Aiming at solving the problem of excessive material input and equipment power consumption in desulfurization system of coal-fired power units

the operation cost evaluation is introduced into the operation optimization of the desulfurization system. Historical data of the desulfurization system of a 660 MW coal-fired power unit are collected to establish the operating cost model and the outlet pollutant mass concentration prediction model. By taking the variable manipulation amount of the desulfurization system as a variable

taking the actual adjustment range of variable manipulation amount as the constraints

and using the hybrid non-dominated sorting genetic algorithm II(NSGA II) combing with multi-objective particle swarm optimization(MOPSO) algorithm

a hybrid optimization model is established

and a set value of the variable manipulation amount is obtained. The optimization results are compared with that of the NSGA-II and MOPSO algorithm. The simulation results show that

by optimizing the variable manipulation amount

the new operation strategy can effectively reduce the cost per kW·h by 9.38%

6.01%

3.69% and 3.99% under four major working conditions

respectively

on the premise of the pollutants mass concentration at outlet meets the standard. The research has certain practical application value.