Title:	DATA MINING FOR ENERGY MANAGEMENT IN A WATER DISTRIBUTION NETWORK
Author(s):	Hohyun Lee, Dae Wook Kim, Sung Taek Hong and Gang Wook Shin
ISBN:	978-989-8533-92-0
Editors:	Ajith P. Abraham and Jörg Roth
Year:	2019
Edition:	Single
Keywords:	Water, Reservoir Tank, Learning Algorithm, Electric Fee
Type:	Poster
First Page:	239
Last Page:	241
Language:	English
Cover:
Full Contents:	click to dowload
Paper Abstract:	In the water treatment process, it is important to predict the flow used by citizens and control valves for using large reservoir tanks maximally. In this study, flow predictions are proposed by applying several non-linear algorithms with recursive form to minimize additional learning. To control the valves properly, the target levels of each tank are determined based on flow prediction and genetic algorithms. A simple polynomial learning algorithm is also proposed to control the valves less frequently than a conventional feedback controller until the target tank levels can be reached, which also help not to break down the valves. The proposed method to maximize the usage of reservoir tanks is expected to reduce the electric fee and improve water quality.
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