Optimal load distribution of thermal power units based on quantum genetic intelligence algorithm

Abstract:
Reasonable distribution of unit load is an important way for thermal power plants to maximize benefits. Therefore, optimal distribution of unit load is an important research field for the economic and safe operation of thermal power plants. The purpose of this paper is to study the optimal load distribution of thermal power units based on quantum genetic intelligence algorithm. The mathematical load optimization distribution model adopted in this paper is determined, carbon consumption is determined as the optimization index, and the objective function of the mathematical model and the constraints it contains are determined. The theoretical basis of quantum genetic algorithm is analyzed, the structure of the algorithm, the advantages and disadvantages of the algorithm are proposed, an improved quantum genetic algorithm is proposed, and the performance advantage of the improved quantum genetic algorithm is verified. The design algorithms of coding, constraint detection, iteration and other details are studied. Finally, the optimization efficiency is compared and analyzed through the simulation optimization example. The good optimization results verify the feasibility and effectiveness of the improved quantum genetic algorithm in solving the optimal load distribution problem of thermal power units.