A bilevel model for electricity retailers' participation in a demand response market environment

• Published in: Energy economics Vol. 36; pp. 182 - 197
• Main Authors: Zugno, Marco, Morales, Juan Miguel, Pinson, Pierre, Madsen, Henrik
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.03.2013; Elsevier
• Subjects: Accounting; Applied sciences; Bilevel programming; computer software; Consumers; Cost; Demand response; Economic data; Electric energy; Electric power; electricity; Electricity markets; Energy; energy costs; Energy economics; Energy market; Energy policy; Energy retail; Environment; Exact sciences and technology; Game theory; General, economic and professional studies; Markets; Methodology. Modelling; Natural energy; Power demand; Prices; Pricing; Profits; Purchasing; Real-time pricing; Regulation; retail marketing; Risk; Stochastic processes; Stochastic programming; wholesale marketing; Q4; Real-time pricing; Electricity markets; Bilevel programming; Demand response; Energy retail; C61; C72; Stochastic programming
• ISSN: 0140-9883; 1873-6181
• DOI: 10.1016/j.eneco.2012.12.010

Demand response programmes are seen as one of the contributing solutions to the challenges posed to power systems by the large-scale integration of renewable power sources, mostly due to their intermittent and stochastic nature. Among demand response programmes, real-time pricing schemes for small consumers are believed to have significant potential for peak-shaving and load-shifting, thus relieving the power system while reducing costs and risk for energy retailers. This paper proposes a game theoretical model accounting for the Stackelberg relationship between retailers (leaders) and consumers (followers) in a dynamic price environment. Both players in the game solve an economic optimisation problem subject to stochasticity in prices, weather-related variables and must-serve load. The model allows the determination of the dynamic price-signal delivering maximum retailer profit, and the optimal load pattern for consumers under this pricing. The bilevel programme is reformulated as a single-level MILP, which can be solved using commercial off-the-shelf optimisation software. In an illustrative example, we simulate and compare the dynamic pricing scheme with fixed and time-of-use pricing. We find that the dynamic pricing scheme is the most effective in achieving load-shifting, thus reducing retailer costs for energy procurement and regulation in the wholesale market. Additionally, the redistribution of the saved costs between retailers and consumers is investigated, showing that real-time pricing is less convenient than fixed and time-of-use price for consumers. This implies that careful design of the retail market is needed. Finally, we carry out a sensitivity analysis to analyse the effect of different levels of consumer flexibility. ► We model the game between electricity retailers and consumers under dynamic pricing. ► The retailer cuts procurement costs by shifting demand in time via price-incentive. ► Imbalance costs for the retailer taper off when using real-time pricing. ► The additional welfare can be distributed unfairly between retailers and consumers. ► Real-time pricing encourages consumers to increase their flexibility.