Open Access

ARTICLE

HVAC Optimal Control Based on the Sensitivity Analysis: An Improved SA Combination Method Based on a Neural Network

by Lifan Zhao^1,2, Zetian Huang^1,2, Qiming Fu^1,2,3,*, Nengwei Fang⁴, Bin Xing⁴, Jianping Chen^2,3,*

1 School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou, 215009, China
2 Jiangsu Key Laboratory of Intelligent Building Energy Efficiency, Suzhou University of Science and Technology, Suzhou, 215009, China
3 Suzhou Key Laboratory of Mobile Network Technology and Application, Suzhou University of Science and Technology, Suzhou, 215009, China
4 Chongqing Industrial Big Data Innovation Center Co., Ltd., Chongqing, 400707, China

* Corresponding Authors: Qiming Fu. Email: ; Jianping Chen. Email:

(This article belongs to the Special Issue: Advanced Intelligent Decision and Intelligent Control with Applications in Smart City)

Computer Modeling in Engineering & Sciences 2023, 136(3), 2741-2758. https://doi.org/10.32604/cmes.2023.025500

Received 17 July 2022; Accepted 26 October 2022; Issue published 09 March 2023

Abstract

Aiming at optimizing the energy consumption of HVAC, an energy conservation optimization method was proposed for HVAC systems based on the sensitivity analysis (SA), named the sensitivity analysis combination method (SAC). Based on the SA, neural network and the related settings about energy conservation of HVAC systems, such as cooling water temperature, chilled water temperature and supply air temperature, were optimized. Moreover, based on the data of the existing HVAC system, various optimal control methods of HVAC systems were tested and evaluated by a simulated HVAC system in TRNSYS. The results show that the proposed SA combination method can reduce significant computational load while maintaining an equivalent energy performance compared with traditional optimal control methods.

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Keywords

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