Applicability of control algorithms for variable water-flow control practice of central air-conditioning cooling water system

Abstract

Cooling water (CW) system with strong nonlinear characteristics is a critical component of central air conditioning systems. Further, variable flow control of CW pumps is a critical measure for achieving energy-saving operation of CW systems. Proportional–integral (PI) control algorithm is widely used in the variable flow control of CW systems, and fuzzy control algorithm also plays a significant role in these systems. In this study, the application of fuzzy control and PI control algorithms is experimentally studied in a CW constant temperature difference system. The results indicate that the PI control algorithm of the CW system is simple in structure, and it only requires a reasonable PI parameter setting to achieve better control effect with high accuracy, good steady-state performance, and low energy consumption. However, the PI control algorithm is not adaptive for different working conditions. The fuzzy control algorithm has better dynamic performance and the adjustment curve is smooth with small fluctuations, although its control accuracy is not high. Over the same test period, the regulation frequency of the water pump under PI control algorithm is higher than that of the fuzzy control algorithm, and the CW system exhibits better stability under the fuzzy control algorithm.

Additional information

Funding

This study was supported by the National Key Research and Development Project of China No. 2017YFC0704100 (entitled New Generation Intelligent Building Platform Techniques). This study was supported by the Fundamental Research Funds for Central Universities (Grant No. DUT17ZD232). This study was supported by the Liaoning Natural Science Foundation Guidance Plan (Grant No. 20180551057). This study was supported by the Dalian High-level Talent Innovation Support Program (Youth Technology Star) (Grant No. 2017RQ099). This study was supported by the Applied Fundamental Research Project of Jiaxing Science and Technology Bureau (Grant No. 2020AY10020).

Notes on contributors

Tianyi Zhao

Tianyi Zhao, PhD, is an Associate Professor.

Pengmin Hua

Pengmin Hua is a Graduate Student.

Peng Fu

Peng Fu is Graduate Student.

Jili Zhang

Jili Zhang, PhD, is a Professor.

Kuishan Li

Kuishan Li, PhD, is an Associate Professor.