Robust optimization based price-taker retailer bidding strategy under pool market price uncertainty

• Proposing electricity procurement strategy for retailers using robust optimization.
• Pool price uncertainty is modeled using robust optimization technique.
• The problem is recast as a robust mixed-integer linear programming problem (RMILP).

In the restructured electricity markets, retailers purchase the required demand of its consumers from different energy resources such as self-generating facilities, bilateral contracts and pool market. In this process, the pool market price uncertainty modeling is important for obtaining the maximum profit. Therefore, in this paper, a robust optimization approach is proposed to obtain the optimal bidding strategy of retailer, which should be submitted to pool market. By the proposed method, a collection of robust mixed-integer linear programming problem (RMILP) is solved to build optimal bidding strategy for retailer. For pool market price uncertainty modeling, upper and lower limits of pool prices are considered instead of the forecasted prices. The range of pool prices are sequentially partitioned into a successive of nested subintervals, which permit formulating a collection of RMILP problems. The results of these problems give sufficient data to obtain optimal bidding strategy for submit to pool market by retailer. A detailed analysis is utilized to delineate the proposed method.