Optimal Reservoir Operation Under Inflow Uncertainty
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Optimal Reservoir Operation Under Inflow Uncertainty
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Author : Jinshu Li
language : en
Publisher:
Release Date : 2021
Optimal Reservoir Operation Under Inflow Uncertainty written by Jinshu Li and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Stochastic programming is a mathematical model used to resolve the uncertainty of random variables in optimization problems. In reservoir management and operation, the reservoir inflow is typically regarded as a random variable as it brings most of the operation uncertainty. Although stochastic programming has been successfully applied to many reservoir managements cases, the pursuit of the improvement on its accuracy, efficiency, and applicability never ceases. This dissertation consists of five chapters. The first introductory presents the classical stochastic model and describes the challenges. Then, the second chapter develops a statistical model that focuses on improving the distribution fitting accuracy for the monthly average inflow as the random variable. The third chapter discusses a method aiming at streamflow scenario tree reduction, which is essential for alleviating the computational burden of a two-stage stochastic programming with recourse model. The fourth chapter expands the applicability of stochastic programming model, by introducing a multi-objective, multi-stage stochastic programming with recourse model. The final chapter offers conclusions, discussions, and potential future research opportunities.
Multi Objective Optimization Of Reservoir Operation Under Uncertainty With Robust And Flexible Decision Variables
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Author : Parnian Hosseini
language : en
Publisher:
Release Date : 2017
Multi Objective Optimization Of Reservoir Operation Under Uncertainty With Robust And Flexible Decision Variables written by Parnian Hosseini and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Franklin D. Roosevelt Lake (Wash.) categories.
Optimization of reservoir operation is involves various competing objectives for a scarce resource (water). To find the optimal operation of reservoirs, it is essential to consider multiple objectives simultaneously. There are various sources of uncertainty associated with the reservoir operation problem that should be considered as well. The overarching goal of this research is to develop a framework for finding flexible and reliable solutions to the reservoir operation problem with competing objectives. Because some sources of uncertainty are not well quantified, providing flexible decision variables lets the decision maker choose accordingly from a range of options knowing that all the flexible decision variables are feasible with a specified probability of failure and that are relatively optimal. To accomplish this goal, each flexible decision variable is represented by a random variable within a specific range instead of a single deterministic decision variable. An additional objective is added to the optimization problem, in order to maximize the flexibility of decision variables. The proposed methodology is tested for two mathematical test problems and the operation of the Grand Coulee reservoir, which is located on the Columbia River in the Northwestern United States. The Stochastic Collocation (SC) method is used to sample the random variables and approximate the expected values of the objectives. For the Grand Coulee reservoir, the decision variables are the daily turbine outflows. The first objective of the optimization is to minimize the forebay elevation deviation at the end of the optimization period. The second objective is to maximize the revenue from the hydropower production. The results show that the proposed methodology could find some flexible decision variables with 45% coefficient of variation. The corresponding expected objectives have less than 20% deterioration from the deterministic Pareto solutions. However, the number of function evaluations increases exponentially with the number of decision variables. Therefore, this methodology is suggested for problems with a few decision variables. For finding flexible decision variables in problems with many decision variables, a dimension reduction method called Karhunen Loeve (KL) expansion is implemented in the optimization problem. By extracting useful information from the decision variables, the decision space can be represented with merely a few random variables using a set of deterministic decision variables. The results show that three random variables are sufficient to generate decision variable realizations which have mean and variance less than 1% and 5% different from the original decision variable realizations, respectively. The proposed methodology is capable of efficiently finding flexible decision variables that lead to expected objective values close to the Pareto deterministic solutions. To force the generated decision variable realizations to stay within the feasible bounds and therefore reduce the number of constraints that need to be checked, the data is transformed to be within bounds first, and then the KL-expansion is performed. Using the transformed data decreases the computational time but the decrease in computational time is not significant. The inflow uncertainty is also considered as the only source of input uncertainty. Forecast inflow ensembles can be used as the source of inflow uncertainty. However in this study due to lack of information, historical inflows are used instead. The inflow uncertainties are represented using the KL-expansion. Robust optimization is performed by optimizing the weighted sum of the expectation and standard deviation of the objective due to uncertain inflows. The weights in the robust objective formulation can be changed based on the decision maker’s preference of robustness versus performance. Finally, the combined framework to find robust and flexible decision variables is tested on a reservoir operation problem and the results were compared to the deterministic case.
