Journal article
Optimizing wastewater pumping system with data-driven models and a greedy electromagnetism-like algorithm
Stochastic environmental research and risk assessment, Vol.30(4), pp.1263-1275
04/2016
DOI: 10.1007/s00477-015-1115-4
Abstract
Optimizing a pumping system in the wastewater treatment process by improving its operational schedules is presented. The energy consumption and outflow rate of the pumping system are modeled by a data-driven 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.
Details
- Title: Subtitle
- Optimizing wastewater pumping system with data-driven models and a greedy electromagnetism-like algorithm
- Creators
- Yaohui Zeng - University of IowaZijun Zhang - University of Hong KongAndrew Kusiak - University of IowaFan Tang - University of IowaXiupeng Wei - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Stochastic environmental research and risk assessment, Vol.30(4), pp.1263-1275
- Publisher
- Springer Berlin Heidelberg
- DOI
- 10.1007/s00477-015-1115-4
- ISSN
- 1436-3240
- eISSN
- 1436-3259
- Grant note
- 10-1 / Iowa Energy Center
- Language
- English
- Date published
- 04/2016
- Academic Unit
- Industrial and Systems Engineering; Nursing; Biostatistics
- Record Identifier
- 9984187074902771
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