical short-circuit ratio, branch current, node voltage, and power balance, a location and capacity determination strategy is constructed to achieve optimal configuration.

[0052] Step 1: Objective function for optimizing distributed synchronous condenser configuration

[0053] The optimal configuration of a camera grading system aims to minimize its capacity while ensuring optimal performance, thereby achieving the best economic efficiency. Therefore, the optimal configuration objective for a camera grading system can be derived as follows:

[0054] min F=S+P loss +dU

[0055] The overall level of camera configuration capacity, system active power loss, and voltage stability margin is minimized.

[0056] (1) Configuration capacity

[0057]

[0058] In the formula: S is the total capacity of the camera converter configuration, S i The capacity of the synchronous condenser at the renewable energy power station is denoted by n, where n is the number of renewable energy power stations in the system.

[0059] (2) Network loss

[0060] The calculation model for grid losses in a new energy power system is as follows:

[0061]

[0062] In the formula: P loss R represents the total active power loss; l represents the number of network branches; R represents the total active power loss. k I is the resistance value of the k-th branch; k Let be the current flowing through the k-th branch.

[0063] (3) Network voltage stability margin

[0064] After synchronous condensers are connected to the renewable energy power system, the system node voltage changes. During peak load periods, connecting synchronous condensers at points with lower node voltages can effectively improve node voltage levels. However, if the capacity of the connected synchronous condensers is too large, the excessive voltage will not meet user expectations. Therefore, a voltage stability margin index is constructed as the objective function for the location and capacity determination of synchronous condensers. Its expression is as follows:

[0065]

[0066] In the above formula: U e U represents the expected value of the node voltage. load U represents the voltage value at the load node. p dU represents the allowable voltage deviation; N represents the number of distribution network nodes; and dU represents the voltage stability margin.

[0067] Step 2: Constraints

[0068] To ensure that the voltage of the sending-end grid can be maintained within a safe range and to have good short-time overload capacity, the minimum short-circuit capacity of the system should be greater than the critical value:

[0069]

[0070] In the formula: S ac，min The minimum short-circuit capacity required for the AC system.

[0071] To ensure the safe and reliable operation of the sending-end power grid, the branch current must meet capacity constraints:

[0072] I l ≤I lmax l = 1, 2, ..., n

[0073] In the formula: I l I is the current flowing through line l; lmax denoted as , where is the maximum current flowing through line l; l represents the number of lines.

[0074] To ensure the safe and reliable operation of the power system and prevent node voltage from exceeding limits, node voltages must meet the following constraints:

[0075] U imin ≤U i ≤U imax i = 1, 2, ..., n

[0076] In the formula: U min and U max These are the lower and upper limits of the node voltage, respectively; U i Let i be the voltage amplitude at node i, and n be the number of nodes.

[0077] To ensure that the sending-end power grid satisfies power balance at all times, the following constraints must be met:

[0078]

[0079] In the formula: Q i,t P i,t G represents the reactive and active power injected into node i during time period t, respectively; ij B ij δ ij,t These represent the conductance, susceptance, and voltage phase angle difference between nodes i and j at time interval t, respectively; n is the number of nodes in the system; V i,t V j,t These are the voltage amplitudes of nodes i and j during time period t, respectively.

[0080] 4) The optimal configuration scheme is obtained by solving the model using the Grey Wolf algorithm.

[0081] Step 1: Read the grid structure, system parameters, and system unit parameters of the power grid;

[0082] Step 2: Calculate the voltage stability index of each node based on the relevant system parameters, and screen out the nodes with poor voltage stability index.

[0083] Step 3: Use the Grey Wolf optimization algorithm to find the best nodes where the system voltage stability index is poor.

[0084] Step 4: Perform simulation verification of the optimization results in a real PSASP example to check the validity and reliability of the results;

[0085] Step 5: The iteration ends, and the configuration results are output.

