Maturity Model Establishment And Evaluation Of Smart Substation Based On GABP Neural Network

A series of challenges such as resource constraints,environmental pollution and climate change are driving the transformations that the global economy from a traditional high-carbon development model to a low-carbon development model and smart grid is the main way to achieve a low-carbon economy.Smart substation is an important part of smart grid and an important support for building smart grid.This paper takes smart substation as the research object,researches smart substation as an individual with "maturity" and evaluates the development status of smart substation as a whole,on the one hand the evaluation results can provide a reference direction for the current stage of the construction or transformations of smart substation;on the other hand the evaluation method can be exported to abroad,thereby increasing China's influence in foreign academic circles and then increasing China's international statue and voice.Therefore,the research in this paper not only has theoretical significance but also has practical value.There are three main tasks in this paper: firstly,proposing the Smart Substation Maturity Model(SSMM)and elaborating the meaning characteristics of each grade;secondly,constructing the smart substation maturity evaluation model based on BP neural network;thirdly,constructing the smart substation maturity evaluation model based on GABP neural network and carrying out an actual verification.Based on the in-depth analysis of the structural characteristics of smart substation and the factors affecting its maturity,takig the five dimensions of electrical equipment,power supply quality,economic value,social personnel and environmental protection indicators as criteria,a total of 20 specific evaluation indicators have been established,then comprehensively analyze the advantages and disadvantages of the existing methods of determining index weights and the analytic hierarchy process is finally selected as the method to determine the weights of each evaluation indicator.On the basis of completing these tasks,firstly,briefly describe the definitionconcept of neural network and according to the principles of neural network construction,establish a maturity evaluation model of smart substation based on BP neural network,then train and simulate;aiming at the shortcomings of BP neural network,such as long convergence time and low convergence accuracy,the genetic algorithm(GA)is used to optimize the BP neural network,establish a maturity evaluation model of smart substation based on GABP neural network,then train and simulate;by comparing and analyzing the prediction simulation results of the two models and selecting GABP neural network as the algorithm to evaluate the maturity of smart substation.Finally,the analytic hierarchy process and GABP neural network are used for the evaluation of the actual substation,and the future development opinions and suggestions of the substation are given based on the evaluation results.