Optimal configuration method of dynamic reactive power compensation device in high proportion of new energy access receiving end power grid

Abstract

The application discloses a kind of high proportion new energy access in the optimization configuration method of dynamic reactive power compensation device in receiving end power grid, it is related to power system planning control technical field.The method includes: establishing the power system simulation model of receiving end power grid, and identifying voltage stability weak node based on the power system simulation model;Build the optimization model with the maximum of total amount of generator reactive power reserve as target, solve the optimization model and obtain the excitation reference voltage of each generator, and update the excitation reference voltage corresponding to each generator in the power system simulation model using the excitation reference voltage;Based on the power system simulation model after updating excitation reference voltage, the dynamic reactive power compensation effect index of each weak node is calculated, and dynamic reactive power compensation device is sequentially configured according to the dynamic reactive power compensation effect index.The present application is used to solve the problem that external reactive power compensation configuration process is not coordinated and the internal transient reactive power support potential of existing generator in network is not mined.

Description

Technical Field

[0001] This invention relates to the field of power system planning and control technology, and more specifically, to an optimized configuration method for dynamic reactive power compensation devices in a receiving-end power grid with a high proportion of renewable energy access. Background Technology

[0002] In power systems with large-scale renewable energy and high-capacity DC centralized feed-in to the receiving-end grid, the operating capacity and construction proportion of conventional synchronous generators dynamically decrease, leading to a weakening of the overall rotating reactive power support capacity of the system. When the grid faces severe transient disturbances such as major faults, the demand for transient reactive power from converter station loads and induction motors surges instantaneously, easily triggering transient voltage drops or even voltage collapse. Therefore, how to economically and efficiently configure dynamic reactive power compensation devices in the receiving-end grid to improve the transient voltage stability of the system is a pressing technical requirement in the field of power system planning.

[0003] To address the aforementioned needs, existing mainstream technical solutions mostly employ reactive power configuration methods based on time-domain simulation, or adopt distributed coordinated control methods such as those described in patent document CN121192734A to implement local reactive power compensation. Conventional time-domain simulation configuration schemes typically begin by simulating and verifying the system's voltage dip response under typical fault conditions to identify transient voltage weak points in the power grid. Subsequently, under a system environment where internal control parameters such as generator excitation reference voltage are set to conventional fixed operating benchmarks, the static voltage sensitivity index is calculated to evaluate the improvement effect of reactive power injected into each bus on the voltage of weak points, and this is used to determine the planning, location, and capacity configuration scheme for external dynamic reactive power compensation devices.

[0004] However, the aforementioned existing technologies have the following limitations in practical applications: First, the external reactive power configuration process is disconnected from the internal operation control of conventional power sources, failing to coordinate and tap the internal transient reactive power output potential of existing synchronous generators within the grid after disturbances occur, resulting in high configuration capacity and investment costs for external reactive power devices; Second, traditional configuration methods are mostly based on linear expansion at the power system equilibrium point. In the process of strong nonlinear evolution caused by large transient disturbances, traditional static sensitivity methods suffer from severe information loss and distortion, failing to accurately characterize the dynamic trajectory of the system; Third, existing reactive power configuration evaluation mechanisms mostly focus on spatial single-point or local distributed control, lacking a multi-temporal and spatial scale dynamic comprehensive evaluation mechanism that couples the severity of fault scenarios, node importance, and transient full-process time evolution factors, making it difficult to achieve optimal and refined configuration of reactive power resources. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide an optimized configuration method for dynamic reactive power compensation devices in a receiving-end power grid with a high proportion of new energy access. The method identifies weak nodes through a simulation model, updates the generator excitation reference voltage using a reactive power reserve maximization model, and calculates indicators to sequentially configure reactive power compensation devices, thereby solving the technical problem of external reactive power configuration not coordinating with the internal reactive power potential of the generator.

