Mixed-Integer Programming Model for Reservoir Performance Optimization
01 Sep 1999-Journal of Water Resources Planning and Management (American Society of Civil Engineers)-Vol. 125, Iss: 5, pp 298-301
TL;DR: In this paper, a mixed-integer programming model for the operation of a water supply reservoir during critical periods has been presented in the literature that incorporates reliability, resilience, and vulnerability, and an improved formulation of this model that represents resilience more completely is discussed.
Abstract: Failures in operation of water supply reservoir systems are often unavoidable during critical hydrologic periods. The failure characteristics of such systems can be represented by performance indicators such as reliability, resilience, and vulnerability. A mixed-integer programming model for the operation of a water supply reservoir during critical periods has been presented in the literature that incorporates these performance indicators. An improved formulation of this model that represents resilience more completely is discussed herein. In addition, a set of constraints with binary integer variables are included to account for reservoir spills. The improvements achieved with the modified model is demonstrated using the same example as presented with the original model.
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TL;DR: In this paper, the authors acknowledge the publisher in granting permission for making post-print version available in open access institutional repository and provide a postprint version of the postprint manuscript.
Abstract: The authors acknowledge the publisher in granting permission for making post-print
version available in open access institutional repository.
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TL;DR: In this paper, three criteria for evaluating the performance of water resource systems are discussed, i.e., reliability, resilience, and vulnerability, which describe how likely a system is to fail, how quickly it recovers from failure, and how severe the consequences of failure may be.
Abstract: Three criteria for evaluating the possible performance of water resource systems are discussed. These measures describe how likely a system is to fail (reliability), how quickly it recovers from failure (resiliency), and how severe the consequences of failure may be (vulnerability). These criteria can be used to assist in the evaluation and selection of alternative design and operating policies for a wide variety of water resource projects. The performance of a water supply reservoir with a variety of operating policies illustrates their use.
1,458 citations
TL;DR: In this paper, a linear decision rule is proposed to specify the release during any period of reservoir operation as the difference between the storage at the beginning of the period and a decision parameter for the period.
Abstract: With the aid of a linear decision rule, reservoir management and design problems often can be formulated as easily solved linear programing problems. The linear decision rule specifies the release during any period of reservoir operation as the difference between the storage at the beginning of the period and a decision parameter for the period. The decision parameters for the entire study horizon are determined by solving the linear programing problem. Problems may be formulated in either the deterministic or the stochastic environment.
290 citations
TL;DR: In this article, the tradeoffs between reliability, vulnerability, and resilience were examined using multiobjective mixed-integer, linear programming, and it was found that as reliability is increased or as the maximum length of consecutive shortfalls decreases (resilience increases), the vulnerability of the water system to larger deficits increases.
Abstract: Reliability in water supply reservoir operation is commonly thought of as the probability of failing to achieve some target release. Here we explore two additional proposed descriptions of reservoir performance: the maximum shortfall from the target (system vulnerability) and the maximum number of consecutive periods of deficit during a record (system resilience). The larger the maximum shortfall, the greater the vulnerability. The shorter the maximum length of deficits, the more resilient the system. Using multiobjective mixed-integer, linear programming, the tradeoffs between reliability, vulnerability, and resilience are examined. It is found that as reliability is increased or as the maximum length of consecutive shortfalls decreases (resilience increases), the vulnerability of the water system to larger deficits increases.
267 citations
TL;DR: In this article, a polytope search algorithm using a combination of simulation and optimization is compared to an iterative mixed integer programming method to determine the parameters of continuous demand management rules.
Abstract: Demand-management policy rules are sought during drought and impending drought for a water system consisting of a reservoir dedicated only to water supply. The creation of such rules requires solution of a nonlinear, nonseparable mathematical programming problem. A polytope search algorithm using a combination of simulation and optimization is compared to an iterative mixed integer programming method to determine the parameters of continuous demand management rules. The signal used for calling rationing is a trigger volume given in terms of months of demand (as a volume) that are needed in storage. When the sum of actual storage plus anticipated inflow is less than the trigger volume, rationing is initiated. The extent of rationing or demand reduction that is required is determined by the ration of the sum of storage plus inflow to the trigger volume. The two methodologies for parameter determination are compared using as a criteria the maximum shortage that occurs over some planning period.
145 citations
TL;DR: A mixed integer programming model is constructed for the operation of a single water supply reservoir during drought and impending drought and determines trigger volumes of storage plus anticipated inflow which signal the need for each of the several phases of rationing.
113 citations