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

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5 Author(s)
Fen Lin ; Chinese Acad. of Sci., Beijing ; Dapeng Zhang ; Zhongzhi Shi ; Minjie Xu
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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.

Published in:

Cognitive Informatics, 6th IEEE International Conference on

Date of Conference:

6-8 Aug. 2007

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