Optimal operation of water distribution networks by predictive control using MINLP

Biscos, C; Mulholland, M.; Lann, M-V Le; Buckley, C.A.; Brouckaert, C.J.

doi:10.4314/wsa.v29i4.5044

Cited by 35 publications

(38 citation statements)

References 90 publications

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“…Note that for each strategy the enforcement of terminal constraints implies an increment of the economic cost. This decrease in Subindex (1) indicates non-periodic behaviour enforced while (2) indicates that the periodic constraint is enforced. (2) , the terminal constraint is set up in relation to a pre-calculated optimal cycle obtained from (6).…”

Section: B Resultsmentioning

confidence: 99%

“…This decrease in Subindex (1) indicates non-periodic behaviour enforced while (2) indicates that the periodic constraint is enforced. (2) , the terminal constraint is set up in relation to a pre-calculated optimal cycle obtained from (6). In the HEMPC (2) , the reference trajectory is computed by the upper layer every 24h.…”

Section: B Resultsmentioning

confidence: 99%

“…The complexity of DWNs, (i.e., dimensionality, nonlinearities, infrastructure constraints, uncertainties), the stronger requirements for water transport service quality and the need for a sustainable exploitation of the available resources make the management of these systems a challenging control problem that has caught the attention of the scientific community, see e.g., [2]- [5], [10], [16], [18]. As discussed in the aforementioned references, several approaches are reported in the literature to address the operation of DWNs, ranging from heuristics and expert systems to more advanced mathematical modelling and optimisation techniques, hierarchical-decompositions, combinatorial schemes, and more recently, model predictive control (MPC).…”

Section: Introductionmentioning

confidence: 99%

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Economic MPC for the management of drinking water networks

Grosso

Ocampo‐Martínez

Puig

et al. 2014

2014 European Control Conference (ECC)

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Abstract-This paper addresses the management of drinking water networks (DWNs) regarding a multi-objective cost function by means of economically-oriented model predictive control (EMPC) strategies. Specifically, assuming the water demand and the energy price as periodically time-varying signals, this paper shows that the EMPC framework is flexible to enhance the control of DWNs without relying on hierarchical control schemes that require the use of real-time optimisers (RTO) or steady-state target optimisers (SSTO) in an upper layer. Four different MPC strategies are discussed in this paper: a hierarchical two-layer approach, a standard EMPC where the multi-objective cost function is optimised directly, and two different modifications of the latter, which are meant to overcome possible feasibility losses in the presence of changing operating patterns. The discussed schemes are tested and compared by means of a case study taken from a part of the Barcelona DWN.

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Section: B Resultsmentioning

confidence: 99%

Section: B Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Economic MPC for the management of drinking water networks

Grosso

Ocampo‐Martínez

Puig

et al. 2014

2014 European Control Conference (ECC)

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“…D'autres auteurs ont choisi de simplifier les problèmes étudiés pour utiliser la programmation linéaire (BOCCELLI et al, 1998;GUHL, 1999;TRYBY et al, 2002). BISCOS et al (2003) et YU et al (1994 …”

Section: Introductionunclassified

Algorithme Génétique (AG) pour le choix optimal des stations d’appoint de chlore sur les réseaux d’eau potable

Nouiri

Lebdi

2006

rseau

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La chloration sur les réseaux de distribution d’eau potable constitue une tâche délicate. Elle assure la protection contre la reviviscence microbienne et contre la contamination du réseau. Les réactions du chlore avec la matière organique du système entraînent la formation des sous‑produits chlorés, indésirables pour la santé humaine. Ainsi, le maintien du taux de chlore libre à des valeurs admissibles, sur tout le réseau et à tout moment, constitue un objectif principal des gestionnaires des réseaux.Lors de la chloration à partir des sources d’eau, les processus de réaction-transport créent sur les réseaux, caractérisés par des temps de séjours importants, de mauvaises distributions des taux de chlore libre. Les stations d’appoints sur les réseaux constituent une alternative efficace. La détermination de leur nombre et le choix des emplacements optimums constituent les deux difficultés auxquelles sont confrontés les gestionnaires. Le présent travail utilise un algorithme génétique (AG) pour la détermination du nombre et des emplacements optimums des stations d’appoint de chlore sur les réseaux. Deux objectifs ont été fixés : (1) l’amélioration de l’homogénéité spatio-temporelle de la chloration et (2) la minimisation du nombre de stations d’appoint. L’application du modèle développé sur un réseau test a permis d’identifier les emplacements des deux stations d’appoint de chlore. La solution optimale a considérablement amélioré l’homogénéité et a assuré, pour 98 % des noeuds, des taux de chlore libre dans l’intervalle admissible (0,1-0,5) mg/L.The chlorination of drinking water networks represents a delicate task. It ensures protection against microbial regrowth and network contamination. However, chlorine also reacts with organic matter in the system and leads to the formation of chlorinated by-products, which are undesirable for the human health. Thus, one of the main objectives of the water network manager is to maintain acceptable levels of free residual chlorine, at all network nodes and at all times. When water sources are chlorinated, reaction-transport processes create an unbalanced distribution of free chlorine concentrations, especially in networks characterized by long water residence times. Booster stations in networks constitute an efficient alternative to improve the spatial and temporal chlorine distribution. Their number and their optimum locations are two challenges facing network managers. In this respect, this paper suggests the use of a genetic algorithm (GA) to determine the number and the optimum locations of chlorine booster stations in networks. The two main objectives of this study were: (1) the improvement of the spatio-temporal homogeneity of chlorination and (2) the reduction of the number of booster stations.A solution to this optimisation problem is an arrangement of ns booster stations in n consumption nodes of the water network. To resolve this problem, we linked the toolkit of the hydrodynamic computer program EPANET, which uses a one-dimensional reaction-transport model, to the p...

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“…(Morari and Lee, 1999;Qin and Badgwell, 2003), including open water systems (Igreja and Lemos, 2009;Overloop, 2006). Application of MPC for pump management in WDS was proposed in (Biscos et al, 2003) but that study considered only off-line simulations and some abstract small-scale case study. This paper presents an online implementation of MPC integrated with an industrial supervisory control and data acquisition (SCADA) system and interfaced with an actual medium-scale WDS.…”

Section: Introductionmentioning

confidence: 99%

Model Predictive Control for Energy and Leakage Management in Water Distribution Systems

Skworcow

Ulanicki

AbdelMeguid

et al. 2010

UKACC International Conference on CONTROL 2010

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This paper considers development of a methodology for an on-line energy and leakage management in water distribution systems, formulated within a model predictive control framework. The approach involves calculation of control actions, i.e. time schedules for pumps, valves and sources, to minimize the costs associated with energy used for water pumping and treatment and water losses due to leakage, whilst satisfying all operational constraints. The process of computing the control action utilises EPAnet hydraulic simulator, a mathematical modelling language called GAMS and a non-linear programming solver called CONOPT. The proposed control scheme has been integrated with an industrial SCADA system from ABB and interfaced with an actual medium-scale water distribution systems being part of Yorkshire Water Services. The scheme is currently being tested using on-line telemetry data. It has been operational for over 1 month with 1 hour sampling time and the preliminary results described in this paper indicate a potential for savings of 30% of the cost of electrical energy.

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Optimal operation of water distribution networks by predictive control using MINLP

Cited by 35 publications

References 90 publications

Economic MPC for the management of drinking water networks

Economic MPC for the management of drinking water networks

Algorithme Génétique (AG) pour le choix optimal des stations d’appoint de chlore sur les réseaux d’eau potable

Model Predictive Control for Energy and Leakage Management in Water Distribution Systems

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