Minimizing pump energy in a wastewater processing plant
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DOI: 10.1016/j.energy.2012.08.048
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- Omprakash K. Gupta & A. Ravindran, 1985. "Branch and Bound Experiments in Convex Nonlinear Integer Programming," Management Science, INFORMS, vol. 31(12), pages 1533-1546, December.
- Hansen, Pierre & Mladenovic, Nenad, 2001. "Variable neighborhood search: Principles and applications," European Journal of Operational Research, Elsevier, vol. 130(3), pages 449-467, May.
- Kusiak, Andrew & Tang, Fan & Xu, Guanglin, 2011. "Multi-objective optimization of HVAC system with an evolutionary computation algorithm," Energy, Elsevier, vol. 36(5), pages 2440-2449.
- Kusiak, Andrew & Li, Mingyang & Zhang, Zijun, 2010. "A data-driven approach for steam load prediction in buildings," Applied Energy, Elsevier, vol. 87(3), pages 925-933, March.
- Xu, Zhenjun & Wu, Huaizhi & Wu, Meiling, 2010. "Energy performance and consumption for biogas heat pump air conditioner," Energy, Elsevier, vol. 35(12), pages 5497-5502.
- Kusiak, Andrew & Xu, Guanglin & Tang, Fan, 2011. "Optimization of an HVAC system with a strength multi-objective particle-swarm algorithm," Energy, Elsevier, vol. 36(10), pages 5935-5943.
- Makris, P.A. & Makri, A.P. & Provatidis, C.G., 2006. "Energy-saving methodology for material handling applications," Applied Energy, Elsevier, vol. 83(10), pages 1116-1124, October.
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- Kirchem, Dana & Lynch, Muireann Á. & Bertsch, Valentin & Casey, Eoin, 2020. "Modelling demand response with process models and energy systems models: Potential applications for wastewater treatment within the energy-water nexus," Applied Energy, Elsevier, vol. 260(C).
- Filipe, Jorge & Bessa, Ricardo J. & Reis, Marisa & Alves, Rita & Póvoa, Pedro, 2019. "Data-driven predictive energy optimization in a wastewater pumping station," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
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- Sun, Jin & Feng, Xiao & Wang, Yufei & Deng, Chun & Chu, Khim Hoong, 2014. "Pump network optimization for a cooling water system," Energy, Elsevier, vol. 67(C), pages 506-512.
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- Luca O. Turci & Jingcheng Wang & Ibrahim Brahmia, 2020. "Adaptive and Improved Multi-population Based Nature-inspired Optimization Algorithms for Water Pump Station Scheduling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2869-2885, July.
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- Torregrossa, Dario & Hansen, Joachim & Hernández-Sancho, Francesc & Cornelissen, Alex & Schutz, Georges & Leopold, Ulrich, 2017. "A data-driven methodology to support pump performance analysis and energy efficiency optimization in Waste Water Treatment Plants," Applied Energy, Elsevier, vol. 208(C), pages 1430-1440.
- Rashidi, M.M. & Ali, M. & Freidoonimehr, N. & Nazari, F., 2013. "Parametric analysis and optimization of entropy generation in unsteady MHD flow over a stretching rotating disk using artificial neural network and particle swarm optimization algorithm," Energy, Elsevier, vol. 55(C), pages 497-510.
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- Zhang, Zijun & Kusiak, Andrew & Zeng, Yaohui & Wei, Xiupeng, 2016. "Modeling and optimization of a wastewater pumping system with data-mining methods," Applied Energy, Elsevier, vol. 164(C), pages 303-311.
- Zheng, Chenglin & Chen, Xi & Zhu, Lingyu & Shi, Jiaqi, 2018. "Simultaneous design of pump network and cooling tower allocations for cooling water system synthesis," Energy, Elsevier, vol. 150(C), pages 653-669.
- Vojtěch Zejda & Vítězslav Máša & Šárka Václavková & Pavel Skryja, 2020. "A Novel Check-List Strategy to Evaluate the Potential of Operational Improvements in Wastewater Treatment Plants," Energies, MDPI, vol. 13(19), pages 1-21, September.
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Keywords
Mixed-integer nonlinear programming; Energy saving; Data mining; Pump control; Particle swarm optimization; Neural networks;All these keywords.
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