| With the rapid development of economy,the problem of environmental pollution is increasingly serious.How to achieve energy conservation and emission reduction to improve environmental pollution has become a widespread concern.As one of the main causes of environmental pollution,coal-fired boiler system combustion optimization can not only save the cost of enterprises,but also reduce environmental pollution.To optimize the boiler combustion system,it is necessary to establish an effective combustion prediction model for the boiler and study how to adjust the combustion factors of the boiler so that the system can achieve the goal of high efficiency and energy saving.In order to solve this problem,the combustion system of pulverized coal boiler is studied as follows:Firstly,aiming at the disadvantages of Salp Swarm Algorithm(SSA)which randomly generates the initial population position,resulting in,an Adaptive Salp Swarm Algorithm(ASSA)is proposed to solve unstable optimization results,slow convergence speed and easy to fall into local optimization of SSA.In order to verify the performance of the algorithm,the ASSA was compared with the Butterfly Algorithm(BOA),Whale Algorithm(WOA),Particle Swarm Algorithm(PSO),and Salp Swarm Algorithm(SSA)on 10 benchmark test functions.The results show that the ASSA algorithm has faster convergence speed and the optimization results are better.In addition,an ASSA-FLN network is proposed to solve the shortcomings of random initialization weights and thresholds of FLN networks.Furthermore,based on the historical data of 330MW and 300MW boilers in a power plant,a NO_X emission concentration and thermal efficiency prediction model and a comprehensive prediction model were established,respectively.In order to verify the generalization ability of the model,it is compared with the other four prediction models.The results show that the ASSA-FLN model has better prediction accuracy and generalization ability.Finally,the single objective optimization model and the multi-objective optimization model are established respectively,and different optimization objective functions are set up.The ASSA algorithm is employed to optimize the adjustable parameters of the boiler under different working conditions,provided the pulverized coal boilers could combust at the optimum parameters,and achieve a satisfactory result of NO_X emission concentration and thermal efficiency,providing a direction for the optimization of power plant boilers. |