Reliability Of Reservoir Operation Under Hydrologic Uncertainty
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Author : Han-Lin Lee
language : en
Publisher:
Release Date : 1987
Reliability Of Reservoir Operation Under Hydrologic Uncertainty written by Han-Lin Lee and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with Hydraulic structures categories.
Uncertainty In Optimization Of Multi Reservoir Hydroelectric Systems
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Author : Nazanin Shabani
language : en
Publisher: LAP Lambert Academic Publishing
Release Date : 2011-09-01
Uncertainty In Optimization Of Multi Reservoir Hydroelectric Systems written by Nazanin Shabani and has been published by LAP Lambert Academic Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-01 with categories.
The main objective of reservoir operation planning is to determine the amount of water released from a reservoir and the amount of energy traded in each time step to make the best use of available resources. This is done by evaluating the trade-off between the immediate and the future profit of power generation while meeting a set of constraints such as the continuity equations, transmission limits, generation and reservoir limits, flood control limits and load resource balance. Another important issue in these problems is uncertainty coming from spatial and temporal variability, inherent nature of a problem or parameter, errors in measurement due to human or technology inaccuracy and modeling errors. This research implements a Reinforcement Learning (RL) optimization algorithm to incorporate flood control constraints of the Columbia River Treaty. It considers the main sources of uncertainty in operating a large scale hydropower system: market prices and inflows by using a number of scenarios of historical data on inflow and energy prices in the learning process. The RL method reduces the time and computational effort needed to solve the operational planning problem.
Nested Algorithms For Optimal Reservoir Operation And Their Embedding In A Decision Support Platform
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Author : Blagoj Delipetrev
language : en
Publisher: CRC Press
Release Date : 2020-04-30
Nested Algorithms For Optimal Reservoir Operation And Their Embedding In A Decision Support Platform written by Blagoj Delipetrev and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-30 with Mathematics categories.
Reservoir operation is a multi-objective optimization problem, and is traditionally solved with dynamic programming (DP) and stochastic dynamic programming (SDP) algorithms. The thesis presents novel algorithms for optimal reservoir operation, named nested DP (nDP), nested SDP (nSDP), nested reinforcement learning (nRL) and their multi-objective (MO) variants, correspondingly MOnDP, MOnSDP and MOnRL. The idea is to include a nested optimization algorithm into each state transition, which reduces the initial problem dimension and alleviates the curse of dimensionality. These algorithms can solve multi-objective optimization problems, without significantly increasing the algorithm complexity or the computational expenses. It can additionally handle dense and irregular variable discretization. All algorithms are coded in Java and were tested on the case study of the Knezevo reservoir in the Republic of Macedonia. Nested optimization algorithms are embedded in a cloud application platform for water resources modeling and optimization. The platform is available 24/7, accessible from everywhere, scalable, distributed, interoperable, and it creates a real-time multiuser collaboration platform. This thesis contributes with new and more powerful algorithms for an optimal reservoir operation and cloud application platform. All source codes are available for public use and can be used by researchers and practitioners to further advance the mentioned areas.
Planning Hydropower Production Of Small Reservoirs Under Resources And System Knowledge Uncertainty
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Author : Divas Karimanzira
language : en
Publisher:
Release Date : 2017
Planning Hydropower Production Of Small Reservoirs Under Resources And System Knowledge Uncertainty written by Divas Karimanzira and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Technology categories.
