Environmental/Economic Dispatch Using a New Hybridizing Algorithm Integrated with an Effective Constraint Handling Technique

This work tackles a relatively new issue in power system operation, known as the Environmental/Economic Dispatch problem. For this purpose, combination of two powerful heuristic algorithms, namely, Exchange Market Algorithm (EMA) and Adaptive Inertia Weight Particle Swarm Optimization (AIWPSO), was employed. Additionally, Multiple Constraint Ranking (MCR) technique used to address constraints such prohibited operating zones ramp rate limits. Furthermore, mutation operator improve performance global search mechanism. The main purpose combining these algorithms utilizing EMA’s high explore optimum local exploitation ability AIWPSO. algorithm evaluated on six standard benchmark functions scrutinized several different test systems, including 6–40 units. By using proposed method, minimum values reduction annual costs, with equal or less emissions, compared other methods, were USD 17,520, 8760 10,801,080, respectively, for 6-unit, 10-unit, 40-unit systems (assuming same load profile throughout year). Similarly, 14-unit 1750, 2150, 2650 (MW) demands, 229,879, 148,438, 4483, respectively.