Generator maintenance scheduling with hybrid evolutionary algorithm

This paper proposes a hybrid evolutionary algorithm to solve the maintenance-scheduling problem for thermal generating units. The proposed approach uses a hybrid Fuzzy-Genetic Algorithm that implements Fuzzy Knowledge Based System to emulate the power plant personnel's experience, and uncertainties in the constraints, while a Genetic Algorithm optimizes the total generating cost and the maintenance cost as the objective functions. Two other effective and practical methods based on Evolution Strategy and Particle Swarm Optimization were also applied for the same problem. Simulations were carried out on a practical thermal power plant consisting of 19 generating units, over a six-month planning horizon.