Optimal chiller loading in HVAC System Using a Novel Algorithm Based on the distributed framework

Abstract

Aimed at the optimal chiller loading (OCL) problem in heating, ventilation and air conditioning (HVAC) system, a distributed framework for HVAC control is introduced and discussed. And furthermore, the distributed chaotic estimation of distribution algorithm (DCEDA) based on this framework is proposed. Firstly, compared with the centralized framework, the distributed framework has the features of flexibility and expansibility. Therefore, the distributed framework can fit the development of HVAC control system better. Secondly, in the proposed algorithm, an initialization methodology based on logistic map is developed and the chaotic mutation mechanism is applied to increase the search capability of the algorithm. To testify the performance of DCEDA, two well-known cases based on the OCL problem are tested and the results are compared with other algorithms. The results show that DCEDA is an efficient distributed optimization algorithm with good robustness, stability and convergence, and it can achieve significant energy saving effect.