Multi-objective Optimization for Thermal Power Plant Operation Based on Improved Working Condition

A multi-objective optimization based on improved K-means algorithm for thermal power plant operation is proposed in this paper. First, an improved K-means algorithm that aims at updating the method of selecting the clustering number and initial clustering center is applied to divide unit load and coal quality condition. Furthermore, a multi-objective optimization method is developed to realize the balance between the economic indicator and the environmental indicator, thus the corresponding optimal operation parameters of the two performance indicators for each condition can be obtained, which can effectively guide the power station operation. Lastly, taking the historical operation data of a 300MW unit as the experimental object, the simulation results show that the proposed multi-objective optimization based on improved K-means algorithm in this paper is effective and reasonable for the power station operation.