Artificial intelligence based algorithm for customers to take advantage of the real time pricing systems - Hu, Anshuang. (2008)
Real Time Pricing (RTP) system is becoming more and more important for both electric utility industries and their customers. Many electric utilities and their customers have replaced the traditional Time of Use (TOU) system with the RTP system. This is a reality as well as a trend since the benefits under the RTP system are quite substantial economically. This thesis proposes a method of using the medium concept for the customers to take advantage of the RTP system. It uses the artificial intelligent techniques to realize the proposed idea. Fuzzy logic is utilized to set up the load forecast model. Genetic algorithm is utilized to determine the coefficients of the energy state equation, and a non-simplex method is utilized to fulfill the optimal distribution of the supply energy. Finally, the effect of the thermal storage energy loss (TSEL) to the optimization scheduling under the RTP system is investigated. Some simulation results are presented to illustrate the proposed method and some analyses of the related contents are put forward.