NDLI: Intelligent system based supervision for energy management of water chiller plant

Content Provider	IEEE Xplore Digital Library
Author	Radeerom, M. Tharathanmathikorn, K.
Copyright Year	2015
Description	Author affiliation: Fac. of Inf. Technol., Rangsit Univ., Pathumthani, Thailand (Radeerom, M.; Tharathanmathikorn, K.)
Abstract	For almost a decade, intelligent systems have shown great potential for solving non-linear control problems. This paper exhibits a possibility of using a neuro-fuzzy system to advise a chiller plant. This plant, located at Building No.11 of Rangsit University, consists of three water chillers. Nonlinear dynamic characteristics, resulting from outdoor conditions, and equipment within the plant such as pumps and modulation valves, are discussed herein. The objective of this research is to minimize energy cost while maintaining high performance of the plant. In this paper, identification and prediction of a non-linear discrete time system using a neuro-fuzzy system is investigated. To develop an algorithm for achieving such an objective, the first step is to learn the relationship of outdoor temperature, humidity, and cooling load of the building, or the plant dynamics, from historical data. After being trained completely, the neuro-fuzzy system is used to predict the cooling load for Building No.11 at Rangsit University and operating optimal points of the water chiller plant. We use the visual studio to develop an advised chiller plant management program. This program learns the information from both historical and presents data of the chiller plant. After that, we compared energy costs before (May-July 2014) and after (August-October 2014) using advisory management of the chiller plant program. The system can reduce electrical cost within 5%. Furthermore, it can be trained by plant operators continuously.
Starting Page	1
Ending Page	6
File Size	2497034
Page Count	6
File Format	PDF
e-ISBN	9781479979615
DOI	10.1109/ECTICon.2015.7207123
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-06-24
Publisher Place	Thailand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Temperature measurement Temperature distribution Management System Cooling Buildings Artificial neural networks HAVC Neuro-Fuzzy Intelligent systems The system Identification Intelligence control
Content Type	Text
Resource Type	Article

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