CN-121998482-A - Electric energy quality improvement effect evaluation method and system for large-sized electric vehicle charging station

CN121998482ACN 121998482 ACN121998482 ACN 121998482ACN-121998482-A

Abstract

The invention relates to the technical field of interaction between an electric vehicle and a power grid, in particular to a method and a system for evaluating the electric energy quality improvement effect of a charging station of a large-sized electric vehicle, wherein the method comprises the steps of obtaining and constructing an original data matrix, and carrying out standardized pretreatment on heterogeneous index data; the method comprises the steps of adopting an improved three-gradient analytic hierarchy process to analyze judgment information of importance of electric energy quality indexes in a charge-discharge switching scene by an expert, constructing a judgment matrix, calculating index subjective weights, adopting an entropy weight process based on divergence maximization to process measured data of a charging station under different operation conditions, calculating index objective weights, adopting a cooperative fusion model of the main and objective weights constructed by relative entropy distances, calculating to obtain optimal combination weights based on vehicle network interaction V2G scene decision guiding and mining data internal regular targets, and adopting a multi-criterion compromises sequencing VIKOR algorithm introducing weights and ideal solutions for dynamic adjustment to carry out final priority sequencing on lifting effects of different technical schemes.

Inventors

ZENG FEI
PAN YI
DAI KEMIN
WU HANSONG
LV SIYU
JIANG YETING
MIAO HUIYU
XU SHUAIQI
YUAN XIAODONG
ZHU YING
WU CHUANSHEN
SUN GUOQIANG
WANG MINGSHEN
LI XIANGCHAO

Assignees

国网江苏省电力有限公司电力科学研究院
河海大学
国网江苏省电力有限公司无锡供电分公司

Dates

Publication Date: 20260508
Application Date: 20251230

Claims (10)

