Electric power system robustness optimization system

Abstract

The invention discloses an electric power system robustness optimization system, relates to an electric power system robustness optimization device, and aims to solve the problem that the existing electric power system robustness optimization method cannot ensure the performance of an electric power system under large disturbance. According to the invention, an optimization process establishment module is used for establishing a simulation-based power system robustness analysis process; the evaluation module is used for carrying out robustness evaluation on the robustness analysis process established by the optimization process establishment module and outputting a robustness evaluation result; and the optimization module is used for optimizing the robustness of the power system based on the robustness evaluation result output by the evaluation module. The method has the beneficial effect that the performance of the power system under large disturbance is ensured.

Description

Technical Field

[0001] The invention relates to a device for optimizing the robustness of an electric power system. Background Art

[0002] Robustness is a special term in statistics, which is used to characterize the insensitivity of control systems to characteristic or parameter disturbances. In multivariate cases, robustness is regarded as the sensitivity of the model's predictive ability to changes in external factors (variations in the environment, equipment, and sampling conditions). After the independent power system is developed and put into operation, there are not only small disturbances such as aging, wear, and changes in environmental and operating conditions, but also large disturbances such as high-power load shedding and system failures. Since the laboratory resources cannot fully support the verification under these disturbance conditions, especially the verification of various fault conditions, the system that can operate normally in the laboratory may not meet the design requirements under certain actual conditions. Therefore, in the component design stage, the robust design method based on component prototype experiments can be used to optimize the design of each component in the system separately, hoping to achieve the performance of the independent power system from the influence of design technology, component parameters, manufacturing process, aging and changes in operating conditions, and the designed system can meet the expected performance standard requirements, and to ensure the purpose of safe operation of the system to a greater extent. At the same time, the simplest and most cost-effective design is achieved to avoid over-design of the system; however, the existing file design method based on component prototype implementation to perform robustness optimization of the power system cannot guarantee the performance of the power system under large disturbances. Summary of the invention

[0003] The purpose of the present invention is to solve the problem that the existing power system robustness optimization method cannot guarantee the performance of the power system under large disturbances, and proposes a power system robustness optimization system.

[0004] The power system robustness optimization system described in the present invention comprises an optimization process establishment module, an evaluation module and an optimization module;

[0005] Optimization process establishment module, used to establish a simulation-based power system robustness analysis process;

[0006] The evaluation module is used to perform robustness evaluation on the robustness analysis process established by the optimization process establishment module and output the robustness evaluation results;

[0007] The optimization module optimizes the robustness of the power system based on the robustness evaluation results output by the evaluation module.

[0008] Further, the optimization process establishment module includes a rated design module, a sensitivity analysis module, a statistical analysis module, a stress analysis module and a failure mode analysis module;

[0009] The rated design module is used to build a power system model, perform time domain simulation on the power system model under rated conditions, obtain simulation data of voltage and current, and use the simulation data of voltage and current to analyze two levels of indicators: steady-state characteristic indicators and dynamic characteristic indicators;

[0010] The sensitivity analysis module is used to apply small positive and negative disturbances to each parameter of the system model according to the set parameter disturbance ratio, perform system simulation and record the system response dynamic characteristic indicators, calculate the sensitivity per unit value of different parameters relative to different system response dynamic characteristic indicators, until the sensitivity analysis of all parameters in the system model is completed;

[0011] The statistical analysis module is used to simulate noise factors to perform Monte Carlo simulation on the power system model based on Latin hypercube sampling, and obtain information on the two levels of indicators of steady-state characteristic indicators and dynamic characteristic indicators of the established power system model parameters under uncertain noise factors;

[0012] The stress analysis module is used to search the voltage and current data of each component from the simulation results that meet the requirements of the steady-state characteristic index in the statistical analysis, obtain the maximum stress rate, and perform stress analysis based on the maximum stress rate;

[0013] The fault mode analysis module is used to model the faults that need to be analyzed in an independent power system model. By setting components to fail in multiple ways at specific times, it studies how the system performance is affected when a single fault or a combined fault mode occurs in the component, and obtains the two-level indicator analysis results of the system under the fault mode.

