A Sequential Evolutionary Programming Approach to Profit-Based Unit Commitment

This paper presents the application of a Sequential Evolutionary Programming (SEP) approach for solving the Profit-Based Unit Commitment problem (PBUC). The PBUC problem is a variant of the traditional Unit Commitment (UC) that has arisen as a result of the deregulation of power system markets. Specifically, PBUC is used for Generation Companies (Genco's) in order to maximize their own profits without the responsibility of satisfying necessary the forecasted demand. The PBUC is a highly dimensional mixed-integer optimization problem, which might be very difficult to solve. The SEP approach introduced in this paper offers a good balance between accuracy and computational effort while solving the PBUC problem. For its implementation, the PBUC problem is decomposed into three sub-problems that are solved in a sequential way. The proposed method is suitable for a wide variety of power system market rules. In this paper, two case studies are considered, each with different sets of power system market rules. The obtained results were compared with those available in the literature, and they showed the effectiveness of the proposed method for reaching optimal PBUC solutions.