[0086] This application quantitatively assesses the grid voltage support capacity based on the voltage change curve after a system fault, analyzes the impact of configuring synchronous condensers on the system voltage level, and proposes a distributed synchronous condenser location and capacity grading strategy considering voltage stability constraints. Simulation examples verify the effectiveness of the proposed method.

[0087] Through the above design scheme, the present invention can bring the following beneficial effects:

[0088] 1) The high proportion of new energy access leads to a significant reduction in the voltage support level of the sending-end grid. Distributed synchronous condensers can change the short-circuit capacity of the system by changing the system's impedance matrix, thereby significantly improving the voltage support strength of the system at the convergence point, improving the problem of low voltage that may occur after the fault of the new energy grid-connected system is cleared, and thus improving the system's ability to accept new energy.

[0089] 2) This application proposes a distributed synchronous condenser optimization configuration method that first uses voltage stability index to screen candidate nodes and then solves the optimization model. This method reduces the risk of transient overvoltage in DC transmission system while taking into account economic benefits. It can effectively determine the distributed synchronous condenser configuration scheme for high-proportion new energy DC transmission system, and is highly practical and economical. Attached Figure Description

[0090] The present invention will be further described below with reference to the accompanying drawings and specific embodiments:

[0091] Figure 1 The following is a graph showing the system voltage variation after configuring different numbers of synchronous condensers, based on a distributed synchronous condenser location and capacity setting strategy considering voltage stability constraints according to the present invention:

[0092] Figure 2 The following is a graph showing the system voltage variation after configuring synchronous condensers on different nodes according to a distributed synchronous condenser location and capacity setting strategy considering voltage stability constraints, as described in this invention:

[0093] Figure 3 The flowchart below shows the optimized configuration strategy for distributed synchronous condensers that considers voltage stability constraints, based on the present invention:

[0094] Figure 4 The following is a diagram of a 10-unit, 39-node system including wind turbines, based on a distributed synchronous condenser location and capacity setting strategy considering voltage stability constraints according to the present invention:

[0095] Figure 5 The iterative curve of the Grey Wolf optimization algorithm for a distributed synchronous condenser location and capacity setting strategy considering voltage stability constraints according to the present invention is shown in the figure.

[0096] Figure 6 The diagram shows the voltage changes of system nodes before and after the configuration of a distributed synchronous condenser location and capacity setting strategy considering voltage stability constraints, according to the present invention.

[0097] Figure 7 The following is a distribution diagram of voltage stability index before and after the configuration of a distributed synchronous condenser with voltage stability constraints, according to the present invention:

[0098] Figure 8 This is a comparison chart of the short-circuit ratio before and after the configuration of a distributed synchronous condenser with voltage stability constraints, according to the present invention. Detailed Implementation

[0099] This invention proposes a distributed synchronous condenser location and capacity setting strategy that considers voltage stability constraints, such as... Figures 1 to 8 As shown, it includes the following steps:

[0100] 1. Analyze the voltage support principle after configuring a synchronous condenser in the system to analyze system faults.

[0101] A three-phase ground fault is set at a certain node in the system, and the node voltage change curves after installing 1, 3, and 5 synchronous condensers at that node are shown in the figure. Figure 1 As shown.

[0102] Therefore, it is evident that configuring different numbers of synchronous condensers at the same node in a power system results in varying degrees of bus voltage change after a fault. A larger number of synchronous condensers allows for more timely reactive power compensation and voltage support, more effectively reducing AC system voltage dips, increasing voltage recovery speed, shortening recovery time, and improving AC system voltage stability.

[0103] A three-phase ground fault is set at a certain node of the system, and synchronous condensers are configured at the other three nodes. The bus voltage change curves of the three nodes with synchronous condensers configured are shown in the figure. Figure 2 As shown.

