Revisiting the use of Robust Optimization for optimal energy offering under price uncertainty

TL;DR

This paper introduces a new Robust Optimization approach for energy offering under price uncertainty, addressing limitations of previous methods by improving computational efficiency and profit outcomes for generating companies.

Contribution

The paper presents a novel single-step Robust Optimization method with intermediate protection levels, enhancing practicality and profitability over existing approaches.

Findings

Significant profit improvement demonstrated on industrial case studies

Method reduces computational complexity compared to previous approaches

Offers at zero price effectively mitigate non-acceptance risk

Abstract

We propose a new Robust Optimization method for the energy offering problem of a price-taker generating company that wants to build offering curves for its generation units, in order to maximize its profit while taking into account the uncertainty of market price. Our investigations have been motivated by a critique to another Robust Optimization method proposed in [Baringo and Conejo, 2011], which entails the solution of a sequence of robust optimization problems imposing full protection and defined over a sequence of nested subintervals of market prices: this method presents a number of issues that may severely limit its application and computational efficiency in practice and that may expose a company to the risk of presenting offering curves resulting into suboptimal or even infeasible accepted offers. To tackle all such issues, our method provides for solving one single robust counterpart, considering an intermediate level of protection between null and full protection, and to make energy offers at zero price, practically eliminating the risk of non-acceptance. Computational results on instances provided by our industrial partners show that our new method is able to grant a great improvement in profit.