Intelligent Substation WSN Location Algorithm Based On Decision Theory

Smart grid is based on the physical grid,based on the integration of today's more advanced types of technology and the formation of a new grid.As an important role of energy routing and distribution in smart grid,substations are moving from automation to intelligent development to improve the efficiency of grid operation.According to the different voltage levels,substation construction volume and construction environment vary.From unmanned area to the urban area,from the ground to the ground,from the outside to the interior,the change of substation environment presents a huge challenge to the accuracy of the positioning system.In addition,the wider the range of functions of the substation itself,the positioning system and positioning environment to be covered by the positioning system will therefore also increase.Gathering information and adaptively optimizing the results based on the information and executing the results are the most widely used scenarios for decision theory.Therefore,inspired by decision theory,this paper proposes a wireless sensor network location algorithm based on decision theory.Positioning algorithm running in the positioning system background software services.Intelligent substation positioning system hardware components are mainly divided into sensing side,transmission side,mobile side,console and monitoring cluster server.System software part of the background positioning monitoring system.The sensing end is mainly played by the wireless sensors dispersed in the main collection points and function points inside and outside the substation.Such nodes are anchor nodes in the entire wireless sensor network.Their daily functions are to collect operation data of function points and monitor the signals sent by the mobile terminals.The mobile terminal is mainly portable sensors and inspection robots carried by inbound personnel inside and outside the substation.In the algorithm research,by introducing an intuitionistic fuzzy set,the relationship between the node-to-node distance represented by the received signal strength is expressed in terms of membership,non-affiliation and hesitancy degrees,and the uncertainty information of the environment is reduced.Negative impact between intensity and actual physical distance.Specifically,from the perspective of fuzzy entropy,the degrees of non-membership and hesitation are calculated by membership.According to the knowledge base established by the fuzzy process,the discrepancy between the accepted signal strength and the degree of environmental noise,obstacle and shadowing is quantified by the dispersion method.Then multiply the Lagrange numbers to get the weight of the decision attribute of each anchor node.Offset function to determine the offset of each reference point.The final sort of merit,draw the optimal positioning solution.On the basis of the traditional one-type fuzzy sets,one type of fuzzy is carried out for each type of fuzzy-type one,and the interval type ? fuzzy set is introduced.So that the accepted signal strength can more accurately reflect the relationship between the actual physical distance between nodes.Then,the concept of credibility is established to compare each interval type ? fuzzy set.With the correlation calculation of two-dimensional random variables,the confidence value of each reference node is obtained from the type ? fuzzy set,which is combined with the cooperative game theory Adaptively determine the contribution of each anchor node attribute weights,to determine the location of the optimal location.