Modified Genetic Algorithm for the Profit-Based Unit Commitment Problem in Competitive Electricity Market

Abstract

This article proposes a solution to the Profit-Based Unit Commitment (PBUC) problem to maximize the profit of a power generation company that owns thermal units and compressed air energy storage (CAES) systems, considering the Day-Ahead market. The proposed methodology is more realistic as it considers a mixed-integer nonlinear formulation of the PBUC. The problem is solved through two stages, with Stage 1 dedicated to obtaining the operational state of the generating units (On or Off) and the operation mode of the storage system (energy exchange: charging, discharging, idle). Stage 2 determines the dispatch of power from the thermoelectric units and the energy exchange in the storage system. The analysis of the system consisting of 20 thermoelectric units and three storage systems shows the efficiency of the proposed method in making decisions for the power generation company and is therefore promising for real-world applications.

Keywords

• profit-based unit commitment
• compressed air energy storage
• day-ahead energy market
• hybrid optimization
• genetic algorithm