Optimal Reservoir Storage Research Articles

Forecast-informed hydropower optimization at long and short-time scales for a multiple dam network

This study presents a scheme for co-optimizing the long-term (seasonal) reservoir operating objectives with the short-term (daily) objectives for multi-dam networks to maximize hydropower generation. Long-term optimal reservoir storage provides temporal space to optimize operation of the dams at short-term based on forecasted reservoir inflow. This study asks if there is an added benefit of co-optimization of operations at long- and short-term scales for hydropower generation. The multi-objective optimization problem at both the temporal scales was simultaneously solved considering Pareto optimality between conflicting objectives. Constraints pertaining to flood control, dam safety, and environmental flow were imposed. The proposed scheme was implemented over a network of Blue Mesa, Morrow Point, and Crystal dams in the Upper Colorado Basin. Ensemble forecast forcings from publicly available numerical weather prediction and climate models were used as inputs for the daily and monthly scale inflow forecasts. The results show improvements of 41%, 27%, and 15% in hydropower generation using the co-optimization during wet, moderate, and dry years, respectively, against a benchmark that neglects inflow forecasts. This study demonstrates added benefit of co-optimizing the operations for hydropower generation based on short- and long-term forecasted reservoir inflow. Given that most dams today operate as a network in a river basin, we recommend moving away from single dam and single time scale optimization to a multiple-dam with long- and short-term scale co-optimization-based operations to make renewable energy generation more efficient.

Derivation of Hydropower Rules for Multireservoir Systems and Its Application for Optimal Reservoir Storage Allocation

AbstractHydropower operating rules can guide reservoir release and storage for maximizing hydropower generation. The optimal hydropower operating rules are usually derived by numerical hydropower s...

Derivation of water and power operating rules for multi-reservoirs

ABSTRACTWater operating rules have been universally used to operate single reservoirs because of their practicability, but the efficiency of operating rules for multi-reservoir systems is unsatisfactory in practice. For better performance, the combination of water and power operating rules is proposed and developed in this paper. The framework of deriving operating rules for multi-reservoirs consists of three modules. First, a deterministic optimal operation module is used to determine the optimal reservoir storage strategies. Second, a fitting module is used to identify and estimate the operating rules using a multiple linear regression analysis (MLR) and artificial neural networks (ANN) approach. Last, a testing module is used to test the fitting operating rules with observed inflows. The Three Gorges and Qing River cascade reservoirs in the Changjiang River basin, China, are selected for a case study. It is shown that the combination of water and power operating rules can improve not only the assurance probability of output power, but also annual average hydropower generation when compared with designed operating rules. It is indicated that the characteristics of flood and non-flood seasons, as well as sample input (water or power), should be considered if the operating rules are developed for multi-reservoirs.EDITOR D. Koutsoyiannis ASSOCIATE EDITOR not assigned

A simplified model for reservoir operation considering the water quality issues: Application of the Young conflict resolution theory

In this study, an algorithm combining a multi-objective genetic algorithm (GA)-based optimization model and a water quality simulation model is developed for determining a trade-off curve between objectives related to the allocated water quantity and quality. To reduce the run-time of the GA-based optimization model, the main problem is decomposed to long-term and annual optimization models. The reliability of water supply is considered to be the objective function in the long-term stochastic optimization model, but the objective functions of the annual models are related to both the allocated water quantity and quality. The operating policies obtained using this long-term model provide the time series of the optimum reservoir water storages at the beginning and the end of each water year. In the next step, these optimal reservoir storage values are considered as constraints for water storage in the annual reservoir operation optimization models. The epsilon-constraint method is then used to develop a trade-off curve between the reliability of water supply and the average allocated water quality. The Young conflict resolution theory, which incorporates the existing conflicts among decision-makers and stakeholders, is used for selecting the best solution on the trade-off curve. The monthly reservoir operating rules are then calculated using an Adaptive Neuro-Fuzzy Inference System, which is trained using the optimal operating policies. The proposed model is applied to the 15-Khordad Reservoir in the central part of Iran. The results show that this simplified procedure does not reduce the accuracy of the reservoir operating policies and it can effectively reduce the computational burden of the previously developed models.

Can Reservoir Storage Be Uneconomically Large?

The effect of reservoir losses on the economically optimal use of reservoir storage capacity is explored theoretically and numerically. We demonstrate that reservoir seepage and evaporation losses lead to a trade-off between the reliability and mean level of water deliveries, and that as the price elasticity of demand increases and variability of inflows decreases, the optimal reservoir storage decreases. Corresponding reductions in the optimal maximum use of reservoir storage capacity as price elasticity of demand increases, variability of inflows decreases, and losses increase are illustrated. The approach helps clarify the role of storage in maximizing economic benefits from consumptive uses.