1. The method for evaluating the electric energy quality improvement effect of the large electric vehicle charging station is characterized by comprising the following steps of: Acquiring and constructing an electric energy quality evaluation original data matrix aiming at a large-scale electric vehicle charging station, wherein the original data matrix at least comprises voltage deviation, frequency deviation, harmonic distortion rate and three-phase unbalance degree, and carrying out standardized pretreatment on heterogeneous index data; adopting an improved three-gradient analytic hierarchy process to analyze judgment information of the importance of the power quality index in a charge-discharge switching scene by an expert, constructing a judgment matrix and calculating the subjective weight of the index; Adopting an entropy weight method based on divergence maximization to process measured data of the charging station under different operation conditions, and calculating an index objective weight; Constructing a collaborative fusion model of subjective and objective weights by adopting a relative entropy distance, and calculating to obtain an optimal combination weight of an intrinsic rule target based on vehicle-network interaction V2G scene decision guiding and mining data; and calculating group utility values, individual regrets and compromise evaluation indexes corresponding to the running states of the charging stations under different power supply quality improvement schemes based on the optimal combination weights by adopting a multi-criterion compromised solution ordering VIKOR algorithm with introduced weights and ideal solution dynamic adjustment, and finally ordering the improvement effects of different technical schemes according to the group utility values, the individual regrets and the compromise evaluation indexes.
2. The method for evaluating the power quality improvement effect of a large electric vehicle charging station according to claim 1, wherein the standardized preprocessing of the heterogeneous index data comprises: The original data matrix is formed by n observation points and m evaluation indexes In order to eliminate the dimension influence, preprocessing the data by adopting a nonlinear standardization method; for the benefit index, the standardized formula is: ; for the cost index, the standardized formula is: ; in the formula, As an observation value after the normalization, For the observation prior to normalization, 、 The upper and lower limits of the standardized interval, respectively.
3. The method for evaluating the effect of improving the electric energy quality of a charging station for a large electric vehicle according to claim 1, wherein the steps of analyzing the judgment information of the importance of the electric energy quality index in the charge-discharge switching scene by the expert, constructing the judgment matrix and calculating the subjective weight of the index include: constructing a three-gradient judgment matrix: ; in the formula, =1 Means that index i is more important than index j, =0 Indicates that index i is equally important as index j, -1 Indicates that index i is less important than index j; Calculating a relative dominance matrix B: ; in the formula, Is a hyperbolic tangent function for smoothing differences; Solving a matrix Corresponding feature vector of the maximum feature value of the (a) and normalizing the feature vector to obtain a subjective weight vector 。
4. The method for evaluating the power quality improvement effect of a large electric vehicle charging station according to claim 3, wherein the step of processing measured data of the charging station under different operation conditions by using an entropy weighting method based on divergence maximization, and calculating an objective weight of an index comprises: Calculate the first Under the index of Individual observations Specific gravity of (2) : ; Calculate the first Entropy value of individual index And degree of divergence : ; ; For the degree of divergence Normalizing to obtain objective weight vector : ; In the formula, Is the objective weight of the j index.
5. The method for evaluating the electric energy quality improvement effect of a large electric vehicle charging station according to claim 4, wherein the constructing a collaborative fusion model of subjective and objective weights by using a relative entropy distance comprises: calculating subjective weights Objective weight Relative to its arithmetic mean weight Relative entropy of (2): ; Relative entropy And The degree of deviation of the subjective weight and the objective weight from the average weight is measured respectively, and a fusion coefficient is calculated based on the degree of deviation: ; final combining weights The method comprises the following steps: 。
6. the method for evaluating the power quality improvement effect of a large electric vehicle charging station according to claim 1, wherein the multi-criterion compromises a rank VIKOR algorithm employing an introduced weight and an ideal solution dynamic adjustment, comprises: determining a weighted normalization matrix: ; in the formula, For the combining weight of the j-th index, Is the observed value after standardization; Weight factors are introduced, and a dynamic ideal solution is defined as follows: Positive ideal solution: ; Negative ideal solution: ; in the formula, The method is used for adjusting parameters, is used for making the index with larger weight, and has the advantages of wider range of ideal solutions and enhanced distinction of important indexes in decision making.
7. The method for evaluating the power quality improvement effect of a large electric vehicle charging station according to claim 6, wherein calculating the group utility value, the individual regressive value and the compromise evaluation index corresponding to the charging station operation states under different power quality improvement schemes based on the optimal combination weight, and performing final ranking on the improvement effects of different technical schemes according to the group utility value, the individual regressive value and the compromise evaluation index comprises: calculating group utility values And individual regret values : ; Calculating a compromise evaluation index : ; In the formula, , , , , Is a decision mechanism coefficient; According to The values are ordered from small to large, The smaller the value, the better the integrated level of power quality representing the observation point.
8. A large electric vehicle charging station power quality improvement effect evaluation system, characterized in that a method according to any one of claims 1 to 7 is used, the system comprising: The system comprises an acquisition unit, a data processing unit and a data processing unit, wherein the acquisition unit is used for acquiring and constructing an electric energy quality evaluation original data matrix aiming at a large-sized electric vehicle charging station, and the original data matrix at least comprises voltage deviation, frequency deviation, harmonic distortion rate and three-phase unbalance degree, and performs standardized pretreatment on heterogeneous index data; The subjective weight unit is used for analyzing the judgment information of the importance of the power quality index in the charge-discharge switching scene by an expert by adopting an improved three-gradient analytic hierarchy process, constructing a judgment matrix and calculating the subjective weight of the index; The objective weight unit is used for processing actual measurement data of the charging station under different operation conditions by adopting an entropy weight method based on the maximization of the divergence, and calculating an index objective weight; the combination weight unit is used for constructing a collaborative fusion model of the subjective and objective weights by adopting the relative entropy distance, and calculating to obtain the optimal combination weight of the intrinsic rule target based on vehicle-network interaction V2G scene decision guiding and mining data; The evaluation unit is used for calculating group utility values, individual regrets and compromise evaluation indexes corresponding to the running states of the charging stations under different power supply quality improvement schemes based on the optimal combination weights by adopting a multi-criterion compromised solution ordering VIKOR algorithm with introduced weights and ideal solution dynamic adjustment, and finally ordering the improvement effects of different technical schemes according to the group utility values, the individual regrets and the compromise evaluation indexes.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any of claims 1-7 when executing the computer program.
10. A storage medium having stored thereon a computer program which, when executed by a processor, implements the method of any of claims 1-7.

