Large customer price response simulation under time-of-use electricity pricing policy based on multi-agent system

Authors:
Yu Shunkun;Yuan Jiahai;Zhao Changhong
Affiliations:
School of Business Administration, North China Electric Power University, Beijing, China;School of Business Administration, North China Electric Power University, Beijing, China;School of Business Administration, North China Electric Power University, Beijing, China
Venue:
ACOS'06 Proceedings of the 5th WSEAS international conference on Applied computer science
Year:
2006

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Abstract

To enhance the effectiveness of electricity time-of-use (TOU) pricing, the mechanism of customer TOU response, especially that of large customer, should be researched thoroughly. Therefore multi-agents simulation is introduced. In simulation research TOU price response is taken as a decentralized decision process of all related customers, while Power Supply Corporation can dynamically adjust its policy according to customer response. The paper discusses in details with the design principle and framework of the simulation system. In the system customer agent is implemented as responsive agent with its response rules built on fuzzy logic, utility agent is implemented as learning agent with Classifier Learning Algorithm as its learning rules, then environment management module manages the interaction between them. Then the simulation flow is given and finally a case study based on a real power supply corporation is given and simulation results reported.