Dynamic Pricing for Demand Response Considering Market Price Uncertainty

Mohammad Ali Fotouhi Ghazvini, João Soares, Hugo Morais, Rui Castro and Zita Vale
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Mohammad Ali Fotouhi Ghazvini: GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development-Polytechnic of Porto (IPP), R. Dr. António Bernardino de Almeida 431, 4200-072 Porto, Portugal
João Soares: GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development-Polytechnic of Porto (IPP), R. Dr. António Bernardino de Almeida 431, 4200-072 Porto, Portugal
Hugo Morais: Automation and Control Group, Department of Electrical Engineering, Technical University of Denmark (DTU), Elektrovej, Building 326, DK-2800 Kgs. Lyngby, Denmark
Rui Castro: Instituto de Engenharia de Sistemas e Computadores—Investigação e Desenvolvimento/Instituto Superior Técnico (INESC-ID/IST), University of Lisbon, 1049-001 Lisbon, Portugal
Zita Vale: GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development-Polytechnic of Porto (IPP), R. Dr. António Bernardino de Almeida 431, 4200-072 Porto, Portugal

Energies, 2017, vol. 10, issue 9, 1-20

Abstract: Retail energy providers (REPs) can employ different strategies such as offering demand response (DR) programs, participating in bilateral contracts, and employing self-generation distributed generation (DG) units to avoid financial losses in the volatile electricity markets. In this paper, the problem of setting dynamic retail sales price by a REP is addressed with a robust optimization technique. In the proposed model, the REP offers price-based DR programs while it faces uncertainties in the wholesale market price. The main contribution of this paper is using a robust optimization approach for setting the short-term dynamic retail rates for an asset-light REP. With this approach, the REP can decide how to participate in forward contracts and call options. They can also determine the optimal operation of the self-generation DG units. Several case studies have been carried out for a REP with 10,679 residential consumers. The deterministic approach and its robust counterpart are used to solve the problem. The results show that, with a slight decrease in the expected payoff, the REP can effectively protect itself against price variations. Offering time-variable retail rates also can increase the expected profit of the REPs.

Keywords: call option; demand response; forward contract; retail electricity provider; robust optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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