Building-mix Optimization Of The District-cooling System In The Typical Climate Area

A district-cooling system(DCS) can serve a group of buildings with diversifying daily cooling-load patterns which means different combinations of building types will result in different cooling-load patterns of the whole DCS. As we know, a more uniform cooling energy production is to minimize the start and stop counts of chillers and supply stable cooling energy. The improvement of the refrigeration efficiency is possible when the fluctuation in cooling load can be leveled out by serving a mix of building types with remarkable differences in cooling-load patterns. Therefore, the study of the building-mix optimization in district-cooling system implementation is very meaningful to the DCS.This paper has put the hot summer and cold winter region and the hot summer and warm winter region as the study area and studied the best combination of building types in DCS under different conditions on the basis of selecting the office, residential, hotel and shop as the customer buildings of the DCS. Firstly, this paper establishes the typical building models of the office, residential, hotel and shop, and then analyzes the cooling-load pattern of every kind of building on the basis of the hourly cooling load of the four kinds of buildings got by the use of the Design Builder energy simulation software. Secondly, this paper establishes the building-mix optimization model on the basis of using the fluctuation index as the objective function and selects the genetic algorithm to solve the best combination of building types in DCS under different conditions. Then, this paper has done a further analysis about the applicability of the building-mix optimization model, and the results turns out that with a slight modification, the model can be used for the building-mix optimization of almost all kinds of DCSs in the decision-making process even though the building-mix optimization model is estabilished on the basis of the four types of typical buildings.Finally, this paper analyzes the best combination of building types, the capacity index, load frequency and time frequency under twelve conditions. The conclusion shows the relationship between the actual cooling requirement and the design load at each time when the air conditioning is running which can be a guidance for the selection of the air Conditioning equipment and the design of the air-conditioning system.