Research On Optimization Model And Algorithm Of Central Heating System

With the continuous increase of heating area in our country and the continuous improvement of people's living standard,higher requirements are put forward for heating quality.How to improve the scientificity and flexibility of heat distribution and realize on-demand heating is an important topic in the heating industry.Based on the actual investigation of the heating system of a thermal power plant in Shenyang,this study finds that the supply and demand of the system are unbalanced,the satisfaction of heat users is low,and complaints are frequent.The heat exchange station is an important part of the central heating system.The primary network is connected to the core equipment of the secondary network and is mainly responsible for the heat distribution of the secondary network.The operation state and control method directly affect the heating quality of the whole heating system.Combining the advantages of chemical reaction and polar bear algorithm,a new hybrid algorithmhybrid chemical method is proposed,which is the polar bear algorithm(HCRPBOA).It is applied to the flow distribution optimization of heat exchange station.The flow control valve of the heat exchange station is used to regulate the water quantity entering the heat exchange station to realize the on-demand distribution of heat in the secondary network.Starting from the user demand and the economic benefits of thermoelectric enterprises,the fuzzy function of user satisfaction is introduced to evaluate the service quality of heating system,and two objective functions of total satisfaction of heat users and system heating cost are established for multi-objective optimization.The objective function is quantized to obtain a quantization function of the dissatisfaction degree of heat users and a quantization function of heating cost.Multi-objective optimization is used to improve the utilization rate of heat in the system,ensure the quality of heat supply and realize on-demand heat supply.This study theoretically proves that HCRPBOA is superior to NGSA-II algorithm in on-demand heat supply optimization,and uses super-volume evaluation index to evaluate the quality of the optimization solution set.It verifies that the hybrid chemical method should polar bear algorithm is obviously superior to NSGA-II algorithm in handling on-demand heat supply problems.The simulation verifies that the distribution,diversity and convergence of HCRPBOA solution are obviously superior to NSGA-II algorithm.We have a more systematic understanding of the application of multiobjective optimization in the field of heating,and also provide new ideas for thermoelectric enterprises to use intelligent optimization algorithms to reduce energy consumption and improve customer satisfaction.