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.
Highlights
Small electricity consumers, apart from the regulations that ban them from participation in the pool market, are usually unwilling to participate in volatile pool markets
This risk-hedging tool guarantees that a minimum level of critical profit and bilateral contract fulfillment for virtual power player (VPP) will be obtained, based on the assumption that the realized market prices are deviated in a trust region [13]
Robust optimization is used to consider the impact of market price uncertainty on the short-term decisions of Retail electricity providers (REPs) in the retail market
Summary
Apart from the regulations that ban them from participation in the pool market, are usually unwilling to participate in volatile pool markets. They are unprepared for forecasting the market price and even predicting their own load forecast. In addition to the forward contracts, they procure part of the demand of their customers through the pool market [1] They have an intermediary role in electricity markets [2]. The main challenge of REPs is buying power on the wholesale market at volatile prices and selling it to the clients at the retail level at fixed agreed rates [2]. Robust optimization models are proposed for decision-making frameworks that are affected by uncertainty, where the decision-maker lacks the full information
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