Research on temperature control optimization method of ice storage refrigeration system empowered by Internet of Things in digital transformation environment

Abstract

Aiming at the problem of high energy consumption and low level of intelligent operation and maintenance of ice storage cold air conditioning system, this paper analyzes the intelligent operation and maintenance design of ice storage cold air conditioning system empowered by Internet of Things (IoT) technology. In order to optimize the control of temperature during the operation of ice storage cold air conditioning system and achieve the goal of minimizing the operation energy consumption, this paper adjusts the inertia weight of particle swarm optimization algorithm, introduces the artificial immunity idea to form the immune particle swarm algorithm, and strengthens the algorithm's ability of local optimization. Through the AI-PSO algorithm to optimize the ice storage air conditioning system PID controller parameters to solve the objective function. The optimization results of the ice storage air conditioning system show that under different ratios of rated demand loads, the optimization results of the AI-PSO algorithm have smaller fluctuation values and the system consumes less energy. In the same cooling cycle, the AI-PSO algorithm is 27.29% and 8.08% smaller than the mainframe-first and ice-melting-first control methods, respectively, with significant peak-shaving and valley-filling effects, and better energy-saving effects and control quality. Compared with the host-first and ice-melting-first methods, the method has better temperature control effect and economic benefits.