A static reactive power compensator capacity and site selection method based on electromagnetic transient simulation

Abstract

The application relates to the field of power system planning, and relates to a static reactive power compensator capacity and location selection method based on electromagnetic transient simulation, which comprises the following steps: randomly generating P simulation scenes and P speed vectors; performing electromagnetic transient simulation on each simulation scene to obtain the result of electromagnetic transient simulation, and calculating the optimization target of each scene based on the result of electromagnetic transient simulation; repeating step S2 until the P simulation scenes are traversed, selecting the historical optimal solution of each simulation scene in the iteration process and all global optimal solutions; updating the speed value vector of each scene, and calculating the static reactive power compensator capacity configuration scheme of each scene based on the updated speed value vector; repeating steps S2-S4 until the iteration converges, so that the final static reactive power compensator configuration scheme is obtained. The application can comprehensively consider economy and power system stability, find the most suitable bus position for a newly-built static reactive power compensator, and provide an optimized strategy scheme for the reactive power voltage support of the system.

Description

Technical Field

[0001] This invention relates to the field of power system planning, and specifically to a method for determining the location of static reactive power compensators based on electromagnetic transient simulation. Background Technology

[0002] With the integration of numerous HVDC transmission lines and renewable energy sources into the power grid, the traditional AC power grid has gradually evolved into a hybrid AC / DC power grid with HVDC transmission as its backbone and incorporating a large number of renewable energy generation and distributed power consumption devices. A large number of power electronic devices exhibit nonlinear characteristics, including complex dynamic responses, high frequencies, and multi-timescale coupling. The new power system structure demands more reactive power support, posing new challenges to the reactive power and voltage stability of the power grid. Installing reactive power compensation equipment is an effective measure to supplement reactive power support and improve voltage stability. Compared to other reactive power compensation equipment (such as synchronous condensers and static var generators), static var compensators (SVCs) have inherent advantages in terms of size, price, and response speed.

[0003] On the other hand, the dynamic characteristic analysis of large-scale power grids relies on time-domain simulation. Traditionally, transient stability analysis of large transmission and transformation systems has been conducted using electromechanical transient simulation programs. However, with the development of power systems, modern power grids integrate more and more complex components, such as renewable energy devices and high-voltage direct current (HVDC) transmission devices. Electromechanical transient simulation programs can no longer meet the required accuracy when facing complex faults such as commutation failure and subsynchronous oscillations. Therefore, electromagnetic transient simulation is now required for the dynamic characteristic analysis of actual power grids. The basic algorithm for electromagnetic transient simulation of power systems (EMTP) was proposed by Dommel et al. in the early 1960s, initially used to study transient overvoltage problems in power systems. With technological advancements, the number of HVDC transmission systems and power electronic components in power grids has increased. To better simulate the transient processes of the power grid, electromagnetic transient simulation has become increasingly important, leading to the emergence of commercially available and relatively mature electromagnetic transient simulation software, such as EMTP-RV, PSCAD / EMTDC, and CloudPSS.

[0004] When a power grid encounters transmission line faults or grounding issues during operation, voltage fluctuations may occur throughout the grid, potentially leading to DC transmission commutation failures and impacting the safe and stable operation of the grid. To address potential voltage instability in the grid, static var compensators (SVCs) need to be added at specific nodes to provide reactive power support. For large-scale power systems with thousands of nodes, there are many potential locations for adding SVCs; however, not all locations can meet the grid's voltage instability requirements, and the reactive power and voltage support capabilities of different locations and capacity configurations vary. Currently, research on the location and capacity configuration of new SVCs is lacking, necessitating an optimization method for SVC location. Summary of the Invention

[0005] To address the technical problems existing in the prior art, this invention provides a method for determining the capacity and location of static reactive power compensators based on electromagnetic transient simulation. This method can comprehensively consider economic efficiency and power system stability to find the most suitable bus position for newly built static reactive power compensators, providing an optimized strategy for reactive power voltage support of the system.

