Abstract

In this paper, we present a scalable approach for DSM (demand side management) of PHEVs (plug-in hybrid electric vehicles). Essentially, our approach consists of three steps: aggregation, optimization, and control. In the aggregation step, individual PHEV charging constraints are aggregated upwards in a tree structure. In the optimization step, the aggregated constraints are used for scalable computation of a collective charging plan, which minimizes costs for electricity supply. In the real-time control step, this charging plan is used to create an incentive signal for all PHEVs, determined by a market-based priority scheme. These three steps are executed iteratively to cope with uncertainty and dynamism. In simulation experiments, the proposed three-step approach is benchmarked against classic, fully centralized approaches. Results show that our approach is able to charge PHEVs with comparable quality to optimal, centrally computed charging plans, while significantly improving scalability.

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