Multi-agent simulation-based residential electricity pricing schemes design and user selection decision-making

• Published in: Natural hazards (Dordrecht) Vol. 90; no. 3; pp. 1309 - 1327
• Main Authors: Wang, Chen, Zhou, Kaile, Li, Lanlan, Yang, Shanlin
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.02.2018; Springer Nature B.V
• Subjects: Civil Engineering; Communication; Communications systems; Computer simulation; Decision making; Earth and Environmental Science; Earth Sciences; Electric power; Electric power demand; Electric power generation; Electric power sources; Electric power supplies; Electricity; Electricity distribution; Electricity pricing; Environmental Management; Geophysics/Geodesy; Geotechnical Engineering & Applied Earth Sciences; Hydrogeology; Intelligent agents; Market prices; Markets; Motivation; Multiagent systems; Natural Hazards; Original Paper; Residential energy; Simulation; User satisfaction; Residential electricity price; Demand response; Multi-agent system; Satisfaction function
• ISSN: 0921-030X; 1573-0840
• DOI: 10.1007/s11069-017-3096-8

Multi-agent system employs the functions of communication, coordination and cooperation among intelligent agents to help people judge and analyze complex phenomena that cannot be directly observed, and it has become an important tool for solving large-scale complex problems. The problem of demand response (DR) in electric power system is difficult to be modeled due to the complicated environment and continuously evolving subjects. Multi-agent system can simulate the operation mechanism of electric power system, thus playing an important role in solving the DR problems. In this study, based on multi-agent simulation, we establish a multi-agent model of residential power market and propose a satisfaction function of residential users about electricity price. We focus on the interaction process among all the agents of power supply side, selling side and demand side and conduct simulation to obtain the selection and decision-making of residential users on different electricity pricing schemes. The results show that multi-agent system is beneficial to analyze, simulate and solve the DR problem in power market. Also, the satisfaction function of residential users on electricity price can support power selling enterprise to better understand the intention of residential users when choosing electricity pricing schemes and participating in DR program.