[0006] This invention can be achieved by adopting the following technical solutions:

[0007] A static var compensator (SVC) constant-capacity location method based on electromagnetic transient simulation, the method comprising:

[0008] S1. Randomly generate P simulation scenarios and P velocity vectors, with each simulation scenario corresponding to a static var compensator configuration scheme;

[0009] S2. Perform electromagnetic transient simulation for each simulation scenario to obtain the electromagnetic transient simulation results. Set the optimization target for the scenario based on the system's fault severity index, and calculate the optimization target for each scenario based on the electromagnetic transient simulation results.

[0010] S3. Repeat step S2 until P simulation scenarios are traversed, and select the local optimal solution and all global optimal solutions for each simulation scenario during the iteration process.

[0011] S4. Update the velocity value vector for each scenario, and calculate and update the static reactive power compensator capacity configuration scheme for each scenario based on the updated velocity value vector;

[0012] S5. Repeat steps S2-S4 until the iteration converges to obtain the locally optimal configuration scheme on each bus and determine the final global static var compensator's constant-capacity location scheme.

[0013] Preferably, the optimization objective of the scenario based on the system's fault severity index includes: when the system's fault severity index is less than or equal to a preset value, the optimization objective of the scenario is the total investment cost; when the system's fault severity index is greater than the preset value, the optimization objective of the scenario is the combined value of the total investment cost and the fault severity index.

[0014] Preferably, the static var compensator fixed-capacity addressing method based on electromagnetic transient simulation is characterized in that the function f of the optimization objective is:

[0015]

[0016] The system has M buses, ε is a preset value, A is a constant, and Q... j For the static var compensator capacity at bus j, c j The cost required to deploy a unit capacity static var compensator on the j-th bus.

[0017] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0018] This invention provides a method for determining the location of static var compensators based on electromagnetic transient simulation. It uses electromagnetic transient simulation results as the data source for the static var compensator location scheme, resulting in high accuracy. The optimization objective function is calculated by comprehensively considering the severity of the fault and the investment in establishing the static var compensator. This approach can comprehensively consider both economic efficiency and power system stability, finding the most suitable bus location for the new static var compensator and providing an optimized strategy for the reactive power and voltage support of the system. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0020] Figure 1 This is a flowchart of a static reactive power compensator fixed-capacity addressing method based on electromagnetic transient simulation in an embodiment of the present invention;

[0021] Figure 2 This is a schematic diagram illustrating the calculation of the fault severity index in an embodiment of the present invention. Detailed Implementation

[0022] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments, and the implementation of the present invention is not limited thereto. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Example 1:

[0024] To address potential voltage instability issues in power grids during operation, static var compensators (SVCs) need to be added at specific nodes. The selection of new SVC locations must address voltage instability, and the site selection and capacity configuration must meet the grid's reactive power and voltage support requirements. This invention proposes an optimization method for SVC site selection and capacity configuration based on electromagnetic transient simulation. For power grid fault scenarios, it uses a method based on the WECC / NERC standard to calculate the severity of faults in typical scenarios, calculating the fault severity and total capacity under various site selection and capacity configuration schemes. An iterative algorithm is then used to calculate the optimal site selection and capacity configuration strategy. This method can guide power grid construction and accident prevention, identifying the most suitable bus location for new SVCs and providing an optimized strategy for system reactive power and voltage support.

[0025] like Figure 1 As shown, the static var compensator fixed-capacity location method based on electromagnetic transient simulation of the present invention includes the following steps:

[0026] S1. Randomly generate P simulation scenarios and P velocity vectors. Each simulation scenario corresponds to a configuration scheme of the static var compensator. The generated P simulation scenarios and P velocity vectors are used to complete the initial scenario configuration, and subsequent optimization processes will start iterating from this initial scenario.

[0027] P simulation scenarios are randomly generated, where P can be any positive integer, preferably between 5 and 20. Each scenario corresponds to a static var compensator (SVC) configuration scheme, denoted as Q. 1 Q 2 ,…,Q P Simultaneously, P velocity vectors are randomly generated, denoted as v. 1 v 2 , ..., v P .

[0028] Preferably, when there are M buses available for adding static var compensators, and the bus set is I... B,SVC Let Q be a configuration scheme for a static var compensator, where Q is:

[0029] Q = [Q1Q2…Q] M (1)

[0030] Where Q1, Q2, ... QM represent the static var compensator capacity added to each of the M buses.

