The objective of this paper is to review the state-of-the-art of mathematical models developed for reservoir operations, including simulation. Algorithms and methods surveyed include linear programming (LP), dynamic programming (DP), nonliner programming (NLP), and simulation. A general overview is first presented. The historical development of each key model is critically reviewed. Conclusions and recommendations for future research are presented.

Reservoir Management and Operations Models: A State‐of‐the‐Art Review

This paper presents a survey of simulation and optimization modeling approaches used in reservoir systems operation problems. Optimization methods have been proved of much importance when used with simulation modeling and the two approaches when combined give the best results. The main objective of this review article is to discuss simulation, optimization and combined simulation–optimization modeling approach and to provide an overview of their applications reported in literature. In addition to classical optimization techniques, application and scope of computational intelligence techniques, such as, evolutionary computations, fuzzy set theory and artificial neural networks, in reservoir system operation studies are reviewed. Conclusions and suggestive remarks based on this survey are outlined, which could be helpful for future research and for system managers to decide appropriate methodology for application to their systems.

/pdf/simulation-optimization-modeling-a-survey-and-potential-1xvkgabzfk.pdf

Simulation-optimization modeling: a survey and potential application in reservoir systems operation.

This research develops a mixed integer linear programming (MILP) model that considers simultaneously both the traditional reservoir rule curves and the hedging rules to manage and operate a multipurpose, multireservoir system. During normal periods of operation, when inflows are plentiful, this optimization model efficiently distributes the available stored water from different reservoirs to meet the planned demands imposed by competing users. However, during periods of drought, or when anticipating a drought, the planned demands cannot be fully met, and a water shortage occurs. By considering the hedging rules along with the rule curves, guidelines are provided for reservoir releases. To minimize the impact of drought, the hedging rules effectively reduce the ongoing water supply to balance with the target storage requirement. The MILP model is applied to a multireservoir system in the southern region of Taiwan, where the results obtained demonstrate the applicability and utility of the model.

Optimization of Reservoir Management and Operation with Hedging Rules

Reservoir operating policies are derived to improve the operation and efficient management of available water for the Aliyar Dam in Tamil Nadu, India, using a dynamic programming (DP) model, a stochastic dynamic programming (SDP) model, and a standard operating policy (SOP). The objective function for this case study is to minimize the squared deficit of the release from the irrigation demand. From the DP algorithm, general operating policies are derived using a neural network procedure (DPN model), and using a multiple linear regression procedure (DPR model). The DP functional equation is solved for 20 years of fortnightly historic data. The field irrigation demand is computed for this study by the modified Penman method with daily meteorological data. The performance of the DPR, DPN, SDP, and SOP models are compared for three years of historic data, using the proposed objective function. The neural network procedure based on the dynamic programming algorithm provided better performance than the other mo...

Deriving a General Operating Policy for Reservoirs Using Neural Network

This paper describes the application of deterministic optimization to the main stem Missouri River reservoir system and the development and testing of inferred optimal operating rules from these model results. An implicit stochastic optimization approach is taken and tested using a simplified simulation model. This work illustrates the applicability and limitations of applying deterministic optimization to development of strategic operating rules for large-scale water resource systems. For this multipurpose multireservoir system, simple data display and simulation modeling are found to be superior to classical regression techniques for inferring and refining promising operating rules from deterministic optimization results.

Operating Rule Optimization for Missouri River Reservoir System

A single multiple-purpose reservoir is analyzed using a backward looking dynamic program algorithm to obtain optimal releases. The dynamic program is solved for both one-sided and two-sided quadratic loss functions. Monthly policies are derived by regressing the optimal set of releases on the input and state variables. Linear and nonlinear release policies are developed, then verified and compared through simulation. For a two-sided quadratic loss function, linear policies are as good or better than nonlinear policies. However, for a one-sided quadratic loss function, nonlinear policies give improved performance over linear policies. It is also illustrated that the maximum R2 criterion for selecting release policies may not always be appropriate. Hoover Reservoir, located on Big Walnut Creek in central Ohio, is used as a case example.

Derivation of monthly reservoir release policies

The problem of determining the optimal number, location, and level of treatment for regional domestic sewage treatment plants along an estuary or river is considered. The formulation is one of minimizing the sum of treatment and transport (piping and pumping) costs such that water quality improvement goals for dissolved oxygen are met. Restrictions may also be placed upon the overall level of treatment (required secondary, required uniform, or least cost) if desired. An optimization procedure is developed which utilizes dynamic programing, linear programing, and heuristic location techniques in a series of steps which lead to progressively improved (lower total cost) solutions. The location procedure is intended for use by an engineer-planner during the design stage and requires his participation and skilled judgment during the course of the algorithm. The technique is illustrated for the Delaware estuary for 22 domestic waste sources, nine potential regional sewage treatment plant sites, and 22 industrial waste sources. Results of the case study show considerable savings over previous nonregional treatment schemes.

Designing regionalized waste water treatment systems

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/WR008i006p01605

Elbert E. Whitlatch

Papers

Derivation of monthly reservoir release policies

Designing regionalized waste water treatment systems

Comments on `Mathematical programing for regional water quality management' by Glenn W. Graves, Gordon B. Hatfield, and Andrew B. Whinston