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Article

Dynamic Pricing for Demand Response Considering Market Price Uncertainty

1
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
2
Automation and Control Group, Department of Electrical Engineering, Technical University of Denmark (DTU), Elektrovej, Building 326, DK-2800 Kgs. Lyngby, Denmark
3
Instituto de Engenharia de Sistemas e Computadores—Investigação e Desenvolvimento/Instituto Superior Técnico (INESC-ID/IST), University of Lisbon, 1049-001 Lisbon, Portugal
*
Author to whom correspondence should be addressed.
Energies 2017, 10(9), 1245; https://doi.org/10.3390/en10091245
Received: 22 May 2017 / Revised: 14 July 2017 / Accepted: 8 August 2017 / Published: 23 August 2017
(This article belongs to the Section F: Electrical Engineering)
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. View Full-Text
Keywords: call option; demand response; forward contract; retail electricity provider; robust optimization call option; demand response; forward contract; retail electricity provider; robust optimization
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MDPI and ACS Style

Fotouhi Ghazvini, M.A.; Soares, J.; Morais, H.; Castro, R.; Vale, Z. Dynamic Pricing for Demand Response Considering Market Price Uncertainty. Energies 2017, 10, 1245. https://doi.org/10.3390/en10091245

AMA Style

Fotouhi Ghazvini MA, Soares J, Morais H, Castro R, Vale Z. Dynamic Pricing for Demand Response Considering Market Price Uncertainty. Energies. 2017; 10(9):1245. https://doi.org/10.3390/en10091245

Chicago/Turabian Style

Fotouhi Ghazvini, Mohammad Ali, João Soares, Hugo Morais, Rui Castro, and Zita Vale. 2017. "Dynamic Pricing for Demand Response Considering Market Price Uncertainty" Energies 10, no. 9: 1245. https://doi.org/10.3390/en10091245

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