Available energy from water varies widely from season to season, depending on precipitation and streamflows, especially in small catchments. In addition, the reservoir operation problem is associated with the inability of operators to formulate crisp boundary conditions, due to uncertainty in knowledge. In this chapter, an approach for planning the operation of small multipurpose reservoir systems for hydropower generation and flood control under consideration of the stochastic nature of inflows and initial storage levels and allowed formulation of constraints with some range of uncertainty will be presented. The approach is based on joint chance constrained and fuzzy programming, which addresses the problem of including risk directly in the optimization. Therefore, the stochastic nature of inputs is incorporated directly in the model through the use of convolution of random variables. Furthermore, probabilistic/vague constraints and preassigned tolerance levels are used to transform the stochastic optimization problem into its deterministic equivalent. The approach searches for a control strategy, which maximizes the benefits acquired from hydropower generation and minimizes the economic losses incurred due to not meeting the required reliability levels from the various purposes served by the reservoir system. Besides the optimal reservoir release strategy, this approach also determines the optimal reliabilities of satisfying hydropower demand and flood control storage requirements. Therefore, this tool has some advantages in planning the operations of reservoirs in extreme hydrological events such as floods and droughts. The system is applied to the Wuyang small hydropower plants cascade in the People's Republic of China.
Hydrological Dimensioning And Operation Of Reservoirs
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Author : I.V. Nagy
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Hydrological Dimensioning And Operation Of Reservoirs written by I.V. Nagy and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Science categories.
Storage reservoirs represent one of the most effective tools for eliminating, or at least for minimizing, discrepancies in the time and space variations of water resources distribution and requirements. In fact, the different - often contradictory - and increasing demands on water resources utilization and control usually can be fulfilled only by building multi-purpose reservoir systems. In this way, the available water resources can be exploited and/or managed in a more rational way. Typically, the construction of a dam across a river valley causes water to accumulate in a reservoir behind the dam; the volume of water accumulated in the reservoir will depend, in part, on the dimensions of the dam. The size of the dam will normally affect the capital expenditure in a very significant way. Indeed the construction of large water resource control systems - such as dams - generally involves rather huge manpower and material outlays. Consequently, the elaboration of effectual methods of approach that can be used in establishing the optimal reservoir parameters is of great practical significance. For instance, in the design and operation oflarge multi-reservoir systems, simple simulation and/or optimization models that can identify potentially cost effective and efficient system design are highly desirable. But it should be recognized that the problem of finding optimal capacities for multi-reservoir systems often becomes computationally complex because of the large number of feasible configurations that usually need to be analyzed.
Artificial Neural Network And Monte Carlo Optimization For Reservoir Operation
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Author : Stephen James Klein
language : en
Publisher:
Release Date : 1999
Artificial Neural Network And Monte Carlo Optimization For Reservoir Operation written by Stephen James Klein and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Monte Carlo method categories.
Sustainable Water Management Solutions For Large Cities
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Author : International Association of Hydrological Sciences. Scientific Assembly
language : en
Publisher:
Release Date : 2005
Sustainable Water Management Solutions For Large Cities written by International Association of Hydrological Sciences. Scientific Assembly and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Nature categories.
Advances In Water Resources Management
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Author : Lawrence K. Wang
language : en
Publisher: Springer
Release Date : 2015-12-16
Advances In Water Resources Management written by Lawrence K. Wang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-16 with Technology & Engineering categories.
This volume provides in-depth coverage of such topics as multi-reservoir system operation theory and practice, management of aquifer systems connected to streams using semi-analytical models, one-dimensional model of water quality and aquatic ecosystem-ecotoxicology in river systems, environmental and health impacts of hydraulic fracturing and shale gas, bioaugmentation for water resources protection, wastewater renovation by flotation for water pollution control, determination of receiving water’s reaeration coefficient in the presence of salinity for water quality management, sensitivity analysis for stream water quality management, river ice process, and computer-aided mathematical modeling of water properties. This critical volume will serve as a valuable reference work for advanced undergraduate and graduate students, designers of water resources systems, and scientists and researchers. The goals of the Handbook of Environmental Engineering series are: (1) to cover entire environmental fields, including air and noise pollution control, solid waste processing and resource recovery, physicochemical treatment processes, biological treatment processes, biotechnology, biosolids management, flotation technology, membrane technology, desalination technology, water resources, natural control processes, radioactive waste disposal, hazardous waste management, and thermal pollution control; and (2) to employ a multimedia approach to environmental conservation and protection since air, water, soil and energy are all interrelated.