Study On Energy-Saving Optimization Of Central Air Conditioning Chilled Water System In An Airport Terminal Building Based On Swarm Intelligence

Central air conditioning is an important energy-consuming facility in airport terminals,and chilled water system energy consumption accounts for more than 70% of the central air conditioning system.By optimizing the operation parameters of chillers,pumps and other equipment in the chilled water system,energy consumption can be effectively reduced,carbon emissions can be reduced,and the operation efficiency and economy of the air conditioning system can be improved.In this paper,we take the central air conditioning chilled water system of an airport terminal building in Northwest China as the research object,establish the chilled water system equipment operation optimization model,and obtain the optimal operation control strategy by using the swarm intelligent optimization algorithm to solve,so as to guide the energy-saving and low-carbon operation of the air conditioning system and meet the comfort demand of the airport cooling load.The main research contents of this paper are as follows:(1)Research on physical models of electromechanical equipment and equipment standard information sets for central air-conditioning chilled water systems.The intelligent control and management of the building and its internal systems are realized through a flat and centerless distributed computing network.The physical models of chillers and pumps are established respectively with the objective of minimizing energy consumption of the central air-conditioning chilled water system,and the corresponding constraints are introduced considering the physical characteristics of the equipment.The standard information set of chiller units and pumps is established to provide data support for the subsequent development of effective strategies to improve the performance and energy efficiency of central air-conditioning chilled water systems.(2)Study of the optimal load distribution problem of parallel chillers in central airconditioning chilled water systems.Based on the physical model of the chiller plant established in Chapter 2 and the corresponding constraints are introduced according to the actual situation.The goal of optimization is to minimize the energy consumption of the parallel chillers under the established constraints.The problem is then solved using an improved distributed whale optimization algorithm,and the feasibility of the algorithm is verified through experiments.The experimental results show that the algorithm converges faster than the standard whale optimization algorithm,the algorithm is more stable,and the maximum relative error does not exceed 0.0035%.(3)Research on the parallel pump flow distribution problem of central air-conditioning chilled water system.Based on the physical model of the pumps established in Chapter 2 and the corresponding constraints are introduced according to the actual situation.The goal of optimization is to minimize the energy consumption of the parallel pumps under the established constraints,after which the problem is solved using a breadth-first stochastic search algorithm.First,to be able to process the information of the entire CPN network,each node constructs a spanning tree for information transfer using the breadth-first random search algorithm.Secondly,the intelligent nodes find the optimal solution by continuously sampling the speed ratio sample points in the feasible domain and collaborating with their neighbors.Finally,the proof of convergence of the algorithm is given through experiments,and the experimental results show that the energy consumption is saved about 29% compared with the traditional centralized control algorithm,which can accurately meet the end-load demand and has good energy-saving potential.(4)Research on energy-saving control strategy of chilled water system based on group intelligence.Relying on the building group intelligence platform,the chilled water system of an airport terminal in the northwest region was collected as the basis for energy-saving control research.Two kinds of equipment working conditions,high and low,were selected for simulation experiments to verify.The experimental results show that the total energy saving rate of the equipment in the high working condition is about 14.59%,and the energy saving rate in the low working condition can be improved by about 11.62%,and the proposed improved distributed optimization algorithm has better energy saving effect compared with the traditional distributed optimization algorithm.The paper addresses the parallel chiller load distribution problem and parallel pump flow distribution problem in chilled water system.Based on the group intelligence architecture,the electromechanical equipment models of chillers and pumps are established,and the improved distributed whale optimization algorithm and the breadth-first stochastic search algorithm are proposed to optimize the energy consumption of chillers and pumps,respectively,so as to reduce the energy consumption of the central air conditioning chilled water system,and the thesis research provides a theoretical basis for the formulation of the optimal operation strategy of the airport central air conditioning system.