[0014] Furthermore, the steady-state characteristic indicators in the rated design module and the statistical analysis module are defined as primary indicators, which are used to reflect the steady-state function of the power system and indicate that the current system is in a stable operating state; the dynamic characteristic indicators in the rated design module and the statistical analysis module are defined as secondary indicators, which are used to reflect the dynamic performance of the independent power system and measure the dynamic performance of the system when it is subjected to different disturbances.

[0015] Furthermore, the specific steps of the evaluation module for performing robustness evaluation on the robustness analysis process are as follows:

[0016] Step 1: Determine the robustness assessment indicators of the power system;

[0017] Step 2: Determine a power system robustness assessment method based on the power system robustness assessment index determined in step 1;

[0018] Step 3: Evaluate the robustness of the independent power system according to the independent power system robustness evaluation method determined in step 2.

[0019] Furthermore, the optimization module includes a parameter analysis module and a parameter determination module;

[0020] Parameter analysis module, which performs independent power system parameter analysis based on Pareto analysis and outputs analysis results;

[0021] The parameter determination module is used to determine the parameters of the robust optimization design of the power system according to the analysis results output by the parameter analysis module.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] The optimization process establishment module of the present invention can quantitatively evaluate the robustness advantages and disadvantages of different designs of the power system, including different protection strategies, different control logics, different design parameters, etc., so as to make candidate design decisions; the optimization module can optimize the system performance of the established design, improve the robustness of the power system, and ensure the performance of the power system under large disturbances. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A structural block diagram of a power system robustness optimization system according to a specific implementation mode 1;

[0025] Figure 2 It is a structural block diagram of the optimization module in the fifth specific implementation method. DETAILED DESCRIPTION

[0026] Specific implementation method 1. Combination Figure 1 This embodiment is described. This embodiment is a power system robustness optimization system, and the robustness optimization system includes an optimization process establishment module 1, an evaluation module 2 and an optimization module 3;

[0027] Optimization process establishment module 1, used to establish a simulation-based power system robustness analysis process;

[0028] Evaluation module 2 is used to perform robustness evaluation on the robustness analysis process established by optimization process establishment module 1 and output robustness evaluation results;

[0029] The optimization module 3 optimizes the robustness of the power system based on the robustness evaluation result output by the evaluation module 2.

[0030] In this embodiment, the optimization process is used to establish module 1, which can quantitatively evaluate the robustness of different designs of the power system, including different protection strategies, different control logics, different design parameters, etc., so as to make candidate design decisions; the optimization module 3 can optimize the system performance of the established design, improve the robustness of the power system, and ensure the performance of the power system under large disturbances; the power system robustness optimization system described in this embodiment adopts a modular design, which reduces the number of iterations of the hardware experimental prototype to achieve the purpose of optimizing the power system development process, and provides an effective solution for optimizing system performance, improving system development efficiency, and saving development costs.

[0031] Specific implementation method 2, this implementation method further limits the power system robustness optimization system described in specific implementation method 1. In this implementation method, the optimization process establishment module 1 includes a rated design module, a sensitivity analysis module, a statistical analysis module, a stress analysis module and a failure mode analysis module;

[0032] The rated design module is used to build a power system model, perform time domain simulation on the power system model under rated conditions, obtain simulation data of voltage and current, and use the simulation data of voltage and current to analyze two levels of indicators: steady-state characteristic indicators and dynamic characteristic indicators;

[0033] The sensitivity analysis module is used to apply small positive and negative disturbances to each parameter of the system model according to the set parameter disturbance ratio, perform system simulation and record the system response dynamic characteristic indicators, calculate the sensitivity per unit value of different parameters relative to different system response dynamic characteristic indicators, until the sensitivity analysis of all parameters in the system model is completed;

[0034] The statistical analysis module is used to simulate noise factors to perform Monte Carlo simulation on the power system model based on Latin hypercube sampling, and obtain information on the two levels of indicators of steady-state characteristic indicators and dynamic characteristic indicators of the established power system model parameters under uncertain noise factors;

