Power generation loading optimization using a multi-objective constraint-handling method via PSO algorithm

Power generation loading optimization problem will be of practical importance in the coming carbon constrained power industry. A major objective for the coal-fired power generation loading optimization is to minimize fuel consumption to achieve output demand and to maintain NOx emissions within the environmental license limit. This paper presents a multi-objective constraint-handling method incorporating the particle swarm optimization (PSO) algorithm for the power generation loading optimization application. The proposed approach adopts the concept of Pareto dominance from multi-objective optimization, and uses several selection rules to determine particlespsila behaviors to guide the search direction. The simulation results of the power generation loading optimization based on a coal-fired power plant demonstrates the capability, effectiveness and efficiency of using a multi-objective constraint-handling method with PSO algorithm in solving significant industrial problems.