Research On Energy-saving Control Strategy Of Air-conditioning Cooling Water System In Terminal Building Based On Swarm Intelligent Building Automation System

Terminal building is a large-scale public building with high energy consumption,and the operating energy consumption of its central air-conditioning system accounts for about 50% to 60% of the total energy consumption.Furthermore,the operating parameter control and equipment control of the air-conditioning cooling water system plays a decisive role in the overall energy-saving effect of the central air-conditioning system.Hence,research on energy-saving control of central air-conditioning cooling water systems is critical.Taking the refrigeration station of a terminal building in the northwest region as the research object,this study demonstrated an energy-saving control strategy of cooling water system based on swarm intelligent building automation system to solve real-world engineering problems such as complex network configuration and difficult system transformation.The main contents of this paper are as follows:(1)Build a swarm intelligent simulation experiment platform for the air-conditioning cooling water system in the terminal building and established an energy-saving optimization model for the air-conditioning cooling water system.Firstly,establish the standard information set of chillers,cooling towers,cooling pumps,and the network topology of its controller nodes under the swarm intelligent architecture;secondly,the energy consumption model of various equipment in the cooling water system was established.Finally,taking the energy conservation between the equipment and the physical characteristics of the equipment as the constraints,the energy-saving optimization model was established with the goal of the minimum energy consumption of the air-conditioning cooling water system.(2)Research on energy-saving optimization of operating parameters of air-conditioning cooling water systems.Aiming at the problem of energy-saving optimization of operation parameters between equipment modules,firstly,we selected the inlet temperature and flow rate of cooling water as optimization parameters;secondly,the operator splitting method was used to decompose the energy-saving optimization problem of the cooling water system into the local optimization problem;finally,a distributed alternating direction multiplier method was proposed to perform distributed optimization of the operating parameters of the local optimization problem.The proposed algorithm was compared with the actual operation method and the penalty function method using a typical example.The results showed that the energy-saving rate could be increased by about 12.2% and 3.56%,respectively.(3)Research on energy-saving control of equipment in air conditioning cooling water systems.Aiming at the distribution optimization problem in the equipment module of the cooling water system,we established the optimal operation models of the cooling water pump and cooling tower fan,respectively.Furthermore,an improved alternating direction multiplier method with Gaussian return using Gaussian penalty function,that is,ADMM-GPF-GBS double-layer distributed computing framework,was proposed to optimize the feed control of parallel cooling pumps and parallel cooling towers,respectively.Based on the typical examples of four working conditions of parallel pumps,the proposed algorithm can improve the convergence speed by92.4% compared with other distributed algorithms,and the maximum energy saving rate can reach 22.5% compared with the centralized algorithm.(4)Research the energy-saving control strategy of air conditioning cooling water systems based on swarm intelligent building automation system.The distributed energy-saving control of air-conditioning cooling water system was carried out based on the experimental platform of the swarm intelligent building automation system,combined with the proposed operation parameter optimization algorithm and equipment energy-saving control algorithm.The simulation results showed that in a typical day,compared with the centralized control method and the general distributed control method,the energy-saving rate of the proposed optimization strategy can be increased by 8.11% and 4.02%,respectively,under high operating conditions.Under low operating conditions,the energy-saving rate can be increased by 11.69% and5.33%,respectively.It is proved that the proposed strategy has better convergence than the general distributed algorithm;compared with the centralized control mode,it can obtain a more reasonable energy consumption distribution ratio of various equipment and can achieve the best energy-saving effect quickly and effectively.In conclusion,the energy-saving control strategy of the terminal air-conditioning cooling water system based on swarm intelligent building automation system researched in the thesis can realize the efficient and energy-saving optimized operation of the cooling water system,which will provide a reference value for the energy-saving management of the terminal central air-conditioning cooling water system in the future.