[0006] To achieve the above objectives, the present invention provides the following technical solution: An optimized configuration method for dynamic reactive power compensation devices in a receiving-end power grid with a high proportion of renewable energy access includes the following steps: establishing a power system simulation model of the receiving-end power grid and identifying weak nodes with voltage stability based on the power system simulation model; constructing an optimization model with the objective of maximizing the total reactive power reserve of generators, solving the optimization model to obtain the excitation reference voltage of each generator, and updating the excitation reference voltage corresponding to each generator in the power system simulation model using the excitation reference voltage; calculating the dynamic reactive power compensation effect index of each weak node based on the updated excitation reference voltage of the power system simulation model, and sequentially configuring the dynamic reactive power compensation devices according to the dynamic reactive power compensation effect index.

[0007] In addition, the present invention also provides an optimized configuration device for dynamic reactive power compensation devices in a receiving-end power grid with a high proportion of new energy access, comprising: a weak point identification module, used to establish a power system simulation model of the receiving-end power grid and identify weak nodes in voltage stability based on the power system simulation model; an excitation optimization module, used to construct an optimization model with the goal of maximizing the total reactive power reserve of generators, solve the optimization model to obtain the excitation reference voltage of each generator, and update the excitation reference voltage corresponding to each generator in the power system simulation model using the excitation reference voltage; and a sequential configuration module, used to calculate the dynamic reactive power compensation effect index of each weak node based on the power system simulation model after updating the excitation reference voltage, and perform sequential configuration of the dynamic reactive power compensation device according to the dynamic reactive power compensation effect index.

[0008] The present invention provides a computer device, including a processor and a memory: the memory is used to store computer programs and send the instructions of the computer programs to the processor; the processor executes the optimization configuration method of the dynamic reactive power compensation device in the receiving-end power grid with a high proportion of new energy access according to the instructions of the computer programs.

[0009] The present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements an optimized configuration method for a dynamic reactive power compensation device in a receiving-end power grid with a high proportion of renewable energy access.

[0010] In summary, the optimized configuration method of dynamic reactive power compensation device in a receiving-end power grid with a high proportion of new energy access, as proposed in this invention, has the following technical effects and advantages: This invention identifies weak nodes in voltage stability by establishing a power system simulation model of the receiving-end power grid, constructs and solves an optimization model with the goal of maximizing the total reactive power reserve of generators to update the excitation reference voltage of each generator in the simulation model, and calculates the dynamic reactive power compensation effect index of each weak node based on the simulation model after updating the excitation reference voltage, and sequentially configures dynamic reactive power compensation devices. This solves the technical problem that the external reactive power compensation configuration process does not coordinate with the transient reactive power potential inside the generators, and achieves the technical effects of tapping the reactive power reserve space of existing generators in the grid, reducing the configuration capacity of external dynamic reactive power compensation devices, and improving the transient voltage stability of the receiving-end power grid. Attached Figure Description

[0011] Figure 1 A schematic diagram of the optimization configuration method for dynamic reactive power compensation devices in a receiving-end power grid with a high proportion of new energy access provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the IEEE 39-node system in an embodiment of the present invention; Figure 3 This is a response curve of the generator excitation reference voltage before optimization in an embodiment of the present invention; Figure 4 This is a response curve of the generator excitation reference voltage after optimization in an embodiment of the present invention; Figure 5 Node voltage waveform before reactive power compensation; Figure 6 Node voltage waveform after reactive power compensation; Figure 7 This is a block diagram of an optimized configuration system for a dynamic reactive power compensation device in a receiving-end power grid with a high proportion of renewable energy access, provided in an embodiment of the present invention. Detailed Implementation

[0012] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0013] Figure 1 This invention presents an optimized configuration method for dynamic reactive power compensation devices in a receiving-end power grid with a high proportion of renewable energy access, comprising the following steps: S1. Establish a power system simulation model of the receiving-end power grid, and identify weak nodes with voltage stability based on the power system simulation model.

[0014] In this embodiment, the identification of weak points in voltage stability includes: S101, in areas with heavy loads and where the number of synchronous generator batteries supporting the system is lower than a set value, typical faults are selected for time-domain simulation, and supplementary time-domain simulations are performed on typical fault points around these areas; specifically, the correlation between system stability and disturbance location is taken into account; since the weak voltage stability area is caused by large-capacity new energy sources and large-capacity DC centralized feed, this embodiment focuses on the dynamic core load area corresponding to the new energy sources and DC centralized feed to perform targeted disturbance verification, so as to comprehensively extract dynamic response data under different spatiotemporal disturbances. The specific steps are as follows: In the power system simulation model, a region with heavy load and few synchronous generator supports is located and typical faults are selected for calculation and analysis. At the same time, 2 to 3 typical fault points are selected around the region for supplementary calculations. Time-domain simulations corresponding to the typical faults and supplementary calculations are run respectively to provide a dataset of system transient responses containing different disturbance locations.