[0031] S2. Perform electromagnetic transient simulation for each simulation scenario to obtain the electromagnetic transient simulation results. Set the optimization target for the scenario based on the system's fault severity index, and calculate the optimization target for each scenario based on the electromagnetic transient simulation results.

[0032] An iterative process was completed for each scenario. By calculating the optimization objective function, it can be determined whether the scenario is locally optimal under the current configuration. Assuming the iteration reaches the k-th iteration, for the p-th simulation scenario (1≤k≤P), the static var compensator capacity Q is configured. p The electromagnetic transient simulation results are obtained by solving (k), and the optimization objective value f for the p-th scenario is calculated based on the electromagnetic transient simulation results. p (k), the optimization objective is to minimize the value of the objective function f.

[0033] Assuming the system has N buses, define the percentage voltage deviation D of bus j at time t after a fault. j (t) is:

[0034]

[0035] Among them, V i (t) is the effective value of the bus voltage i at time t, V i init It is the initial voltage amplitude before the fault.

[0036] Correspondingly, the fault severity index s of bus i at time t is defined. i (Q,t) is:

[0037]

[0038] t cl It is the time for fault clearing, t s Generally, 3 seconds is used. For example... Figure 2 The diagram shown illustrates the calculation of the fault severity index.

[0039] Furthermore, the failure severity index of the entire system is calculated. s (Q) is:

[0040]

[0041] The system has N buses, and s(Q) is the system's fault severity index. i (Q) is the fault severity index of the i-th bus, s i(Q,t) represents the severity index of the fault on the i-th bus at time t, and T is the total simulation time after the fault is cleared.

[0042] Specifically, the optimization objectives for scenarios based on the system's fault severity index include: when the fault severity index of the entire system is less than or equal to a preset value, the optimization objective for the scenario is the total investment cost; when the fault severity index of the entire system is greater than the preset value, a certain penalty is imposed based on the fault severity index, and the optimization objective for the scenario is the combined value of the total investment cost and the fault severity index.

[0043] Specifically, the function f for optimizing the scenario is:

[0044]

[0045] Where ε is a preset value, preferably 0.05, A is a constant, and Q... j To deploy a static var compensator with a capacity of c on the j-th bus. j The cost required to deploy a unit capacity static var compensator at bus j can be set according to requirements, and its magnitude is the estimated total budget.

[0046] S3. Repeat step S2 until all P simulation scenarios are traversed, selecting the local optimum and the global optimum for each simulation scenario during the iteration process. Selecting the local optimum for each particle and the global optimum for all particles helps all scenarios converge towards their respective local and global optima in subsequent processes.

[0047] Specifically, the local optimal solution for the p-th scenario after the k-th iteration is the minimum value of the objective f optimized during iterations 1 to k of the p-th scenario, denoted as Q. pBest,p The global optimal solution after the k-th iteration is the configuration scheme corresponding to the smallest objective function f among the local optimal solutions of all P scenarios. This global optimal solution is denoted as Q0. gBest .

[0048] S4. Update the velocity value vector for each scenario, and calculate and update the static reactive power compensator capacity configuration scheme for each scenario based on the updated velocity value vector.

[0049] The velocity value v for each scene can be calculated using the formula for calculating the velocity value vector. The formula for calculating the velocity value vector is as follows:

[0050] v p (k)=ωv p (k-1)+c1α(Q pBest,p (k)-Q p (k))+c2β(Q gBest (k)-Q p(k)) (6)

[0051] Among them, v p (k) represents the velocity value of the p-th scene in the k-th iteration, Q pBest,p (k) is the local optimal solution of the p-th scene after the k-th iteration, α and β are random numbers between 0 and 1, ω is a velocity decay factor between 0 and 1, and c1 and c2 are learning factors, usually taken as c1 = c2 = 2; Q p (k) represents the result of the electromagnetic transient simulation of the p-th simulation scenario after the k-th iteration.

[0052] The velocity of each particle was calculated with the aim of bringing the configuration of each scenario closer to the global and local optimum, thereby achieving the addressing and sizing optimization of the static var compensator.

