Modeling And Predictive Control Of Double Effect Libr Absorption Chiller

With the rapid development of China’s economy,China’s energy industry is facing further transformation and upgrading.Distributed energy system provides a new idea for the transformation and upgrading of China’s energy industry.The double effect Li Br Absorption Chiller Driven by micro gas turbine is the most widely used in distributed energy system.Among them,Li Br absorption chiller has been paid more and more attention because of its advantages of low-grade heat utilization,safe and non-toxic working medium,low noise and stable performance under load change.However,due to the characteristics of Li Br absorption refrigeration system,such as non-linear,large inertia and easy to be disturbed by the outside world,the conventional PID control method can not meet the control requirements.Therefore,the mechanism modeling and dynamic simulation of double effect Li Br absorption chiller are carried out in this paper,and the generalized predictive control based on improved particle swarm optimization algorithm is applied to the control system of Li Br absorption refrigerator,and the control effect is good.Due to the high probability of standard PSO falling into local optimum,an adaptive migration strategy is proposed according to the migration strategy of bacterial foraging algorithm and applied to particle swarm optimization algorithm.The test function is used to test the ability of the improved algorithm to jump out of the local optimum,the convergence speed and the convergence accuracy.The test results show that the improved algorithm is better than the standard particle swarm optimization algorithm.And the improved particle swarm optimization algorithm is applied to the identification of thermal parameters,the identification results and the actual data fitting degree is high,the accuracy can meet the actual needs.The working process of double effect Li Br refrigerator is analyzed,and the mathematical models of each part are established.Combined with the thermal properties of water and Li Br solution and the parameters of the refrigerator,the dynamic modeling and Simulation of the double effect Li Br refrigerator are carried out,and the step disturbance test is carried out to analyze its dynamic characteristics.The cooling and heating load regulation strategy of Li Br refrigeration system is designed,and the control object model is established.The parameters of the control object model are identified by the improved particle swarm optimization algorithm,and the accuracy of the model is verified by comparing with the actual simulation results.In order to solve the problem that it is difficult to solve the optimal control quantity due to the constraints of the control object in the actual control process,the improved particle swarm optimization algorithm is used to optimize the performance index function.The improved generalized predictive control is applied to the load control system of Li Br absorption chiller,and the control effect is compared with the traditional PID control algorithm,which verifies that the improved predictive controller has better control effect.