[0015] S102, output the dynamic response data of node voltages in the region under study. Define the region with the highest probability of the lowest voltage value occurring during the transient process as the voltage stability weak region, and identify the nodes within the voltage stability weak region as the voltage stability weak nodes. Specifically, based on the existence of voltage dip regions in the power grid, regardless of whether the system can recover stability after a disturbance, the voltage in this region is always the lowest during the dynamic process, thus making the voltage stability weak region correspond to the physical characteristics of the voltage dip region. The steps are as follows: Extract the output results of the time-domain simulation to obtain the dynamic trajectory data of the node voltage in the region under study; count the frequency of each AC node reaching the minimum voltage during the transient process and calculate the probability of each node reaching the minimum voltage; define the region with the highest probability of the minimum voltage as the voltage stability weak region; finally define the nodes in the region as voltage stability weak nodes, and use this as the node space set for participating in the dynamic reactive power compensation effect evaluation.

[0016] S2. Construct an optimization model with the goal of maximizing the total reactive power reserve of generators, solve the optimization model to obtain the excitation reference voltage of each generator, and use the excitation reference voltage to update the excitation reference voltage of each generator in the power system simulation model.

[0017] In this embodiment, the expression for the total reactive power reserve of the generator is as follows: ; ; In the formula, This represents the total reactive power reserve of the generator. For generator Reactive power standby; For fault scenarios The severity; For weak nodes in voltage stability The importance of nodes; For generator In failure scenarios Below are weak nodes in voltage stability The continuous function of the time-varying voltage stability contribution; For generator exist Reactive power output at any given moment; For generator Reactive power output in steady state; This refers to the number of generators. This represents the number of fault scenarios. The number of weak points in voltage stability.

[0018] The total reactive power reserve of the generator is determined based on the time-varying voltage stability contribution, node importance, and fault scenario severity. Specifically, given the extremely complex influencing factors on the generator's dynamic reactive power output capacity, which are affected by various factors such as the system's initial operating state, fault type, fault location, fault duration, excitation system parameters, and system stability control strategy, this embodiment defines the generator's dynamic reactive power reserve as the actual reactive power that can be added during the transient process after a fault, taking into account time response. The actual reactive power support capacity of the generator under different fault scenarios, different weak nodes, and different transient time scales is quantitatively calculated by algebraically multiplying and integrating the time-varying voltage stability contribution, node importance, and fault scenario severity. The expression for the time-varying voltage stability contribution is as follows: ; In the formula, For generator In failure scenarios Below Constantly monitor weak points in voltage stability The contribution of time-varying voltage stability; It is a natural number; For generator After a disturbance is applied to the excitation reference voltage, The increment of reactive power output at any given moment compared to before the disturbance; Before excitation reference voltage disturbance Time bus The voltage amplitude; After the excitation reference voltage is disturbed Time bus The voltage amplitude. Specifically, the time decay factor. This allows the optimization model to be highly focused on the initial transient phase after a fault occurs in the time evolution dimension, automatically increasing the reactive power support weight in the critical time domain where the system is most prone to voltage collapse; the increment of the reactive power output compared to before the disturbance. Generator After the excitation reference voltage is disturbed The increment of reactive power output at any given time compared to before the disturbance; the steps are as follows: First, perform time-domain simulation under the reference state without disturbance, and extract... Time bus The voltage amplitude; then supply the generator Apply an excitation reference voltage disturbance and rerun the simulation, then extract the disturbance. Time bus The voltage amplitude and reactive power output increment of the generator are obtained, and finally the time-varying voltage stability contribution value at the discrete time domain sampling point is obtained through differential algebra operation, which is used to reflect the nonlinear support trajectory of the generator dynamic output on the key bus voltage under large disturbance.

