Optimum Reservoir Operating Policies and the Imposition of a Reliability Constraint

Askew, Arthur J.

doi:10.1029/wr010i001p00051

Cited by 64 publications

(32 citation statements)

References 8 publications

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“…Un choix simplificateur est alors d'utiliser la programmation dynamique sur des scénarios d'évolutions possibles (GOUSSEBAILLE et ROCHE, 1988) ou de tester par simulations ou ajustement une classe restreinte de règles de gestion (BHASKAR etWHiTLACH, 1987). Sinon, la prise en compte explicite des aléas, en sus de la plus grande complexité des algorithmes de programmation dynamique stochastique qu'elle entraîne, doit rendre compte des notions de fiabilité et de défaillance de gestion, ASKEW (1974), SIMONOVIC et ORLOB (1984), RICHARD et TURGEON (1988) (1984).…”

Section: -Présentationunclassified

Gestion stratégique d'un système de ressources en eau : l'exemple du système NESTE

Parent¹,

Lebdi²,

Hurand³

2005

rseau

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L'article que nous proposons s'inscrit dans le cadre des problèmes d'optimisation bimensionnelle (irrigation & salubrité) des ressources en eau durant la période d'étiage. Sur le cas du système NESTE, la résolution est effectuée selon deux approches :- un modèle de programmation dynamique avec état de dimension deux (niveau des réserves, niveau dans la rivière) où, dans la solution numérique, les variables sont discrétisées;- un modèle « synthétique » où l'on calcule une probabilité de non dépassement caractérisant l'état hydrique des ressources du système. Une règle empirique permet d'associer à cette grandeur une décision de consigne à effectuer.Les résultats numériques sont comparés sur une série de chroniques historiques. Les avantages et les inconvénients de chacune des deux approches sont mis en lumière sur le cas réel du système NESTE.This paper deals with bicreteria (irrigation & water quality) weekly operation of a water resource system during dry period. Two ways of handling the problem are assessed and compared on a real case study :- a stochastic dynamic programming modal with a two dimensional state (reservoirs level, river level) that is numerically solved by discretization ;- a more « synthetic » model where the state is expressed in term of a tail aera probability related to the consumption of all the present water resources in the future. A practical decision rule is based upon the associated critical value.Numerical results are plotted on historical varies for both methods.From the present application to the NESTE system, the conclusions are :1) Both procedures allow the system manager to formulate operating strategies in a rational way :- An operating rule can be derived to allocate water so as to meet a combination of the various objectives. It is expressed as a feedback law linking what we know from the state of the system to how we control its evolution.- Both methods need a parameter to be set up by stochastic simulation.- They give close results on the basis of the past data and can be conveniently proposed to system managers.2) The system analysis approach is based on stochastic dynamic programming. If can be efficiently used to derive optimal feedback ruses of operation and can routinely deal with complex decisions such as limiting irrigation when a shortage is to occur or take the risk to keep going and decrease output targets for water quality management. At the same time, this procedure entails heavy computing time, uneasy interpretation of the weighting coefficient between irrigation and water quality objectives, and a rather artificial elicitation of the global compromise.Such an approach is very well fit for simulation because it is composed of elementary blocks that are gathered in a transition relationship to describe the system's dynamic evolution. This approach also provides a means to get an optimal policy as long as the system manager accepts the necessity to formulate an objective function consistently with dynamic programming (i. e. stages are separable and additive). Of co...

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Section: -Présentationunclassified

Gestion stratégique d'un système de ressources en eau : l'exemple du système NESTE

Parent¹,

Lebdi²,

Hurand³

2005

rseau

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“…Askew [21] used SDP to derive optimum reservoir operating policy considering reliability constraints. A DP procedure was developed in [22] to solve reliability-constrained reservoir operation problems.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Relaxed Cellular Automata Method for Reliability-Based Hydropower Operation of Reservoirs

Azizipour

Afshar

2017

Scientia Iranica

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Abstract. This paper presents a novel cellular automata Approach as the solution to reliability-based reservoir hydropower operation problems. The method is based on the observation that a low value of the penalty parameter would lead to partial enforcement of the constraints. Therefore, in this method, the constraints of the chance-constrained operation problem, namely operational and reliability constraints, are dealt with di erently. A high enough value of the penalty parameter is used for the rst set while a lower than enough value is used for the second set, leading to strong enforcement of the rst set of the constraint and partial ful llment of the second set. Since the proper value of the penalty parameter to be used for the reliability constraints is not known a priori, an adaptive method is proposed to nd the proper value. The proposed model is used for operation of Dez reservoir in Iran and the results are presented and compared with those of a Genetic Algorithm. Hydropower operation is considered over short, medium, and long-term periods to demonstrate the e ciency and e ectiveness of the proposed method for problems of di erent scales. The proposed model has proven to produce results superior to the results of GA with much reduced computational e ort.

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“…While most of the methods developed were used for optimal operation of reservoirs disregarding the importance of reliability, some researchers proposed methods to solve chance constrained reservoir management problems. Askew (1974) used SDP to derive optimum reservoir operating policy considering reliability constraints. A DP procedure was developed by Sniedovich (1979) to solve reliability-constrained reservoir operation problems.…”

Section: Introductionmentioning

confidence: 99%

The Density Classification Problem in the Context of Continuous Cellular Automata

Wolnik

Dembowski

Bołt

et al. 2016

Lecture Notes in Computer Science

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Optimum Reservoir Operating Policies and the Imposition of a Reliability Constraint

Cited by 64 publications

References 8 publications

Gestion stratégique d'un système de ressources en eau : l'exemple du système NESTE

Gestion stratégique d'un système de ressources en eau : l'exemple du système NESTE

An Adaptive Relaxed Cellular Automata Method for Reliability-Based Hydropower Operation of Reservoirs

The Density Classification Problem in the Context of Continuous Cellular Automata

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