Optimizing wastewater pumping system with data-driven models and a greedy electromagnetism-like algorithm

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

22 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)1263-1275
Journal / PublicationStochastic Environmental Research and Risk Assessment
Volume30
Issue number4
Online published26 Jun 2015
Publication statusPublished - Apr 2016

Abstract

Optimizing a pumping system in the wastewater treatment process by improving its operational schedules is presented. The energy consumption and out- flow rate of the pumping system are modeled by a datadriven approach. A mixed-integer nonlinear programming (MINLP) model containing data-driven components and pump operational constraints is developed to minimize the energy consumption of the pumping system while maintaining the required pumping workload. A greedy electromagnetism-like (GEM) algorithm is designed to solve the MINLP model for optimized operational schedules and pump speeds. Three computational cases are studied to demonstrate the effectiveness of the proposed data-driven modeling and GEM algorithm. The computational results show that significant energy saving can be obtained.

Citation Format(s)

Optimizing wastewater pumping system with data-driven models and a greedy electromagnetism-like algorithm. / Zeng, Yaohui; Zhang, Zijun; Kusiak, Andrew; Tang, Fan; Wei, Xiupeng.

In: Stochastic Environmental Research and Risk Assessment, Vol. 30, No. 4, 04.2016, p. 1263-1275.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review