[0019] The expressions for the node importance and the fault scenario severity are as follows: ; ; In the formula, For weak nodes in voltage stability The rated transmission power; Weak nodes in voltage stability prior to the fault The voltage amplitude; For the weak point of voltage stability at the time of fault clearing The voltage amplitude.

[0020] The objective function and constraints of the optimization model are as follows: The objective function is: ; In the formula, For generator The excitation reference voltage, For generator The change in excitation reference voltage; The constraints include system power flow constraints, generator capacity constraints, node voltage quality constraints, and transformer tap constraints, expressed as follows: ; ; ; ; In the formula, and These are the active power and reactive power of the generator, respectively. and These are the active power and reactive power of the load, respectively. and They are nodes and nodes The voltage amplitude; For nodes and nodes The voltage phase angle difference; and These are the branch conductance and susceptance, respectively. This represents the total number of nodes in the system. This refers to the number of generators. This refers to the number of ordinary communication nodes; This refers to the number of transformers. and These are the minimum and maximum reactive power outputs of the generator, respectively. and These are the upper and lower voltage limits for the generator node, respectively; and These are the upper and lower voltage limits for a normal AC node; and These are the upper and lower limits of the transformer taps, respectively.

[0021] Furthermore, solving the optimization model includes: S201, Establish the dynamic nonlinear differential-algebraic equation system of the receiving-end power grid; specifically, considering the nonlinear characteristics of the power system and the need to consider the dynamic response of system components in transient voltage stability analysis, the steps are as follows: Describe the dynamic evolution behavior of the system in the form of a combination of differential equations and algebraic equations. The calculation formula of the dynamic nonlinear differential-algebraic equation system of the receiving-end power grid is as follows: ; In the formula, For system state variables; For system algebra variables; These are system operating parameters; and These are the initial values ​​for the system state variables and the algebraic variables, respectively; S202, the trajectory sensitivity of the state variables and algebraic variables in the dynamic nonlinear differential-algebraic equation system to the system operating parameters is calculated using the numerical perturbation method. Specifically, considering that traditional static sensitivity methods are unsuitable for scenarios with strong nonlinearity and large disturbances due to excessive errors caused by information loss, the concept of trajectory sensitivity from the control field is introduced into the dynamic analysis of power systems. The steps are as follows: To reduce the analytical calculation difficulty in complex large-scale systems, a small deviation is applied to the system operating parameters to discretize the parameter domain, and the trajectory sensitivity is obtained through difference approximation. The calculation formulas for the trajectory sensitivity of the state variables and algebraic variables to the system operating parameters are as follows: ; In the formula, State variables System operating parameters Trajectory sensitivity; algebraic variables System operating parameters Trajectory sensitivity; Numerical perturbations applied to the system's operating parameters; S203, Solve the optimization model using the trajectory sensitivity. Specifically, convert the calculated time-varying trajectory sensitivity result into the gradient vector of the total reactive power reserve with respect to the generator excitation voltage parameter in the objective function of the optimization model. The steps are as follows: Use the nonlinear dynamic sensitivity relationship reflected by the partial derivatives to drive the optimization process, solve for the optimal excitation reference voltage of each generator that satisfies all constraints, and then directly rewrite the initial operating state parameters of each synchronous generator in the simulation model to complete the dynamic reconstruction of the simulation grid foundation environment.

[0022] The specific technical effects of step S2 are as follows: When configuring dynamic reactive power compensation devices, by prioritizing the optimization of generator excitation voltage, the transient reactive power support capacity of generators is further explored, reducing the investment cost of reactive power compensation equipment. This is attributed to the physical mechanism that as the generator terminal voltage increases, the transient impact reactive power reserve of generators will be enhanced, and the transient impact reactive power reserve capacity of other generators will also increase without changing the initial operating state of the system. At the same time, by using dynamic nonlinear differential algebraic equations and numerical perturbation method to obtain time-domain trajectory sensitivity, the distortion defects of traditional static sensitivity analysis in dealing with large disturbance nonlinear processes are overcome, providing a highly adaptable and feasible pre-emptive internal potential tapping method for reactive power optimization configuration of large-scale receiving-end power grids.

