Price-based unit commitment in power systems with renewable energy resources considering security and reserve constraints in competitive electricity markets using a differential evolution algorithm

In modern competitive electricity markets, Independent System Operators (ISOs) have difficulty managing the scheduling of generation units in accordance with system security and minimizing the overall system’s operational costs with increasing penetration of renewable energy. This paper develops a differential evolution (DE) based optimization framework for day-ahead price-based unit commitment, which simultaneously schedules energy generation and 24-hour spinning reserves whilst respecting security, technology and reserve constraints. The proposed modeling framework explicitly addresses the uncertainty in wind power generation, generator ramp rates and spinning reserves requirements. Case studies apply the proposed methodology on a modified IEEE 30-bus system, and demonstrates that specifying a wind farm in the study system decreases the total cost of the overall system by 17% and the spinning reserve requirements by 34%. The DE based unit commitment scheduling framework saves an overall system operational cost of 3.4–8.5% compared to the traditional optimal power flow (OPF) method while maintaining feasibility to all the operational constraints. Additionally, by comparing the results for the DE unit commitment scheduling framework to metaheuristic algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), the results exhibit a faster convergence and a higher quality solution with lower computational times. The case studies present a reliable and inexpensive method to allow for the effective implementation of renewable energy resources in the operation of electricity systems in the competitive electricity market while maintaining reliability in the system and providing adequate reserve capacity.