Baseline Estimation and Scheduling for Demand Response
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abstract
2018 IEEE. Demand Response (DR) programs serve to reduce the demand for electricity at times when the supply is scarce and expensive. Consumers or agents with flexible consumption profiles are recruited by an aggregator who manages the DR program. These agents are paid for reducing their energy consumption from contractually established baselines. Baselines are counter-factual consumption estimates against which load reductions are measured. Baseline consumption and the true cost of load reduction are consumer specific parameters and are unknown to the aggregator. The key components of any DR program are: (a) establishing a baseline against which demand reduction is measured, (b) designing the payment scheme for agents who reduce their consumption from this baseline, and (c) the selection scheme. We propose a self-reported baseline mechanism (SRBM) for the DR program. We show that truthful reporting of baseline and marginal utility is both incentive compatible and individually rational for every consumer under SRBM. We also give a a pod-sorting algorithm based DR scheduling for selecting consumers that is nearly optimal in terms of expected cost of DR provision.
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2018 IEEE Conference on Decision and Control (CDC)