Water Supply for Power in Texas‐Gulf Region

Hobbs, Benjamin F.

doi:10.1061/(asce)0733-9496(1984)110:4(373)

Cited by 3 publications

(2 citation statements)

References 21 publications

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“…The model we analyze is a nonlinear program (NLP) extracted from a model of power plant water supply and use in the Texas-Gulf region [Hobbs, 1984]. The NLP is a simplified representation of water supplies and conservation options available to electric utilities in the Brazos River basin of Texas during the year 2000.…”

Section: Mathematical Programing Examplementioning

confidence: 99%

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Is optimization optimistically biased?

Hobbs¹,

Hepenstal²

1989

Water Resources Research

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Does optimization systematically lead to solutions that appear better than they actually turn out to be when implemented? The answer can be yes if there are errors in estimating objective function coefficients. Even if such errors are unbiased, the calculated value of the objective function for the optimal solution will, in an expected value sense, overstate that solution's true performance. This presupposes that errors in the constraint set are relatively unimportant. The existence of such a bias is shown by proof; Monte Carlo simulations of two realistic water resources optimization problems show its significance for water planners. The most important implication is that the estimated net benefits of model solutions may be exaggerated compared to existing water systems, whose performance is generally known with more accuracy. 221-222]:most would agree that applications of modeling designed to i•l• or aid decision-makers should only rarely, if at all, be designed to provide actual decisions regarding often complex management or policy problems the model output serves only to focus the debate about what to do; it is not itself a substitute for the planning, managing, or policy making process.Model solutions are just one of many inputs to the decision process. Solutions are modified to reflect institutional considerations and are often subjected to extensive simulation. Or optimization may be used just to screen out obviously inferior solutions. Optimization can also yield insights into the workings of the system, the critical issues, and the general form of good solutions.In this paper, we focus on the use of optimization to predict the performance of alternative designs, operating rules, and government policies. We address the following question, Do estimation errors in objective function coefficients cause optimization to have a fundamental bias toward optimism? Specifically, will such errors lead us to expect to gain more than we really will when we implement the optimal solution? Below, we show that under certain circumstances, the answer is yes. 152HOBBS AND HEPENSTAL: IS OPTIMIZATION OPTIMISTICALLY BIASED? 153 HoBBs AND HEPENSTAL: IS OPTIMIZATION OPTIMISTICALLY BIASED. 9 edited by M. A. H. Dempster, pp. 245-262, Academic, San Diego, Calif., 1980.

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Section: Mathematical Programing Examplementioning

confidence: 99%

“…The true values of the 35 objective function coefficients are assumed to be those used in the work by Hobbs [1984]. The assumed errors are lognormal, with standard deviations equal to 40% of their respective true parameters.…”

Section: Mathematical Programing Examplementioning

confidence: 99%

Is optimization optimistically biased?

Hobbs¹,

Hepenstal²

1989

Water Resources Research

Self Cite

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Allocation of Augmented Water Supply Under a Priority Water Rights System

Graham¹,

Labadie²,

Hutchison³

et al. 1986

Water Resources Research

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A generalized network flow model has been developed to simulate the allocation of additional water supplies in a river basin with observance of the prior appropriation doctrine of water rights and other legal requirements such as interstate compact agreements. The computer model, called MODSIMR, is capable of simulating complex river basin morphology while incorporating a relational data base management system for efficiently accessing prioritized water rights. Program MODSIMR is a generalized model designed to be applicable to a wide variety of river basins operating under an appropriative water rights system. As a demonstration of its usage, MODSIMR was applied to the Rio Grande Basin of Colorado, New Mexico, and Texas for predicting allocation and use of increased runoff from simulated silvicultural activities on the Rio Grande National Forest. Results indicate that under the current institutional framework, increased runoff would primarily be allocated to agricultural users in Colorado. Computer results also showed the potential value to Colorado of the Closed Basin Project in the San Luis Valley and the possibility of determining optimal pumping schemes for the Project using MODSIMR. Program MODSIMR will be useful in future economic studies to determine the benefits of the augmented water supply under various water use scenarios.

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Drought and Power Production

Palmer¹,

Lund²

1986

J. Water Resour. Plann. Manage.

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Water Supply for Power in Texas‐Gulf Region

Cited by 3 publications

References 21 publications

Is optimization optimistically biased?

Is optimization optimistically biased?

Allocation of Augmented Water Supply Under a Priority Water Rights System

Drought and Power Production

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