[0023] S3. Based on the power system simulation model after updating the excitation reference voltage, calculate the dynamic reactive power compensation effect index of each weak node, and perform sequential configuration of the dynamic reactive power compensation device according to the dynamic reactive power compensation effect index.

[0024] In this embodiment, the sequential configuration of the dynamic reactive power compensation device based on the dynamic reactive power compensation effect index includes: S301, inject reactive power changes point by point into each weak node. Extract the voltage change values ​​of each weak node. The dynamic reactive power compensation effect index of each weak node is calculated. Specifically, in order to determine the optimal location of the external dynamic reactive power compensation device, this embodiment adopts the idea of ​​voltage sensitivity analysis to construct the compensation effect index of the reactive power compensation device. Since the ideal installation point of dynamic reactive power compensation is basically consistent with the dominant node (also known as the pilot node) in voltage control theory, that is, when the system voltage fluctuates, the reactive power compensation action of the installation point can minimize the voltage deviation under system disturbance. Therefore, the overall voltage of the system can be controlled by controlling a few dominant nodes. The steps are as follows: In the power system simulation model that updates the excitation reference voltage of each generator in step S2, each identified voltage stability weak node is traversed and used as the scanning node for dynamic reactive power injection. ; at the selected node The change in reactive power applied at the specified rate This paper utilizes time-domain simulation to directly calculate the voltage amplitude evolution trajectory of each node after reactive power injection. Given the complexity of the dynamic processes in high-voltage and high-efficiency power systems, time-domain simulation offers better adaptability. This method is simple in principle, easy to implement, and has no restrictions on component models. It can reflect the influence of parameters such as component capacity and regulation speed, and can achieve full node scanning. The paper also identifies weak voltage stability nodes in the transient simulation output. The voltage response is calculated, and the difference between this and the reference voltage amplitude before reactive power injection is taken to extract the corresponding voltage change value. Ultimately, this The voltage changes at each weak node are substituted into the index formula and summed to quantitatively reflect the overall voltage improvement effect of reactive power compensation at the current node on the weak areas of the entire network. The expression for the dynamic reactive power compensation effect index is as follows: ; In the formula, For the node Effectiveness indicators of installing dynamic reactive power compensation devices; Inject reactive power changes into nodes At that time, weak nodes in voltage stability The voltage change value.

[0025] S302, sort the dynamic reactive power compensation effect index of each weak node from high to low; specifically, the priority of configuration is characterized by comparing the magnitude of the scalar values, so as to accurately screen out a few key buses that play a dominant and decisive role in the system voltage level. The steps are as follows: after collecting the scanning calculation data of all weak nodes, sort the values, sort the compensation effect index of each node from high to low, and generate the corresponding configuration priority candidate queue.

[0026] S303: Install a dynamic reactive power compensation device at the first weak node in the sequence, increment the number of configured devices, and repeatedly execute the calculation and sequencing steps until the number of configured devices reaches a set value. Specifically, considering that the connection of multiple external dynamic reactive power compensation devices will change the dynamic impedance and transient power flow distribution of the overall network, a sequential approximation mechanism must be used to eliminate the nonlinear coupling effects between devices. The steps are as follows: First, install a set of dynamic reactive power compensation devices at the first node in the sequence; set the initial number of configured nodes. The initial value is 0. After each installation of the device, this counter variable is incremented and updated using the following formula: The dynamic mathematical element model of the newly installed reactive power compensation device is incorporated into the current power system simulation model to update the system topology and initial operating state. Then, steps S301 to S303 are repeated, i.e., the updated power system simulation model is called again to recalculate the reactive power change voltage response for weak nodes without the device and to re-rank the performance indicators. The entire sequential configuration process continues cyclically until the number of installed dynamic reactive power compensation devices reaches a preset value, i.e., when the current counting variable is determined... Reaching the specified number of devices The configuration cycle is terminated at the appropriate time, thereby outputting the optimal compensation planning and layout scheme that takes into account both the potential of generators within the grid and the coordination of dynamic devices outside the grid.

