Modified Genetic Algorithm for the Profit-Based Unit Commitment Problem

This chapter presents modifications to the Genetic Algorithm (GA) to solve the Profit-Based Unit Commitment problem, considering the sale of energy in the day-ahead market, and reserve in the ancillary market. The proposed modifications to the GA include the use of special operators: Swap Window Operator, Window Mutation Operator, and Swap Window Hill Climb Operator. Additionally, a heuristic is utilized to repair solutions that violate the minimum up/down time constraints. The performance of these modifications is compared with the metaheuristics Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), Sine Cosine Optimization (SCA), and Harris Hawks Optimization (HHO). To demonstrate the effectiveness of the proposed method, both a small-scale system with 10 units and a large-scale system with 100 units were considered.