Abstract
In the multi-chiller of the air conditioning system, the optimal chiller loading (OCL) is an important research topic. This research is to find the appropriate partial load ratio (PLR) for each chiller in order to minimize the total energy consumption of the multi-chiller under the system cooling load (CL) requirements. However, this optimization problem has not been well studied. In this paper, in order to solve the OCL problem, we propose an improved fruit fly optimization algorithm (IFOA). A linear generation mechanism is developed to uniformly generate candidate solutions, and a new dynamic search radius method is employed to balance the local and global search ability of IFOA. To empirically evaluate the performance of the proposed IFOA, a number of comparative experiments are conducted on three well-known cases. The experimental results show that IFOA found 14 optimal values (the optimal values among all algorithms) under a total of 17 CLs in three cases, and the ratio of the optimal values found was 82.4%, which was the highest among all algorithms. In addition, the mean value of all objective functions of IFOA is smaller and the standard deviation is equal to or close to 0, which proves that the algorithm has high stability. It can be concluded that IFOA is an ideal method to solve the OCL problem.
Highlights
To maintain comfort level of an indoor life during hot and humid weather, many people rely on air-conditioning systems
Three well-known cases are selected to verify the performance of improved fruit fly optimization algorithm (IFOA) in solving the optimal chiller loading (OCL) problem
Of a total of 17 cooling load (CL), IFOA found a total of 14 optimal values; the ratio of the optimal value found is 82.4%, and the ratio of the optimal value found in all algorithms is the highest
Summary
To maintain comfort level of an indoor life during hot and humid weather, many people rely on air-conditioning systems. Air-conditioning systems are used in large quantities, and their energy consumption for the supply of CL accounts for more than 30% of the total power generation [1]. In air-conditioning systems, the multi-chiller system is the main energy-consumption equipment. If the chillers are improperly managed, the energy consumption of the chiller will be increased significantly. Because the multi-chiller system is composed of chillers of different design capacities and performance feature, the optimal load distribution of each chiller can obtain minimum energy consumption when meeting CL demand [2]. For the part load ratios of all chillers, it is a valuable research topic to find their optimal combination by using optimization methods
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