[0027] To further illustrate the overall implementation process and technical effects of the optimized configuration method for dynamic reactive power compensation devices in the receiving-end power grid with a high proportion of renewable energy access, this embodiment also provides a specific simulation application example based on a standard calculation system. Specific implementation details are as follows: The power system simulation model is constructed using the IEEE 39-bus system, and the network topology of the system is shown in the attached figure. Figure 2 As shown. In the simulation network structure, nodes 1-29 are PQ nodes, node 31 is a balancing node, and the remaining nodes are generator nodes; the steps are as follows: during simulation initialization, the load of system nodes is adjusted to form a heavy load area, thereby simulating the heavy load operation state of the receiving end under a high proportion of centralized new energy feed-in.

[0028] In the step of identifying voltage stability weak nodes, a simulation model of a 39-node system is built using PSASP power system simulation software, and simulation analysis is performed through power flow calculation and transient calculation programs. The specific steps for setting typical fault scenarios are as follows: When the simulation clock reaches 0.2s, three-phase metallic short-circuit faults are set at the beginning of lines BUS-6-BUS-11 and BUS-23-BUS-24, respectively, and the fault clearing time is controlled to 0.22s. During the time-domain transient simulation calculation, the voltage drop and voltage recovery of each node are observed. Test data shows that under different multi-disturbance line faults, nodes BUS-7, BUS-8, BUS-5, BUS-6, BUS-12, BUS-31, BUS-4, BUS-11, BUS-13, and BUS-10 exhibit the worst voltage drop and voltage recovery. Therefore, the area formed by these nodes is defined as a voltage stability weak region, and these nodes are identified as voltage stability weak nodes.

[0029] In the step of constructing and solving the optimization model with the goal of maximizing the total reactive power reserve of generators, the specific steps are as follows: First, calculate the control sensitivity of the excitation reference voltage and dynamic reactive power reserve of each generator. After discretization and differentiation by numerical perturbation method, the normalized generator excitation voltage control sensitivity data are obtained as shown in Table 1.

[0030] Table 1. Normalized generator excitation voltage control sensitivity

[0031] When solving the optimization model, the specific constraints are as follows: generator node voltage constraints satisfy a per-unit value between 0.95 and 1.05; load node voltage constraints satisfy a per-unit value between 0.95 and 1.05; transformer tap constraints satisfy a per-unit value between 0.95 and 1.05; generator steady-state reactive power output constraints satisfy that the balancing node G31 operates between 0 and 600 MVar, and the steady-state reactive power output of the other generators operates between 0 and 400 MVar. The optimal excitation voltage reference values ​​for each generator are calculated and obtained by performing the optimization solution, as shown in Table 2.

[0032] Table 2 Reference values ​​for optimal excitation voltage of generator

[0033] To illustrate the effectiveness of pre-optimization of generator excitation voltage, the optimal excitation reference voltages for each generator obtained in Table 2 were updated into the power system simulation model. Dynamic voltage fluctuation waveform data of the balancing node under the fault scenario of the BUS-23-BUS-24 line were extracted and compared. The response curves before and after optimization are shown in the attached figures. Figure 3 With appendix Figure 4As shown in the figure, the time-domain trajectory extraction results indicate that before optimizing the generator excitation reference voltage, the node voltage drops to a minimum of 0.9272 pu during the fault period, and the maximum voltage fluctuation after fault clearance is 0.0998 pu. However, after optimizing the generator excitation voltage using the method described in this invention, the node voltage drops to a minimum of 0.974 pu during the fault period, and the maximum voltage fluctuation after fault clearance is 0.0484 pu. Simulation comparison results confirm that pre-optimizing the generator excitation reference voltage changes the initial operating state of the system, suppressing both the dynamic voltage drop amplitude during the fault period and the transient voltage fluctuation after fault clearance.

[0034] In the step of sequentially configuring dynamic reactive power compensation devices based on the dynamic reactive power compensation effect index, the system plans to deploy four 100MVar STATCOMs as dynamic reactive power compensation devices. The steps are as follows: First, in a system environment where the generator excitation reference voltage has been updated, the reactive power compensation effect index formula is called to calculate the effect of configuring dynamic reactive power compensation devices at each node in the voltage-weak region. The effect index of configuring dynamic reactive power compensation devices at the nodes obtained in the first round of scanning is shown in Table 3.

