A fuzzy membership filtering aided neural network based transmission loss allocation scheme using game theory
作者:
Highlights:
•
摘要
The present paper proposes development of a transmission loss allocation scheme in a deregulated environment using fuzzy memberships and supervised neural networks. This method can be effectively utilized in online applications where game theory based solutions, which otherwise produce acceptable results, cannot be utilized for prohibitive computation load. We propose a fuzzy membership based approach to filter data from a global database and create a local relevant database, for each transaction detail online, each time. A neural network is trained for each such local database formed and utilized for estimating loss allocations among players, for the transaction detail under consideration. The proposed method has been employed for an IEEE 14 bus system and the results of our proposed method have been shown to be sufficiently accurate, when compared to results obtained by using game theoretic approach.
论文关键词:Artificial neural network,Bilateral transaction,Fuzzy membership,Game theory,Shapley value,Transmission loss allocation
论文评审过程:Available online 5 September 2011.
论文官网地址:https://doi.org/10.1016/j.eswa.2011.09.002