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A multi-agent system of evaluating residential demand response

This paper presents a multi-agent system (MAS) to evaluate implementation of the residential demand response (DR), in which the main stakeholders are modeled by a class of software agents including Conventional Home Agents, Smart Home Agents, and a Utility Agent. DR is a recent effort to improve efficiency of the electricity market and the stability of the power system. We develop a Residential Load Model, a Dynamic Price Model, an Energy Management System Model, a Primary Power Plant Model and a Secondary Power Plant Model, which are further incorporated into the MAS. Simulation results show that, without the assistance of the home energy management system (EMS) or other similar technologies, the strategy of dynamic price does not lead to a successful DR application. However, by scheduling controllable load using the home EMS, the peak demand and demand standard deviation is dramatically reduced by 23.8% and 41.6% respectively, and the generation cost also decreases by 30.8%. The scheduling algorithm can be embedded into a home EMS. The proposed agent system can be utilized to evaluate various strategies, emerging techniques and algorithms that enable the DR implementation.