[0035] Table 3. Effects of Node Configuration with Dynamic Reactive Power Compensation Devices

[0036] Based on the first round of calculation and ranking results in Table 3, BUS-31 shows the best compensation effect. Therefore, one STATCOM is installed at this node. Given that the introduction of new reactive power compensation equipment will affect the voltage sensitivity of other nodes, especially neighboring nodes, thus altering the ranking results, if the existing static one-time ranking configuration is used, the marginal effect of subsequent equipment deployment will be significantly lower than the preset value when the nodes with the highest rankings are concentrated in adjacent positions within the same reactive power balance region. To eliminate the dynamic nonlinear coupling effect between the compensation devices, this embodiment strictly implements cyclic sequential optimization. After configuring the first device at node BUS-31, the system impedance and time-domain simulation response are refreshed, and steps S301 to S303 are run again to calculate and rank the performance indicators. In subsequent calculations, the node with the highest compensation performance indicator ranking is changed to BUS-8, BUS-7, and BUS-31. The final compensation scheme for the four sets of dynamic reactive power compensation devices is: BUS-7 compensates 200MVar, BUS-8 compensates 100MVar, and BUS-31 compensates 100MVar. In the BUS-6-BUS-11 line fault scenario, the transient voltage response waveforms of the voltage weak points before and after implementing the final compensation scheme are shown in the attached figures. Figure 5 With appendix Figure 6As shown, the configured time-domain voltage trajectory indicates that the transient voltage drop of each weak bus is effectively blocked and can quickly recover to steady state, verifying the overall technical effect of the collaborative scheme of internal potential mining of the power grid and sequential configuration of external devices.

[0037] Accordingly, embodiments of this application also disclose an optimized configuration device for dynamic reactive power compensation devices in receiving-end power grids with a high proportion of renewable energy access, such as... Figure 7 As shown, the device includes: The weak point identification module is used to establish a power system simulation model of the receiving-end power grid and identify weak nodes in voltage stability based on the power system simulation model. The excitation optimization module is used to construct an optimization model with the goal of maximizing the total reactive power reserve of generators, solve the optimization model to obtain the excitation reference voltage of each generator, and use the excitation reference voltage to update the excitation reference voltage of each generator in the power system simulation model. The sequential configuration module is used to calculate the dynamic reactive power compensation effect index of each weak node based on the power system simulation model after updating the excitation reference voltage, and to perform sequential configuration of the dynamic reactive power compensation device according to the dynamic reactive power compensation effect index.

[0038] The specific workflow of each of the above modules can be found in the relevant content disclosed in the foregoing embodiments, and will not be repeated here.

[0039] Embodiments of this application also provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in the embodiments of the optimized configuration method of dynamic reactive power compensation device in the receiving-end power grid with a high proportion of new energy access described above.

[0040] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0041] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0042] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0043] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0044] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0045] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for optimizing the configuration of dynamic reactive power compensation devices in a receiving-end power grid with a high proportion of renewable energy access, characterized in that, include: Establish a power system simulation model of the receiving-end power grid, and identify weak nodes with voltage stability based on the power system simulation model; An optimization model is constructed with the goal of maximizing the total reactive power reserve of generators. The excitation reference voltage of each generator is obtained by solving the optimization model, and the excitation reference voltage of each generator in the power system simulation model is updated using the excitation reference voltage. Based on the power system simulation model after updating the excitation reference voltage, the dynamic reactive power compensation effect index of each weak node is calculated, and the dynamic reactive power compensation device is sequentially configured according to the dynamic reactive power compensation effect index.

2. The method according to claim 1, characterized in that, Solving the optimization model includes: Establish the dynamic nonlinear differential-algebraic equation system of the receiving-end power grid; The trajectory sensitivity of the state variables and algebraic variables in the dynamic nonlinear differential-algebraic equation system to the system operating parameters is calculated using the numerical perturbation method. The optimization model is solved using the trajectory sensitivity.

3. The method according to claim 1, characterized in that, The total reactive power reserve of the generator is determined based on the contribution of time-varying voltage stability, node importance, and fault scenario severity. The expression for the time-varying voltage stability contribution is as follows: In the formula, For generator In failure scenarios Below Constantly monitor weak points in voltage stability The contribution of time-varying voltage stability; It is a natural number; For generator After a disturbance is applied to the excitation reference voltage, The increment of reactive power output at any given moment compared to before the disturbance; Before excitation reference voltage disturbance Time bus The voltage amplitude; After the excitation reference voltage is disturbed Time bus The voltage amplitude.

