Variable Parameter Control And Working Point Optimization Of The Compression Refrigeration

Nowadays,state of energy is becoming increasing serious in our country with building energy efficiency even being in the backward level.There are many problems to be solved.Starting with air-conditioning system which occupies the biggest part in building energy consumption,this article mainly studied the control method and operating point optimization problems of compressive refrigeration unit.Nonlinear PID control method basing on particle swarm optimization was applied to solve the system control problem.A hybrid particle swarm optimization algorithm was used to solve problems about operating point optimization.After primary acknowledge of compressive refrigeration particle swarm optimization was also introduced in the paper.Particle swarm optimization is a bionic optimization algorithm.This paper summarized the advantages,disadvantages and improvement of the algorithm.Basing on in-depth knowledge of the algorithm principle,improvement strategies and methods,two kinds of hybrid particle swarm optimization were designed for parameters optimization of air-conditioning nonlinear controller and compressive refrigeration operating point optimization respectively.The hybrid particle swarm optimization algorithm I introduced concept of state feedback,and used success rate as feedback parameters which was based on to adjust the inertia coefficient.The acceleration coefficient was adjusted according to the time meanwhile.The hybrid particle swarm optimization algorithm II used another completely different strategy which introduced concept of population management and divided the population into high fitness population and low fitness population.By adjusting population quantity and introducing a series of rules for the new particle,optimizing capacity of particle was improved under complex cases.Simulation experiment results using test functions show that both algorithm precision and convergence speed of two kinds of hybrid particle swam optimization algorithm mentioned in this paper are improved by a certain degree compared with other particle swarm optimization.Nonlinear PID controller basing on particle swarm optimization was designed aiming at compressive air-condition system.Through analyzing influence of every parameter in traditional PID controller,each parameter was nonlinear adjusted pointedly.The controller consists of differential replacement unit,error adjustment unit,error signal power calculator,linear error signal calculator,linear error signal ratio regular,error signal power ratio regular,integral signal conditioner,PID gains calculator,saturator,etc.Simulation experiment results show that controller designed in this paper improved control effect in compressive air-condition system,and solved the problems of long adjustment time and big overshoot existed in traditional PID controller.Both long-term changes and short-time changes exist in air-condition system load.And furthermore,when air-condition was designed about ten to twenty percent load margin was reserved.So,air-condition system runs under non-rated conditions for long time.Energy-saving optimization made aiming at air-condition operating point will surely make great contribution to reduce building energy.Hybrid particle swarm optimization was used for operating point optimization in this paper in order to achieve energy saving goal in this paper.Experiment results show that more efficient operating point can be gained with this method,meanwhile effect will be more outstanding when system runs under non-rated conditions.And the lower the air-condition load is,the better the energy saving effect is.