[0104] Therefore, it is evident that when the same number of synchronous condensers are deployed at different nodes in a power system, the degree of change in the system's bus voltage varies after a fault. The closer the synchronous condenser is to the fault point, the more significant its reactive power compensation and voltage support effects become. This effectively reduces the voltage drop in the AC system, improves voltage recovery speed and time, and enhances the voltage stability of the AC system. Therefore, research on the selection of synchronous condenser location and capacity is of great importance.

[0105] 1. Construction of the objective function and constraints for the optimized configuration of distributed synchronous condensers

[0106] Step 1: Objective function for optimizing distributed synchronous condenser configuration

[0107] The optimal configuration of a camera grading system aims to minimize its capacity while ensuring optimal performance, thereby achieving the best economic efficiency. Therefore, the optimal configuration objective for a camera grading system can be derived as follows:

[0108] min F=S+P loss +dU

[0109] The overall level of camera configuration capacity, system active power loss, and voltage stability margin is minimized.

[0110] (1) Configuration capacity

[0111]

[0112] In the formula: S is the total capacity of the camera converter configuration, S i The capacity of the synchronous condenser at the renewable energy power station is denoted by n, where n is the number of renewable energy power stations in the system.

[0113] (2) Network loss

[0114] The calculation model for grid losses in a new energy power system is as follows:

[0115]

[0116] In the formula: P loss R represents the total active power loss; l represents the number of network branches; R represents the total active power loss. k I is the resistance value of the k-th branch; k Let be the current flowing through the k-th branch.

[0117] (3) Network voltage stability margin

[0118] After synchronous condensers are connected to the renewable energy power system, the system node voltage changes. During peak load periods, connecting synchronous condensers at points with lower node voltages can effectively improve node voltage levels. However, if the capacity of the connected synchronous condensers is too large, the excessive voltage will not meet user expectations. Therefore, a voltage stability margin index is constructed as the objective function for the location and capacity determination of synchronous condensers. Its expression is as follows:

[0119]

[0120] In the above formula: is the expected value of the node voltage; is the voltage value of the load node; is the allowable voltage deviation; N is the number of distribution network nodes; dU is the voltage stability margin.

[0121] Step 2: Constraints

[0122] To ensure that the voltage of the sending-end grid can be maintained within a safe range and to have good short-time overload capacity, the minimum short-circuit capacity of the system should be greater than the critical value:

[0123]

[0124] In the formula: S ac，min The minimum short-circuit capacity required for the AC system.

[0125] To ensure the safe and reliable operation of the sending-end power grid, the branch current must meet capacity constraints:

[0126] I l ≤I lmax l = 1, 2, ..., n

[0127] In the formula: I l I is the current flowing through line l; lmax denoted as , where is the maximum current flowing through line l; l represents the number of lines.

[0128] To ensure the safe and reliable operation of the power system and prevent node voltage from exceeding limits, node voltages must meet the following constraints:

[0129] U imin ≤U i ≤U imax i = 1, 2, ..., n

[0130] In the formula: U min and U max These are the lower and upper limits of the node voltage, respectively; U i Let i be the voltage amplitude at node i, and n be the number of nodes.

[0131] To ensure that the sending-end power grid satisfies power balance at all times, the following constraints must be met:

[0132]

[0133] In the formula: Q i,t P i,t G represents the reactive and active power injected into node i during time period t, respectively; ij B ij δ ij,t These represent the conductance, susceptance, and voltage phase angle difference between nodes i and j at time interval t, respectively; n is the number of nodes in the system; V i,t V j,t These are the voltage amplitudes of nodes i and j during time period t, respectively.

[0134] 2. Distributed synchronous condenser optimization configuration strategy

[0135] The flowchart of the distributed camera condenser configuration method is as follows: Figure 3 As shown.

[0136] Step 1: Read the grid structure, system parameters, and system unit parameters of the power grid;

[0137] Step 2: Calculate the voltage stability index of each node based on the relevant system parameters, and screen out the nodes with poor voltage stability index;

[0138] Step 3: Use the Grey Wolf optimization algorithm to find the best nodes where the system voltage stability index is poor;

[0139] Step 4: Perform simulation verification of the optimization results in a real PSASP example to check the validity and reliability of the results;

[0140] Step 5: The iteration ends, and the configuration results are output.

