Generalized Minimax: A Self-Enforcing Pricing Scheme for Load Aggregators

• Published in: IEEE transactions on smart grid 2018-05, Vol.9 (3), p.1953-1963
• Main Authors: Sedzro, Kwami Senam, Lamadrid, Alberto J., Chuah, Mooi Choo
• Format: Article
• Language: English
• Subjects: Aggregates; Contracts; demand response; Electronic mail; Load modeling; Optimization; Pricing; Retail electricity pricing; stochastic generation; Uncertainty
• ISSN: 1949-3053; 1949-3061
• DOI: 10.1109/TSG.2016.2602870

This paper introduces a novel electricity retail pricing scheme we designate generalized minimax (GenMinimax). GenMinimax is characterized by three rate zones with the narrowest in the middle, called threshold band, constituting the attraction zone where the lowest rate is charged. The scheme is designed so that the threshold band envelops a negotiated reference consumption profile. We consider a cooperative group of customers pooling together their flexible loads and participating in the energy market via an aggregator. The aggregator computes an optimal daily profile taking into account the gross daily demand from the consumer group and the energy market's expected conditions and opportunities, and assigns prices and rate zones accordingly. The consumer group reacts by deferring and curtailing the flexible loads in order to minimize their daily cost consisting of the energy bill, the utility cost, and the curtailment reward. We model the consumers' response and interaction with the aggregator as a two-stage sequential optimization problem. We perform sensitivity analysis over the most significant parameter combinations through two scenarios and five cases. We compare the performance of our scheme to that of time-of-use (TOU) and real time pricing (RTP). Using a 40-home aggregate energy profile, we show that consumers can match a test supply profile with 5% maximum error and 2% average error while TOU and RTP can lead, respectively, to 163% and 97% maximum error, and 37% and 25% average error.