**A Fuzzy Control Strategy Using the Load Forecast for Air Conditioning System**

#### **Jing Zhao \* and Yu Shan**

*Article*

Tianjin Key Lab of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China; shanyu@tju.edu.cn

**\*** Correspondence: zhaojing@tju.edu.cn; Tel.: +86-022-8740-2072

Received: 9 December 2019; Accepted: 19 January 2020; Published: 21 January 2020

**Abstract:** The energy consumption of air-conditioning systems is a major part of energy consumption in buildings. Optimal control strategies have been increasingly developed in building heating, ventilation, and air-conditioning (HVAC) systems. In this paper, a load forecast fuzzy (LFF) control strategy was proposed. The predictive load based on the SVM method was used as the input parameter of the fuzzy controller to perform feedforward fuzzy control on the HVAC system. This control method was considered as an effective way to reduce energy consumption while ensuring indoor comfort, which can solve the problem of hysteresis and inaccuracy in building HVAC systems by controlling the HVAC system in advance. The case study was conducted on a ground source heat pump system in Tianjin University to validate the proposed control strategy. In addition, the advantages of the LFF control strategy were verified by comparing with two feedback control strategies, which are the supply water temperature (SWT) control strategy and the room temperature fuzzy (RTF) control strategy. Results show that the proposed LFF control strategy is capable not only to ensure the minimum indoor temperature fluctuations but also decrease the total energy consumption.

**Keywords:** load forecast fuzzy (LFF) control; SVM method; building HVAC system; time delay effect; optimal control strategy