[0141] 3. Case Analysis

[0142] NEW ENGLAND 10-unit 39-node system including wind farm, such as Figure 4 As shown, by appropriately reducing the generator set capacity and increasing the proportion of new energy power generation, G05, G07, and G10 are replaced with doubly fed wind turbines of the same output, and doubly fed wind turbines with capacities of 600MVA, 500MVA, and 250MVA are connected to G06, G08, and G09 respectively, the correctness of the proposed method is verified.

[0143] This invention uses Matlab simulation software to solve the distributed synchronous condenser optimization configuration model.

[0144] The initial parameters for the Grey Wolf Algorithm are: population size of 50; maximum number of iterations of 100. The Grey Wolf pack is initialized as a 39-column, 1-row matrix, where the rows and columns represent the node and capacity configuration information of the camera adjuster, respectively. Each iteration randomly updates the node and capacity information, calculates the fitness value based on the penalty function, and finally outputs the optimal camera adjuster configuration.

[0145] The change of the global extremum during the optimization calculation process is as follows: Figure 5 As shown, the final optimized configuration scheme for the distributed synchronous condenser is obtained. Figure 5 As can be seen, with the increase of the number of iterations, the global extremum decreases rapidly and eventually stabilizes, indicating that the optimization calculation process converges. It should be noted that, since the Grey Wolf optimization algorithm is a stochastic optimization algorithm, the results obtained from multiple calculations may differ. Figure 6 The result is the best result among multiple calculations, with a total of 13 synchronous condensers configured at 6 sites.

[0146] like Figure 7 As shown, a distribution map of the static voltage indicators of each node in the system before and after the synchronous condenser configuration is generated. The map shows that the node voltages of the system have significantly improved after the synchronous condenser configuration, with darker colors indicating larger node static voltage indicators. (Comparison) Figure 7 It can be seen that the proposed synchronous condenser configuration scheme improves the node voltage at low static voltage stability parameters. The effectiveness of the proposed method is verified through visualization analysis of the system's static voltage distribution.

[0147] To further verify the effectiveness of the proposed site selection and capacity determination strategy, a 39-node system containing a wind farm (NEW ENGLAND 10 turbines) was tested according to... Figure 6 The proposed synchronous condenser configuration scheme places distributed synchronous condensers on corresponding renewable energy power stations, and calculates the minimum short-circuit ratio of each renewable energy power station and the short-circuit ratio of multiple stations before and after the configuration. It is evident that before the configuration of the synchronous condensers, the short-circuit ratios of each renewable energy power station were low, and some even fell below the critical short-circuit ratio, indicating weak system voltage support. After the configuration of the synchronous condensers, the short-circuit ratios of each renewable energy power station reached stable levels, all above 1.5, and all above the critical short-circuit ratio. Figure 8 A comparison chart of short-circuit ratio data for renewable energy power plants before and after configuring synchronous condensers is shown. It is evident that configuring synchronous condensers according to this method can significantly improve the voltage support strength of high-proportion renewable energy systems, enhance voltage safety during system operation, and further verify the effectiveness of the proposed site selection and capacity balancing strategy.

[0148] The calculation conditions, illustrations, etc. in the embodiments of this invention are only used to further illustrate the invention and are not exhaustive. They do not constitute a limitation on the scope of protection of the claims. Those skilled in the art, based on the inspiration gained from the examples of this invention, can conceive of other substantially equivalent alternatives without inventive effort, all of which are within the scope of protection of this invention.

