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 NO, 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 particles' 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.