A Novel Simulation Approach For Estimating Residential Power Demand Based on Multi-Agent Society

The estimation of residential power demand function is an issue of growing significance among policy makers. In this paper, we propose a novel approach to apply multi-agent society to residential power demand estimation. A hybrid social model for more accurate power demand estimation is presented, which extends traditional models by adding a social simulation layer to capture social responsiveness on power conservation policies. To support policy makers in their decisions, we develop a software tool RPDS (residential power demand simulator) for evaluating power-pricing policies, implemented as a multi-agent society. It takes a step ahead in the estimation applied in the residential power demand sector, in which consumers behavior and social interactions are considered and the emergence of social intelligence is realized.