چکیده
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In this paper, an electricity retailer seeks to determine selling price for end-user consumers under fixed pricing
(FP), time-of-use pricing (TOU) and real-time pricing (RTP). Furthermore, in order to provide power exchange
between the retailer and the power market, bidding and offering curves should be prepared to bid and offer to
the day-ahead market. Therefore, this paper proposes a robust optimization approach (ROA) to obtain optimal
bidding and offering strategies for the retailer. To achieve this, ROA is used for uncertainty modeling of power
market prices in which the minimum and maximum limits of prices are considered for uncertainty modeling.
Lower and upper bounds of price is consecutively subdivided into sequentially nested subintervals which allows
formulating robust mixed-integer linear programming (RMIP) problem. The proposed RMIP model helps retailer
to select a robust decision in the presence of market price uncertainty. Furthermore, the bidding and offering
curves of the retailer are obtained from sufficient data through solving these problems. Meanwhile, the uncertainty of customers demand and variable climate condition are modeled based on stochastic programming. To
validate the proposed robust optimization model, three case studies are evaluated and the results are compared
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