[0035] The stress analysis module is used to search the voltage and current data of each component from the simulation results that meet the requirements of the steady-state characteristic index in the statistical analysis, obtain the maximum stress rate, and perform stress analysis based on the maximum stress rate;

[0036] The fault mode analysis module is used to model the faults that need to be analyzed in an independent power system model. By setting components to fail in multiple ways at specific times, it studies how the system performance is affected when a single fault or a combined fault mode occurs in the component, and obtains the two-level indicator analysis results of the system under the fault mode.

[0037] In this embodiment, the function of the rated design module is to use the results of the rated design to establish the response target / reference benchmark for the other four analyses in the robustness analysis process; when performing the rated design, as long as the output voltage value of the model can enter the stable voltage error band (such as ±5%) within a certain period of time, it is considered that the current system stability does not meet the engineering reality;

[0038] The workflow of the rated design module is as follows: S1, building a target power system model;

[0039] S2, setting the power system model parameters to the rated state;

[0040] S3, setting the simulation working condition of the power system model to the rated state;

[0041] S4, power system time domain simulation to obtain model output voltage and current simulation data;

[0042] S5, extracting steady-state characteristic indicators;

[0043] S6. Determine whether the steady-state characteristic index meets the design requirements.

[0044] , execute step S7; otherwise, when the steady-state characteristic index does not meet the design requirements, return to execute step S2;

[0045] S7, extracting dynamic characteristic indicators;

[0046] S8. Determine whether the dynamic characteristic index meets the design requirements. When the dynamic characteristic index meets the design requirements, end; otherwise, when the dynamic characteristic index does not meet the design requirements, return to step S2.

[0047] Specific implementation method three. This implementation method further limits the power system robustness optimization system described in specific implementation method two. In this implementation method, the steady-state characteristic indicators in the rated design module and the statistical analysis module are defined as primary indicators, which are used to reflect the steady-state function of the power system and indicate that the current system is in a stable operating state; the dynamic characteristic indicators in the rated design module and the statistical analysis module are defined as secondary indicators, which are used to reflect the dynamic performance of an independent power system and measure the dynamic performance of the system when it is subjected to different disturbances.

[0048] In this embodiment, the steady-state characteristic index and the dynamic characteristic index are used to select the best from the best system design while ensuring that the steady-state performance meets the requirements.

[0049] Specific implementation method 4: This implementation method further limits the power system robustness optimization system described in specific implementation method 2. In this implementation method, the specific steps of the evaluation module 2 performing robustness evaluation on the robustness analysis process are as follows:

[0050] Step 1: Determine the robustness assessment indicators of the power system;

[0051] Step 2: Determine a power system robustness assessment method based on the power system robustness assessment index determined in step 1;

[0052] Step 3: Evaluate the robustness of the independent power system according to the independent power system robustness evaluation method determined in step 2.

[0053] In this embodiment, the probability measurement of the robustness of the power system is called robustness. The system dynamic performance indicators and the corresponding weights of the dynamic performance indicators in the robustness assessment of the power system are considered in the robustness calculation; the weights are given by the empirical method or the hierarchical analysis method; among them, the method of giving weights by the empirical method is: the designer directly gives weights based on similar cases in the past or personal experience; the method of giving weights by the hierarchical analysis method is: assigning a total weight value of 1 to the target layer, and then assigning the total weight to different indicators in the indicator layer, and the weight size of the corresponding indicator represents the importance of the factor in the system robustness assessment process. Since it is difficult to directly assign weights to factors of different natures, all factors are not compared together, but are compared with each other two by two.

[0054] The independent power system robustness assessment method is determined in two ways: one is to conduct an assessment based on a determined power system robustness assessment index, and the other is to conduct an assessment based on whether the system is stable.

