Parallel pump and chiller system optimization method for minimizing energy consumption based on a novel multi-objective gorilla troops optimizer

Abstract

Minimizing the energy usage of the parallel pump and chiller system is a crucial method for lowering buildings’ energy consumption. The variations in the cooling load of buildings should be taken into account when optimizing the operation of the parallel pump and chiller system. Although several strategies have been put forth, it is challenging to operate at a general optimal level. The parallel pump and chiller system with different chillers and pumps is frequently used in practical applications but is rarely taken into account in literature. Hence, we propose a two-step energy consumption optimization method for a parallel pump and chiller system with different chillers and pumps based on a novel multi-objective gorilla troops optimizer (MOGTO). The gorilla troops optimizer (GTO), which makes use of an exclusive non-dominated sorting (NDS) and a diversity-preserving crowding distance (CD) mechanism, is the inspiration for the proposed MOGTO method. By resolving the trade-off between chillers and pumps, a holistic optimization based on the MOGTO algorithm was carried out to determine the least amount of energy used overall. By optimizing practical parameters, including binary and continuous variables, the overall energy consumption as well as the difference between the flow rates of pumps and chillers were simultaneously reduced. A simulation was used to examine the suggested strategy. The outcomes imply that the optimization was made logically.