Research On Evaluation Model Of Power System Black-Start Scheme Based On AP-WRSR Under Incomplete Information

With the gradual maturity of power system arid technology,grid structure and its dynamic performance become more and more complex,despite the continuous development of operation control theory and electronic technology,the large-scale blackout and collapse of the power system cannot be completely avoided.In recent years,environmental pollution problems have shown global trends,the use of fossil energy to pollute the ecological environment is irreversible,renewable energy has been widely concerned and supported by its entire society due to its characteristics of environmentally friendly,and has developed rapidly.But,the renewable energy have also brought greater uncertainty and more severe challenges to the safe and stable operations of the power system,the probability of blackouts have greatly increased,severely endangering the normal production activities of the society.Therefore,it is of great significance to study the problem of system recovery after a power outage,black-start is the first stage of the power system recovery process,it is important to make a quick recovery of the power system to the rapid of the power system.At present,many experts and scholars have developed a set of black-start decision support system to assist dispatchers to perform power restoration work in the power system.This article starts with the optimization module in the black-start decision making system,and conducts an in-depth study on how to accurately and quickly optimize black-start schemes.Based on the serious study and reference of relevant research work at home and abroad,this paper conducts in-depth research on the evaluation methods of black-start schemes,the main research work is as follow:(1)A comprehensive review of domestic and foreign research in field of evaluation of black-start schemes is carried out,on this basis,the basic knowledge of black-start evaluation methods is explained,the key problems existing in black-start evaluation methods are refined,and the current status of the research on these problems by domestic and foreign researchers is introduced.(2)Aiming at the problem of solving index weights under complete black-start data,a black-start evaluation method based on AP weight is proposed.Entropy method in the field of black-start assessment is a common objective weight solution method.In spite of its success,the entropy method suffers from a range of problems,such as large deviation of weight distribution,being unable to reflect small changes of the decision matrix,etc.Therefore,a novel weight determination method based on Affinity Propagation is proposed,this method uses the Affinity Propagation clustering results and the idea of structure similarity to obtain the weight of each index in the black-start schemes,and then uses the simple additive weighting method method to complete the complete ranking of all black-start schemes.Based on the data of Guangdong power system of China,experiments are carried out to investigate the effectiveness of the proposed method.The results show that the proposed method has high accuracy.(3)Aiming at the black-start decision problem in the case of missing data,a black-start evaluation method based on EM padding and weighted rank sum ratio is proposed.In the actual power production practice,due to factors such as equipment aging,data complexity,and carelessness of operation dispatchers,there will be omissions of indicator value data.Therefore,the optimization module must have the ability to deal with the evaluation of power system black-start schemes under incomplete information.The method first uses the EM algorithm to fill in the black-start scheme evaluation null values,and obtains a complete black-start evaluation matrix;then,according to the difference between the indicators,the weight of each index is obtained by the difference weight method;finally,the weighted rank sum ratio method is used to determine the scoring value of each black-start scheme realizes the classification and complete sorting of black-start schemes.Based on the data of Guangdong power system of China,experiments are carried out to investigate the effectiveness of the proposed method.The results show that the proposed method has high accuracy.(4)On the basis of the above AP weight and EM filling research,the problem of black-start group decision making under incomplete information is studied,a black-start group evaluation method based on genetic algorithm is proposed.The group evaluation method can obtain more accurate results than the individual evaluation method,therefore,it is of great significance to introduce the group evaluation method into the evaluation of the black-start scheme.First,the EM algorithm is used to predict and fill in the missing data in the black-start scheme,and the AP weight method is used on the formed complete black-start scheme data set to obtain objective weights,and merge with the subjective weights of experts to obtain comprehensive weights,constructing each expert’s black-start weighted evaluation matrix.The TOPSIS method is used to obtain the black-start scoring vector of each expert,and the expert weight is calculated by the genetic algorithm,and the expert weight and the expert black-start scheme scoring vector are assembled,and finally the black-start scheme is ranked.Based on the data of Guangdong power system of China,experiments are carried out to investigate the effectiveness of the proposed method.The results show that the proposed method has high accuracy.