Research on Multi-objective Optimization Method of Central Air Conditioning Air Treatment System Based on NSGA-II

In this paper, the composition, working principle and characteristics of the central air conditioning air treatment system are comprehensively analyzed, the energy consumption equipment of the air treatment system is established, the energy consumption model of the chilled water pump and fan is established, and the sum of the energy consumption models of the pump and fan is used as the air The total energy consumption model of the processing system is given, and the constraint conditions of the objective function are given. The characteristics of the evaluation index PMV describing the application of the human body’s cold and hot feeling and the PPD index characterizing the degree of dissatisfaction in the thermal environment are analyzed. The room comfort model with the smallest PPD value is established. Finally, the minimum total energy consumption of the air treatment system and the smallest PPD value are established Established a multi-objective optimization model. The NSGA-II algorithm is used to optimize the established multi-objective function, and the optimal solution set satisfying the two conditions is obtained.


Introduction
The multi-objective optimization of central air conditioning is a comprehensive consideration of economics and human dissatisfaction PPD [1]. It is a practical engineering multi-objective optimization problem to find a series of Pareto optimal solutions that meet the constraints and have the lowest energy consumption of air conditioners and the smallest PPD of human dissatisfaction [2].The multiple constraints of central air conditioners are non-linear, which makes it difficult for the objective function to quickly converge to the local optimum during the optimization process. The multi-objective optimization algorithm is a group-based random search algorithm, which is suitable for multi-objective optimization of air conditioners [3].Multi-objective intelligent optimization algorithm to solve the multi-objective optimization problem of central air-conditioning is a hot issue at present, and domestic and foreign scholars have done a lot of research successively [4]. The new NSGA-II algorithm is added to the original NSGA algorithm. The calculation degree and calculation time are far lower than the NSGA algorithm [5]. At the same time, on the basis of the original algorithm, a new operator is introduced to replace the original shared radius. The introduction of a new congestion degree and a new congestion degree comparison operator makes the comparison criteria after non-dominated sorting, the congestion degree is large. Wins. This new calculation standard makes the solution set distribution in the entire solution set domain more uniform, and all solution sets in the quasi-Pareto domain can be extended to Pareto. After the introduction of new operators, the diversity of algorithms has been greatly improved [6]. Based on the advantages of NSGA-II algorithm, a mathematical model for multi-objective optimization of central air conditioning is established. Simulation results show that the NSGA-II algorithm can avoid falling into a local optimum and thus obtain a more uniformly distributed Pareto optimal solution.

Energy Consumption Model of Central Air Conditioning Air Treatment System
The central air-conditioning air treatment system is a system composed of an Air Handling Unit (AHU), a terminal device, a wind pipe and a room. The air processing unit mixes fresh air and return air according to the corresponding parameters of the air in the air-conditioned room to form a mixed air and transport it to the heat exchange equipment such as the terminal device and the air processing unit. At the same time, the chilled water continuously sends cold capacity to the air processing unit for heat exchange with the mixed air. After the processed mixed air reaches the air supply standard, the room is provided with air through the air supply duct. The structure of the AHU is shown in Figure 1.

Figure 1.
Air-conditioning unit (AHU) structure Based on the system operation principle and overall energy consumption analysis, it was determined that the main energy consumption equipment of the central air conditioning air treatment system is the chilled water pump and air supply fan [7].In order to achieve energy saving effects and minimize the total power consumption of the chilled water pump and air supply fan, the mathematical model and total objective function of the chilled water pump, air supply fan are as follows:

   e d
The overall objective function of the central air conditioning air processing system is:

Room Comfort Index PMV-PPD
There are many factors that affect human comfort. Some factors have little effect and cannot be described in detail. Temperature has the greatest effect on human comfort [8]. Therefore, this paper analyzes the PMV index of indoor thermal comfort in detail, and the relationship is as follows: M is the energy metabolism rate of the human body; W is mechanical work done by the human body; a P is partial pressure of water vapor around the human body; a t is Indoor air temperature; cl f is clothing area coefficient; r t is room average radiation temperature; cl I is clothing thermal resistance; cl t is Outer surface temperature of clothes; c h is Heat transfer coefficient.
0 PMV  , 5% PPD  At this point, the human body is absolutely comfortable. When PMV is [-0.5 0.5], corresponding, more than 90% of people will feel comfortable at this time, indicating that the environment at this time is comfortable. Within the comfortable range, the smaller the PPD index, the more comfortable the human body will feel the environment. The objective function of thermal comfort comprehensive evaluation is as follows: Figure 2. NSGA-II algorithm Pareto surface The above simulation result graph represents the application of the multi-objective optimization algorithm to the multi-objective optimization problem of the central air conditioning air processing system, and the distribution of the Pareto optimal solution set on the target space. In the figure, the abscissa represents the thermal comfort index PPD/%; the ordinate represents the total energy consumption of the central air conditioning /w.

Summary
This paper makes a comprehensive analysis of the central air-conditioning air treatment system, and gives the total energy consumption model of the air treatment system, including chilled water pump energy consumption and air supply fan energy consumption. According to the data of the laboratory related equipment and the relevant information of the central air conditioning system, the relevant operating parameters in the central air conditioning energy consumption model are set, and the evaluation index PMV, which represents the thermal sensation of the human body, and the PPD index, which represents the degree of dissatisfaction with the thermal environment, are applied To describe the comfort of the room, a minimum PPD evaluation model is established, and the PPD constraint range is set. Finally, a multi-objective optimization model is established with the minimum total energy consumption of the air treatment system and the minimum PPD. According to the equipment of the experimental platform, the value range of the optimization variables is set, and the multi-objective optimal solution set of the air treatment system is found within the constraint interval of all variables.