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We consider a novel paradigm for demand side management, assuming that an aggregator communicates with a household only at the meter, imposing a capacity constraint, i.e., a restriction on the total power consumption level within a given time frame. Consumers are then responsible to adjust the set-points of the individual household devices accordingly to meet the imposed constraint. We formulate the problem as a stochastic household energy management program, with stochasticity arising due to local photovoltaic generation. We show how a demand bidding curve for capacity increments can be constructed as a by-product of the developed problem and provide a rigorous pricing analysis that results in a probabilistic “shadow” price envelope. To evaluate the efficacy of the proposed approach, we compare it with an idealized real-time market price set-up and show how our analysis can provide guidelines to consumers when selecting a service contract for load curtailment.
Margellos et al. (Mon,) studied this question.
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