Optimal scheduling method for pressurized pumping stations with structural improvement DOI
Hongqiu Zhu, Yu Quan, Qilong Wan

et al.

Journal of Water Process Engineering, Journal Year: 2025, Volume and Issue: 73, P. 107679 - 107679

Published: April 15, 2025

Language: Английский

Optimization problems for machine learning: A survey DOI
Claudio Gambella, Bissan Ghaddar, Joe Naoum‐Sawaya

et al.

European Journal of Operational Research, Journal Year: 2020, Volume and Issue: 290(3), P. 807 - 828

Published: Aug. 29, 2020

Language: Английский

Citations

251

Efficiency achievement in water supply systems—A review DOI
Bernardete Coelho, A. Andrade‐Campos

Renewable and Sustainable Energy Reviews, Journal Year: 2013, Volume and Issue: 30, P. 59 - 84

Published: Oct. 15, 2013

Language: Английский

Citations

201

Sustainable Operations DOI
Florian Jaehn

European Journal of Operational Research, Journal Year: 2016, Volume and Issue: 253(2), P. 243 - 264

Published: March 5, 2016

Language: Английский

Citations

126

Demand side management in urban district heating networks DOI
Hanmin Cai, Charalampos Ziras, Shi You

et al.

Applied Energy, Journal Year: 2018, Volume and Issue: 230, P. 506 - 518

Published: Aug. 31, 2018

Language: Английский

Citations

113

A Lagrangian decomposition approach for the pump scheduling problem in water networks DOI Open Access
Bissan Ghaddar, Joe Naoum‐Sawaya, Akihiro Kishimoto

et al.

European Journal of Operational Research, Journal Year: 2014, Volume and Issue: 241(2), P. 490 - 501

Published: Oct. 9, 2014

Language: Английский

Citations

106

Demonstrating demand response from water distribution system through pump scheduling DOI Creative Commons

Ruben Menke,

Edo Abraham, Panos Parpas

et al.

Applied Energy, Journal Year: 2016, Volume and Issue: 170, P. 377 - 387

Published: March 11, 2016

Significant changes in the power generation mix are posing new challenges for balancing systems of grid. Many these secondary electricity grid regulation services and could be met through demand response (DR) services. We explore opportunities a water distribution system (WDS) to provide with pump scheduling evaluate associated benefits. Using benchmark network mechanisms available UK, benefits assessed terms reduced green house gas (GHG) emissions from due displacement more polluting sources additional revenues utilities. The optimal problem is formulated as mixed-integer optimisation solved using branch bound algorithm. This formulation finds level capacity commit provision range reserve energy frequency schemes offered UK. For first time we show that DR WDS can offer financial operators while providing less greenhouse than competing technologies. Monte Carlo simulation based on data 2014, demonstrate cost storage compensation equivalent supply. GHG also shown smaller those contemporary technologies such open cycle turbines. considered vary their duration well commitment requirements. viability service committed continuously strongly dependent utilisation pumps tariffs used by Through analysis scenarios incentives real market data, how participate scheme generate gains environmental

Language: Английский

Citations

102

Energy-Optimal Pump Scheduling and Water Flow DOI
Dariush Fooladivanda, Joshua A. Taylor

IEEE Transactions on Control of Network Systems, Journal Year: 2017, Volume and Issue: 5(3), P. 1016 - 1026

Published: Feb. 16, 2017

This paper focuses on the optimal operation of water supply networks. We model networks using hydraulic constraints and formulate a joint pump scheduling flow problem (OWF) characteristics variable speed pumps. OWF is mixed-integer nonlinear program. nonconvex, hence NP-hard. To compute an exact solution OWF, we first focus feasibility region propose second-order cone relaxation for OWF. prove that proposed several relevant network topologies. then objective function in show some energy metrics, can be transformed into Furthermore, ADMM-based algorithm to suboptimal solutions lower bounds value when nonconvex. Finally, consider real-world network, demonstrate effectiveness computing schedules flows.

Language: Английский

Citations

100

Bayesian optimization of pump operations in water distribution systems DOI Creative Commons
Antonio Candelieri, Riccardo Perego, Francesco Archetti

et al.

Journal of Global Optimization, Journal Year: 2018, Volume and Issue: 71(1), P. 213 - 235

Published: March 26, 2018

Bayesian optimization has become a widely used tool in the and machine learning communities. It is suitable to problems as simulation/optimization and/or with an objective function computationally expensive evaluate. based on surrogate probabilistic model of whose mean variance are sequentially updated using observations "acquisition" model, which sets next observation at most "promising" point. The Gaussian Process basis well-known Kriging algorithms. In this paper, authors consider pump scheduling problem Water Distribution Network both ON/OFF variable speed pumps. global accounting for time patterns demand energy price allows significant cost savings. Nonlinearities, binary decisions case pumps, make challenging, even small Networks. EPANET simulator compute associated schedule verify that hydraulic constraints not violated met. Two Optimization approaches proposed where Random Forest, respectively. Both tested different acquisition functions set test functions, benchmark from literature large-scale real-life Milan, Italy.

Language: Английский

Citations

87

McCormick envelopes in mixed-integer PDE-constrained optimization DOI Creative Commons

Sven Leyffer,

Paul Manns

Mathematical Programming, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 6, 2025

Abstract McCormick envelopes are a standard tool for deriving convex relaxations of optimization problems that involve polynomial terms. Such provide lower bounds, example, in branch-and-bound procedures mixed-integer nonlinear programs but have not gained much attention PDE-constrained so far. This lack may be due to the distributed nature such problems, which on one hand leads infinitely many linear constraints (generally state difficult handle) addition equation pointwise formulation and renders bound-tightening successively improve resulting computationally intractable. We analyze model problem class is governed by semilinear PDE involving bilinearity integrality constraints. approximate nonlinearity turn averaging involved terms over cells partition computational domain defined. yields underestimate original up an priori error estimate depends mesh size discretization. These can improved means optimization-based procedure. show their minimizers converge limit with when driving zero. we certify all our imposed assumptions. The results point both potential methodology gaps research need closed. Our provides framework first obtaining underestimators nonconvexities second approximating them finitely inequalities infinite-dimensional setting.

Language: Английский

Citations

1

Work crew routing problem for infrastructure network restoration DOI Creative Commons

Nazanin Morshedlou,

Andrés D. González, Kash Barker

et al.

Transportation Research Part B Methodological, Journal Year: 2018, Volume and Issue: 118, P. 66 - 89

Published: Oct. 26, 2018

Language: Английский

Citations

70