Claims

1. A method for site selection and capacity determination of distributed synchronous condensers considering voltage stability constraints, characterized in that, Includes the following steps: 1) Construct a model of a new energy power system including synchronous condensers; 2) Construct voltage stability indices based on the theory that power flow equations have solutions; 3) Construct a distributed synchronous condenser optimization configuration model that considers the overall equipment configuration cost and the severity of system transient voltage rise; 4) The gray wolf algorithm is used to solve the model to obtain the optimal configuration scheme.

2. The distributed synchronous condenser location and capacity determination method considering voltage stability constraints according to claim 1, characterized in that, The model construction of a new energy power system including synchronous condensers includes the following steps: Step 1: For a multi-infeed system, the reactance between its grid connection point and collection point is expressed by the short-circuit capacity as follows: The current injected into the system from the collection point is the sum of the currents injected at each grid connection point: The relationship between the voltage at grid connection point i and the scale of new energy sources and the short-circuit capacity of the system in the fault steady-state voltage security problem of multi-infeed systems is as follows: Further analysis of the relationship between voltage and power at each grid connection point reveals that the ratio of the horizontal voltage components between grid connection points i and j and the collection point is: Based on the above formula, an active power influence factor describing the power relationship between grid connection point j and grid connection point i is proposed: In the formula K P,ji The active power influence factor of grid connection point j on grid connection point i can be calculated using reactance and voltage. When i = j, K P,ii =1; Representing the power at other points in terms of the power at grid connection point i, the voltage security analysis model for the multi-infeed system is obtained as follows: In multi-infeed systems, the main influencing factors on steady-state voltage safety after a fault are the same as those in single-infeed systems, which are affected by the scale of new energy sources and short-circuit capacity. Step 2: After the synchronous condenser is connected to a node in the AC system, assuming the target AC system has n nodes, the impedance matrix Z before the synchronous condenser is connected can be expressed as: In the formula: Z pq This represents the impedance between any two nodes; After the synchronous condenser is connected, node b gains a ground-to-ground branch. According to the method of adding branches, the impedance between nodes p and q can be expressed as: In the formula: Z bb Z is the self-impedance of node b. pb Z represents the mutual impedance between node b and node p. qb Let be the mutual impedance between node b and node q; Combining the above two equations, we can obtain the multi-infeed short-circuit ratio of the i-th DC line after the synchronous condenser is connected: Simplified to: When any element of the impedance matrix decreases, the multi-feed short-circuit ratio increases, and the system's voltage support capability for the converter bus is improved. The short-circuit ratio is used to characterize the grid voltage support strength. A large short-circuit ratio indicates a strong network, while a small short-circuit ratio indicates a weak network and unstable system operation. Step 3: In the new energy grid-connected system, the new energy input power from each grid connection point is collected at the collection point and transmitted through the collection line. The short-circuit ratio at the collection point is: Where: SCR POI S is the short-circuit ratio at the convergence point; ∑ Inject total power to each grid connection point; The mathematical analysis model for steady-state voltage safety after a fault is derived. After power balancing, the relationship between the short-circuit capacity provided by the AC system at the collection point, the active power, and the voltage at grid connection point i is as follows: The system short-circuit capacity is differentiated with respect to the grid connection point voltage, and the correlation between the two is analyzed: When the grid connection point voltage is between 0.9 pu and 1.0 pu, the above formula is greater than 0. The higher the voltage that the grid connection point needs to maintain, the greater the short-circuit capacity required by the system at the convergence point. When the required grid connection point voltage is above 0.9 pu, the minimum short-circuit capacity that the AC system needs to provide is:

3. The distributed synchronous condenser location and capacity determination method considering voltage stability constraints according to claim 1, characterized in that, The theoretical construction of voltage stability indices based on the solvable power flow equations includes the following steps: The static voltage stability index L, constructed based on the theory of power flow solution existence, is as follows: Q c =Q D +Q j In the formula: P j Q represents the sum of the active power of node j itself, the active power of all load nodes after node j, and the active power losses of all branches after node j; j Q represents the sum of the reactive power of node j itself, the reactive power of all load nodes after node j, and the reactive power losses of all branches after node j; D U represents the capacity of the camera configured in node i. i X represents the node voltage of node i in the system; ij R represents the reactance between nodes i and j; ij This represents the resistance between nodes i and j; When L>0, the corresponding node voltage is stable. The stability level of the voltage is judged by the value of L. The smaller L is, the closer it is to 0, and the lower the voltage stability level of that point. The point with the smallest L is the point where voltage collapse is most likely to occur. By calculating the L value of each node, corresponding measures are taken for nodes with smaller L values ​​to avoid voltage collapse.

