Energy Saving - Another Perspective for Parameter Optimization of P and PI Controllers

Yongling Wu, Xiaodong Zhao, Kang Li, Min Zheng, Shaoyuan Li

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Modern control methods like optimal control and model predictive control (MPC) provide a framework for simultaneous regulation of the tracking performance and limiting the control energy, thus have been widely deployed in industrial applications. Yet, due to its simplicity and robustness, the conventional P (Proportional) and PI (Proportional–Integral) control are still the most common methods used in many engineering systems, such as electric power systems, automotive, and Heating, Ventilation and Air Conditioning (HVAC) for buildings, where energy efficiency and energy saving are the critical issues to be addressed. Yet, little has been done so far to explore the effect of its parameter tuning on both the system performance and control energy consumption, and how these two objectives are correlated within the P and PI control framework. In this paper, the P and PI controllers are designed with a simultaneous consideration of these two aspects. Two case studies are investigated in detail, including the control of Voltage Source Converters (VSCs) for transmitting offshore wind power to onshore AC grid through High Voltage DC links, and the control of HVAC systems. Results reveal that there exists a better trade-off between the tracking performance and the control energy through a proper choice of the P and PI controller parameters.
Original languageEnglish
Pages (from-to)500-513
Number of pages14
JournalNeurocomputing
Volume174
Issue numberPart A
Early online date03 Sep 2015
DOIs
Publication statusPublished - 22 Jan 2016

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