Application of a Genetic Algorithm in the Optimization-based Unit Commitment of the Power Plant

As the electric industry restructures, competitive mechanism begins coming into electricity market. The method of optimizing the unit commitment (UC) in the thermal power plant is an important task. This paper discusses an advanced application of genetic algorithm, the method can create initial generation that is a feasible solution to UC. Feasibility checking builds a relation between infeasible solution and feasible solution space, which reduces lots of invalid processes in genetic searching. The simulation shows that the method has good convergence, adaptability, and rapid calculation capacity, can achieve optimal solution close to whole optimization.