4. The distributed synchronous condenser location and capacity determination method considering voltage stability constraints according to claim 1, characterized in that, The construction of the distributed synchronous condenser optimization configuration model, which considers the overall equipment configuration cost and the severity of system transient voltage rise, includes the following steps: Step 1: Solve the objective function for optimizing the configuration of distributed synchronous condensers. Under the premise of minimizing configuration capacity, the optimal configuration target for the camera adjustment device is: minF=S+P loss +dU In the formula: S represents the total capacity of the camera converter configuration; S i The capacity of the synchronous condenser configured at the new energy power station; P loss dU represents the total active power loss, and dU represents the voltage stability margin; that is, minimizing the combined level of synchronous condenser capacity, system active power loss, and voltage stability margin; among which, 1) Configuration capacity In the formula: S i The capacity of the synchronous condenser configured at the renewable energy power station is denoted by n, where n is the number of renewable energy power stations in the system. 2) Network loss The calculation model for grid losses in a new energy power system is as follows: In the formula: l is the number of network branches; R k I is the resistance value of the k-th branch; k Let be the current flowing through the k-th branch; 3) Network voltage stability margin The voltage stability margin index is constructed as the objective function for the location and capacity determination of the synchronous condenser, and its expression is as follows: In the above formula: U e U represents the expected value of the node voltage. load U represents the voltage value at the load node. p dU is the allowable voltage deviation; N is the number of distribution network nodes; dU is the voltage stability margin. Step 2: Set constraints To ensure that the voltage of the sending-end grid can be maintained within a safe range and to have good short-time overload capacity, the minimum short-circuit capacity of the system should be greater than the critical value: In the formula: S ac，min The minimum short-circuit capacity required for the AC system; To ensure the safe and reliable operation of the sending-end power grid, the branch current must meet capacity constraints: I l ≤I lmax l=1,2,...,n In the formula: I l I is the current flowing through line l; lmax The maximum current flowing through line l; l is the number of lines; To ensure the safe and reliable operation of the power system and prevent node voltage from exceeding limits, node voltages must meet the following constraints: U imin ≤U i ≤U imax i=1,2,...,n In the formula: U min and U max These are the lower and upper limits of the node voltage, respectively; U i Let n be the voltage amplitude at node i, and n be the number of nodes. To ensure that the sending-end power grid satisfies power balance at all times, the following constraints must be met: In the formula: Q i,t P i,t G represents the reactive and active power injected into node i during time period t, respectively; ij B ij δ ij,t These represent the conductance, susceptance, and voltage phase angle difference between nodes i and j at time interval t, respectively; n is the number of nodes in the system; V i,t V j,t denoted as voltage amplitudes at nodes i and j during time period t, respectively.

5. The distributed synchronous condenser location and capacity determination method considering voltage stability constraints according to claim 1, characterized in that, The process of using the Grey Wolf algorithm to solve the model and obtain the optimized configuration scheme includes the following steps: Step 1: Read the grid structure, system parameters, and system unit parameters of the power grid; Step 2: Calculate the voltage stability index of each node based on the relevant system parameters, and screen out the nodes with poor voltage stability index. Step 3: Use the Grey Wolf optimization algorithm to find the best nodes where the system voltage stability index is poor. Step 4: Perform simulation verification of the optimization results in a real PSASP example to check the validity and reliability of the results; Step 5: The iteration ends, and the configuration results are output.

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