[0055] Specific implementation method V. Combination Figure 2 This embodiment is described. This embodiment further limits the power system robustness optimization system described in the specific embodiment 4. In this embodiment, the optimization module 3 includes a parameter analysis module 3-1 and a parameter determination module 3-2;

[0056] Parameter analysis module 3-1, performs independent power system parameter analysis based on Pareto analysis and outputs analysis results;

[0057] The parameter determination module 3-2 is used to determine the parameters of the robust optimization design of the power system according to the analysis results output by the parameter analysis module.

[0058] In this embodiment, the dynamic performance index will decrease as the parameter increases, and increase as the parameter decreases; at the same time, in this embodiment, all parameters are randomly selected as long as they are within their tolerance range, and the sensitivity analysis does not include the influence of parameter interaction; in order to obtain the lowest possible overshoot, the value of the capacitor will increase, resulting in an increase in the volume mass of the capacitor.

[0059] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A power system robustness optimization system, characterized in that: The robust optimization system comprises an optimization process establishment module (1), an evaluation module (2) and an optimization module (3); An optimization process establishment module (1) is used to establish a simulation-based power system robustness analysis process; An evaluation module (2) is used to perform a robustness evaluation on the robustness analysis process established by the optimization process establishment module (1) and output a robustness evaluation result; The optimization module (3) optimizes the robustness of the power system based on the robustness evaluation result output by the evaluation module (2).

2. A power system robustness optimization system according to claim 1, characterized in that: The optimization process establishment module (1) includes a rated design module, a sensitivity analysis module, a statistical analysis module, a stress analysis module and a failure mode analysis module; The rated design module is used to build a power system model, perform time domain simulation on the power system model under rated conditions, obtain simulation data of voltage and current, and use the simulation data of voltage and current to analyze two levels of indicators: steady-state characteristic indicators and dynamic characteristic indicators; The sensitivity analysis module is used to apply small positive and negative disturbances to each parameter of the system model according to the set parameter disturbance ratio, perform system simulation and record the system response dynamic characteristic indicators, calculate the sensitivity per unit value of different parameters relative to different system response dynamic characteristic indicators, until the sensitivity analysis of all parameters in the system model is completed; The statistical analysis module is used to simulate noise factors to perform Monte Carlo simulation on the power system model based on Latin hypercube sampling, and obtain information on the two levels of indicators of steady-state characteristic indicators and dynamic characteristic indicators of the established power system model parameters under uncertain noise factors; The stress analysis module is used to search the voltage and current data of each component from the simulation results that meet the requirements of the steady-state characteristic index in the statistical analysis, obtain the maximum stress rate, and perform stress analysis based on the maximum stress rate; The fault mode analysis module is used to model the faults that need to be analyzed in an independent power system model. By setting components to fail in multiple ways at specific times, it studies how the system performance is affected when a single fault or a combined fault mode occurs in the component, and obtains the two-level indicator analysis results of the system under the fault mode.

3. A power system robustness optimization system according to claim 2, characterized in that: The steady-state characteristic index in the rated design module and the statistical analysis module is defined as a primary index, which is used to reflect the steady-state function of the power system and indicates that the current system is in a stable operating state; The dynamic characteristic indicators described in the rated design module and the statistical analysis module are defined as secondary indicators, which are used to reflect the dynamic performance of the independent power system and measure the dynamic performance of the system when it is subjected to different disturbances.

4. A power system robustness optimization system according to claim 2, characterized in that: The specific steps of the evaluation module (2) for performing robustness evaluation on the robustness analysis process are as follows: Step 1: Determine the robustness assessment indicators of the power system; Step 2: Determine a power system robustness assessment method based on the power system robustness assessment index determined in step 1; Step 3: Evaluate the robustness of the independent power system according to the independent power system robustness evaluation method determined in step 2.

5. A power system robustness optimization system according to claim 4, characterized in that: The optimization module (3) comprises a parameter analysis module (3-1) and a parameter determination module (3-2); Parameter analysis module (3-1), performs independent power system parameter analysis based on Pareto analysis and outputs analysis results; The parameter determination module (3-2) is used to determine the parameters of the robust optimization design of the power system according to the analysis results output by the parameter analysis module.

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