Description

Electric energy quality improvement effect evaluation method and system for large-sized electric vehicle charging station Technical Field The invention relates to the technical field of interaction between an electric vehicle and a power grid, in particular to a method and a system for evaluating the electric energy quality improving effect of a charging station of a large-sized electric vehicle. Background Along with the large-scale development of electric vehicles and the popularization and application of vehicle network interaction technology, a large-sized electric vehicle charging station becomes a novel power load unit with charge and discharge bidirectional power adjustment capability. The random switching of a large number of electric automobile charge and discharge states in the charging station causes the electric energy quality problems of characteristics such as aggravation of voltage deviation, enhancement of frequency fluctuation, complexity of harmonic frequency spectrum and the like in the station. The effective management and evaluation of the problems directly relate to the operation safety of the charging station and the power supply quality of the power distribution network, and urgent requirements are also provided for the effect verification of the station power supply quality improvement technology suitable for freely switching the charging and discharging states. In terms of power quality evaluation, the prior art mainly extends around two links of weight determination and comprehensive evaluation. The subjective and objective combined weighting method can give consideration to the advantages of the subjective and objective combined weighting method, but the traditional fusion method lacks theoretical basis when determining the weight ratio, and does not consider the specificity of the charging and discharging scene of the electric automobile. In the aspect of a comprehensive evaluation model, the conventional method such as fuzzy comprehensive evaluation, TOPSIS and the like has obvious defects in processing charging station evaluation objects with multiple working conditions and strong conflict index characteristics, wherein membership functions of the fuzzy comprehensive evaluation determine subjectivity, although the TOPSIS method can determine positive and negative ideal solutions, the approach degree of an evaluation scheme and the ideal solution and the balance inside the scheme cannot be fully considered, and when the ideal solution is determined, the conventional VIKOR method cannot fully consider the difference of importance of different indexes, so that the decision function of key quality indexes is weakened. At present, aiming at the evaluation of the electric energy quality improvement effect of a large-sized electric automobile charging station, the prior art has the defects that a special evaluation index system adapting to a charging and discharging switching scene is not established, the relative importance of each electric energy quality index in a V2G operation mode cannot be embodied by a weight distribution method, and the transverse comparison capability of different power supply quality improvement technical schemes is lacking in an evaluation model. The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art. Disclosure of Invention The invention provides a method and a system for evaluating the electric energy quality improvement effect of a large-sized electric vehicle charging station, thereby effectively solving the problems in the background technology. In order to achieve the aim, the technical scheme adopted by the invention is that the method for evaluating the electric energy quality improving effect of the large-sized electric vehicle charging station comprises the following steps: Acquiring and constructing an electric energy quality evaluation original data matrix aiming at a large-scale electric vehicle charging station, wherein the original data matrix at least comprises voltage deviation, frequency deviation, harmonic distortion rate and three-phase unbalance degree, and carrying out standardized pretreatment on heterogeneous index data; adopting an improved three-gradient analytic hierarchy process to analyze judgment information of the importance of the power quality index in a charge-discharge switching scene by an expert, constructing a judgment matrix and calculating the subjective weight of the index; Adopting an entropy weight method based on divergence maximization to process measured data of the charging station under different operation conditions, and calculating an index objective weight; Constructing a collaborative fusion model of subjective and objective weights by adopting a relative entropy dista