[0053] The static reactive power compensator capacity configuration scheme for each scenario is updated based on the updated velocity value vector. The calculation formula is as follows:

[0054] Q p (k+1)=Q p (k)+v p (k) (7)

[0055] Among them, Q p (k+1) represents the configuration scheme for the (k+1)th iteration of the scenario, Q p (k) represents the configuration scheme for the k-th iteration, v p (k) is the velocity value calculated in the k-th iteration.

[0056] For the p-th scenario, the configuration scheme for its (k+1)-th iteration is equal to the configuration scheme for the k-th iteration plus the speed value calculated in the k-th iteration.

[0057] S5. Repeat steps S2-S4 until the iteration converges to obtain the locally optimal configuration scheme on each bus and determine the final global static var compensator's constant-capacity location scheme.

[0058] Let Q be the final globally optimal configuration of the static var compensator. gBest,All Its expansion is as follows:

[0059]

[0060] The method provided in this embodiment can ultimately yield a deployment capacity of Q1 on each of the 1st to Mth buses. Best Q2 Best …Q M BestStatic var compensators (SVCs) are a type of SVC configuration that can improve power system stability and is also the most economical.

[0061] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A method for fixed-capacity location selection of static var compensators based on electromagnetic transient simulation, characterized in that, Including the following steps: S1. Randomly generate P simulation scenarios and P velocity vectors, with each simulation scenario corresponding to a static var compensator configuration scheme; S2. Perform electromagnetic transient simulation for each simulation scenario to obtain the electromagnetic transient simulation results. Set the optimization target for the scenario based on the system's fault severity index, and calculate the optimization target for each scenario based on the electromagnetic transient simulation results. The function of the optimization objective for: ； The system has M buses. The system's fault severity index is ε, where ε is a preset value and A is a constant. Let J be the capacity of the static var compensator deployed at bus j. The cost required to deploy a unit capacity static var compensator on the j-th bus is ε = 0.

05. S3. Repeat step S2 until P simulation scenarios are traversed, and select the local optimal solution and all global optimal solutions for each simulation scenario during the iteration process. S4. Update the velocity value vector for each scenario, and calculate and update the static reactive power compensator capacity configuration scheme for each scenario based on the updated velocity value vector; S5. Repeat steps S2-S4 until the iteration converges to obtain the locally optimal configuration scheme on each bus and determine the final global static var compensator's constant-capacity location scheme.

2. The static var compensator fixed-capacity location method based on electromagnetic transient simulation according to claim 1, characterized in that, Step S1 includes: when there are M buses available for adding static reactive power compensators, and one configuration scheme for the static reactive power compensator is denoted as Q. ； Where Q1, Q2, ... QM represent the static var compensator capacity added to each of the M buses.

3. The static var compensator fixed-capacity location method based on electromagnetic transient simulation according to claim 1, characterized in that, The optimization objective of the scenario based on the system's fault severity index includes: when the system's fault severity index is less than or equal to a preset value, the optimization objective of the scenario is the total investment cost; when the system's fault severity index is greater than the preset value, the optimization objective of the scenario is the combined value of the total investment cost and the fault severity index.

4. The static var compensator fixed-capacity location method based on electromagnetic transient simulation according to claim 3, characterized in that, The system's fault severity index can be calculated using the following formula: ； The system has N buses. This is an index representing the severity of system failures. Let s be the fault severity index for the i-th bus. i (Q,t) represents the severity index of the fault on the i-th bus at time t, and T is the total simulation time after the fault is cleared.

5. The static var compensator fixed-capacity location method based on electromagnetic transient simulation according to claim 4, characterized in that, The formula for calculating the velocity value vector is: ； in, Let p be the velocity value of the p-th scene in the k-th iteration. This refers to the local optimum of the p-th scene after the k-th iteration, where α and β are random numbers between 0 and 1, ω is a velocity decay factor between 0 and 1, and c1 and c2 are learning factors, where c1=c2=2. This is the result of the electromagnetic transient simulation of the p-th simulation scenario at the k-th iteration.

6. The static var compensator fixed-capacity location method based on electromagnetic transient simulation according to claim 5, characterized in that, The calculation formula for updating the static reactive power compensator capacity configuration scheme for each scenario based on the updated velocity value vector is as follows: ； in, This is the configuration scheme for the (k+1)th iteration of the scenario. The configuration scheme for the k-th iteration process, This is the velocity value calculated during the k-th iteration.

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