4. The method according to claim 3, characterized in that, The expression for the total reactive power reserve of the generator is as follows: In the formula, This represents the total reactive power reserve of the generator. For generator Reactive power standby; For fault scenarios The severity; For weak nodes in voltage stability The importance of nodes; For generator In failure scenarios Below are weak nodes in voltage stability The continuous function of the time-varying voltage stability contribution; For generator exist Reactive power output at any given moment; For generator Reactive power output in steady state; This refers to the number of generators. This represents the number of fault scenarios. The number of weak points in voltage stability.

5. The method according to claim 4, characterized in that, The objective function and constraints of the optimization model are as follows: The objective function is: In the formula, For generator The excitation reference voltage, For generator The change in excitation reference voltage; The constraints include system power flow constraints, generator capacity constraints, node voltage quality constraints, and transformer tap constraints, expressed as follows: In the formula, and These are the active power and reactive power of the generator, respectively. and These are the active power and reactive power of the load, respectively. and They are nodes and nodes The voltage amplitude; For nodes and nodes The voltage phase angle difference; and These are the branch conductance and susceptance, respectively. This represents the total number of nodes in the system. This refers to the number of generators. This refers to the number of ordinary communication nodes; This refers to the number of transformers. and These are the minimum and maximum reactive power outputs of the generator, respectively. and These are the upper and lower voltage limits for the generator node, respectively; and These are the upper and lower voltage limits for a normal AC node; and These are the upper and lower limits of the transformer taps, respectively.

6. The method according to claim 1, characterized in that, The identified weak points in voltage stability include: In areas with heavy loads and fewer than the set number of synchronous generator supports, typical faults are selected for time-domain simulation, and typical fault points around the area are selected for supplementary time-domain simulation. Output the dynamic response data of node voltage in the region under study, define the region with the highest probability of the lowest voltage value during the transient process as the voltage stability weak region, and identify the nodes in the voltage stability weak region as the voltage stability weak nodes.

7. The method according to claim 1, characterized in that, The sequential configuration of the dynamic reactive power compensation device based on the dynamic reactive power compensation effect index includes: The reactive power change is injected point by point into each weak node, the voltage change value of each weak node is extracted, and the dynamic reactive power compensation effect index of each weak node is calculated. The dynamic reactive power compensation effect indicators of each weak node are sorted from high to low. Install a dynamic reactive power compensation device at the weakest node in the first ranking, increment the number of configured devices, and repeatedly execute the calculation and ranking steps until the number of configured devices reaches the set value. The dynamic reactive power compensation effect index is expressed as follows: In the formula, For the node Effectiveness indicators of installing dynamic reactive power compensation devices; When reactive power changes are injected into nodes, weak nodes with low voltage stability The voltage change value; The number of weak points in voltage stability.

8. The method according to claim 4, characterized in that, The expressions for the node importance and the fault scenario severity are as follows: In the formula, For weak nodes in voltage stability Rated transmission power; Weak nodes in voltage stability prior to the fault The voltage amplitude; For weak points in voltage stability during fault clearing The voltage amplitude.

9. An optimized configuration device for dynamic reactive power compensation in a receiving-end power grid with a high proportion of renewable energy access, characterized in that, include: The weak point identification module is used to establish a power system simulation model of the receiving-end power grid and identify weak points in voltage stability based on the power system simulation model. The excitation optimization module is used to construct an optimization model with the goal of maximizing the total reactive power reserve of generators, solve the optimization model to obtain the excitation reference voltage of each generator, and use the excitation reference voltage to update the excitation reference voltage of each generator in the power system simulation model. The sequential configuration module is used to calculate the dynamic reactive power compensation effect index of each weak node based on the power system simulation model after updating the excitation reference voltage, and to perform sequential configuration of the dynamic reactive power compensation device according to the dynamic reactive power compensation effect index.

10. A computer device, comprising a processor and a memory, characterized in that: The memory is used to store a computer program; the processor executes the computer program to implement the method as described in any one of claims 1-8.

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