Optimal Water Management for Reservoir Based Irrigation Projects Using Geographic Information System

The shortage of reservoir water is the main constraint in establishing stable water management programs in the Muda Irrigation Project, Malaysia. In this study, a water balance equation was derived to evaluate the performance of the project. The water balance components were modeled without calibration, and compared with measured data, whenever possible. The overall project efficiencies for the main and off seasons were also obtained. A reservoir simulation model was developed from which simulated storage capacities compared satisfactorily with the observed storage capacities. An optimization model was also developed to solve the water resources management of the project in a computationally satisfactory manner. The optimal reservoir storage, optimal irrigation demand, and optimal reservoir release (i.e., optimal reservoir operating policy) were computed. The mean (1987–1997) optimized total water requirements for the dry and wet seasons were also computed as were the optimal contributions by rainfall, re...

Optimal Allocation of Monthly Water Withdrawals in Reservoir Systems

In this study, a water balance equation was derived and theperformance of a project was analyzed. The water balancecomponents were modeled without calibration, and compared withmeasured data, whenever possible. A reservoir simulation modelwas develop and the model storage capacities were compared withthe observed storage capacities satisfactorily. An optimizationmodel was developed to solve the water resources of a largeproject in a computationally satisfactory manner. The optimalreservoir storage, optimal irrigation demand, and optimalreservoir release were computed. The optimal mean (1987–1997)model total water requirements for the dry and wet seasons werealso computed and the optimal contributions by rainfall,reservoir, uncontrolled river flow, and recycled water weredetermined. The mean annual optimal water withdrawals from thereservoir systems were found to be 1223 MCM (Million cubicmeters). The optimal mean model total water requirements werecompared with other authors computed values for the same and asignificant water savings was achieved.

Optimal allocation of water resources in large river basins: II. Application to Yellow River Basin

In this paper, the theoretical approach presented in Part I is demonstrated by means of case study on the optimal allocation water resources for Yellow River Basin of China. The object of the case study was to find the optimization of water allocation among subregions and trunk streams of the basin in order to achieve the maximum national economic benefits and the optimal reservoir storage required to maintain the long-term balance of water resources.

Risk‐Reliability Programming for Optimal Water Quality Control

A risk‐reliability programming approach is developed for optimal allocation of releases for control of water quality downstream of a multipurpose reservoir. Additionally, the approach allows the evaluation of optimal risk/reliability values. Risk is defined as a probability of not satisfying constraints given in probabilistic form, e.g., encroachment of water quality reservation on that for flood control. The objective function includes agricultural production losses that are functions of water quality, and risk‐losses associated with encroachment of the water quality control functions on reservations for flood control, fisheries, and irrigation. The approach is demonstrated using data from New Melones Reservoir on the Stanislaus River in California. Results indicate that an optimum water quality reservation exists for a given set of quality targets and loss functions. Additional analysis is presented to determine the sensitivity of optimization results to agricultural production loss functions and the influence of statistically different river flows on the optimal reservoir storage for water quality control. Results indicate the dependence of an optimum water quality reservation on agricultural production losses and hydrologic conditions.

Single multipurpose reservoir design: a modified optimal control problem by chance-constrained programming

This paper presents a chance-constrained programming model for optimal control of a multipurpose reservoir and its modification to a model for single reservoir design. An algorithm is developed for solving complex stochastic problems of multipurpose reservoir planning and design. The complexity of the problem is resolved by a two-step algorithm: (1) transformation of chance constraints on the state and control variables is performed at the first step; and (2) the choice of optimum control or optimal reservoir storage is carried out in the second step. The method of iterative convolution is chosen for the first step, while linear programming is selected for the second step. The algorithm allows the use of random inflows and random demands together with other deterministic demands. The reservoir design problem is presented as a modified optimal control problem. The procedure is illustrated with an example of a hypothetical reservoir design problem with three different types of downstream releases (hydropower production, municipal water supply, and irrigation).

Optimization of real time operation of a multiple‐reservoir system

This paper addresses a typical requirement of real time multiple‐reservoir operation. A methodology is evolved utilizing a form of dynamic programing (DP) for the selection of an optimal reservoir storage policy path through a specified number of policy periods, and a linear programing (LP) routine is used for period by period optimization. The policy periods, in case of the real time operation, correspond to the number of time periods for which a streamflow prediction model is reasonably reliable. The method results in relatively easy computer implementation and high flexibility in that changes in constraints are simply made and additional reservoirs easily added. The method is of considerable value for the determination of release policies in real time operation of an existing system. As an example, application is made to a real system of reservoirs and hydroelectric facilities associated with the Shasta and Trinity sub‐systems of the California Central Valley Project.