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Planning and Operations of Multi-Objective River and Reservoir Systems

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Resources Management, Policy and Governance".

Deadline for manuscript submissions: closed (31 December 2017) | Viewed by 41692

Special Issue Editor


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Guest Editor
Department of Water Resources and Environmental Engineering, Tamkang University, Tamsui, Taiwan
Interests: artificial neural networks; genetic algorithms; data mining; flood forecasting; hydrosystems; reservoir operation; urban hydrology
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Special Issue Information

Dear Colleagues,

Climate variability and change affect the occurrence of extreme hydrological events. Extreme weather and climate events pose serious threats to water and environmental resources management in many regions of the world. River basins are influenced by multiple factors that affect ecological and socio-hydrological systems. These systems operate on different spatial and temporal scales, often with high dynamics. Successful planning and operations of river and reservoir systems require an integrative understanding of coupled human and natural systems for generating scientifically sound, economically-efficient and socially-acceptable and sustainable solutions. To overcome the significant challenges in the planning and operations of multi-objective river and reservoir systems, cutting-edge knowledge, innovative approaches and an in-depth understanding of the inherent scientific, economic, social and environmental issues is imperative. This Special Issue of Water provides the platform for researchers and practitioners to contribute the wide knowledge and best practices for strengthening the management of our precious water resources and to present the advances in water resources systems analysis, planning and management for water resource allocation, conflict resolution, water governance, and sustainable development in a changing world. Papers in the Special Issue will highlight research that addresses processes and innovative concepts and methodologies, strategies, tools, big data application and empirical studies and/or case studies that are relevant to planning and operations of multi-objective river and reservoir systems.

Prof. Li-Chiu Chang
Guest Editor

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Keywords

  • Multi-Objective

  • Rivers

  • Reservoir Systems

  • Simulation and Optimization

  • Artificial Intelligent Techniques

  • Systems Analysis

  • Risk Analysis

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Published Papers (7 papers)

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Research

13 pages, 5176 KiB  
Article
Reflection Phenomena in Underground Pumped Storage Reservoirs
by Elena Pummer and Holger Schüttrumpf
Water 2018, 10(4), 504; https://doi.org/10.3390/w10040504 - 19 Apr 2018
Cited by 19 | Viewed by 4878
Abstract
Energy storage through hydropower leads to free surface water waves in the connected reservoirs. The reason for this is the movement of water between reservoirs at different elevations, which is necessary for electrical energy storage. Currently, the expansion of renewable energies requires the [...] Read more.
Energy storage through hydropower leads to free surface water waves in the connected reservoirs. The reason for this is the movement of water between reservoirs at different elevations, which is necessary for electrical energy storage. Currently, the expansion of renewable energies requires the development of fast and flexible energy storage systems, of which classical pumped storage plants are the only technically proven and cost-effective technology and are the most used. Instead of classical pumped storage plants, where reservoirs are located on the surface, underground pumped storage plants with subsurface reservoirs could be an alternative. They are independent of topography and have a low surface area requirement. This can be a great advantage for energy storage expansion in case of environmental issues, residents’ concerns and an unusable terrain surface. However, the reservoirs of underground pumped storage plants differ in design from classical ones for stability and space reasons. The hydraulic design is essential to ensure their satisfactory hydraulic performance. The paper presents a hybrid model study, which is defined here as a combination of physical and numerical modelling to use the advantages and to compensate for the disadvantages of the respective methods. It shows the analysis of waves in ventilated underground reservoir systems with a great length to height ratio, considering new operational aspects from energy supply systems with a great percentage of renewable energies. The multifaceted and narrow design of the reservoirs leads to complex free surface flows; for example, undular and breaking bores arise. The results show excessive wave heights through wave reflections, caused by the impermeable reservoir boundaries. Hence, their knowledge is essential for a successful operational and constructive design of the reservoirs. Full article
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22 pages, 2591 KiB  
Article
NN-Based Implicit Stochastic Optimization of Multi-Reservoir Systems Management
by Matteo Sangiorgio and Giorgio Guariso
Water 2018, 10(3), 303; https://doi.org/10.3390/w10030303 - 10 Mar 2018
Cited by 30 | Viewed by 10708
Abstract
Multi-reservoir systems management is complex because of the uncertainty on future events and the variety of purposes, usually conflicting, of the involved actors. An efficient management of these systems can help improving resource allocation, preventing political crisis and reducing the conflicts between the [...] Read more.
Multi-reservoir systems management is complex because of the uncertainty on future events and the variety of purposes, usually conflicting, of the involved actors. An efficient management of these systems can help improving resource allocation, preventing political crisis and reducing the conflicts between the stakeholders. Bellman stochastic dynamic programming (SDP) is the most famous among the many proposed approaches to solve this optimal control problem. Unfortunately, SDP is affected by the curse of dimensionality: computational effort increases exponentially with the complexity of the considered system (i.e., number of reservoirs), and the problem rapidly becomes intractable. This paper proposes an implicit stochastic optimization approach for the solution of the reservoir management problem. The core idea is using extremely flexible functions, such as artificial neural networks (NN), for designing release rules which approximate the optimal policies obtained by an open-loop approach. These trained NNs can then be used to take decisions in real time. The approach thus requires a sufficiently long series of historical or synthetic inflows, and the definition of a compromise solution to be approximated. This work analyzes with particular emphasis the importance of the information which represents the input of the control laws, investigating the effects of different degrees of completeness. The methodology is applied to the Nile River basin considering the main management objectives (minimization of the irrigation water deficit and maximization of the hydropower production), but can be easily adopted also in other cases. Full article
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23 pages, 5390 KiB  
Article
Parameter Estimation of Water Quality Models Using an Improved Multi-Objective Particle Swarm Optimization
by Yulin Wang, Zulin Hua and Liang Wang
Water 2018, 10(1), 32; https://doi.org/10.3390/w10010032 - 3 Jan 2018
Cited by 13 | Viewed by 6030
Abstract
Water quality models are of great importance for developing policies to control water pollution, with the model parameters playing a decisive role in the simulation results. It is necessary to introduce estimation through multi-objective parameters, which is often affected by noise in the [...] Read more.
Water quality models are of great importance for developing policies to control water pollution, with the model parameters playing a decisive role in the simulation results. It is necessary to introduce estimation through multi-objective parameters, which is often affected by noise in the data, into water quality models. This paper presents a multi-objective particle swarm optimization algorithm, which is based on the Mahalanobis distance operation, mechanism of cardinality preference and advection-diffusion operator. The Mahalanobis distance operation can effectively reduce the influence of noise in the data on model calibration. The mechanism of cardinality preference and the use of the advection-diffusion operator can prevent non-dominated solutions from falling into the local optimum. Four cases were used to test the proposed approach. The first two cases with true Pareto fronts show that this approach can accurately estimate the true Pareto front with a good distribution, even in the presence of noise. Furthermore, the application of the approach was tested by the O’Connor model and Crops of Engineers Integrated Compartment Water Quality Model. We show that our approach can produce satisfactory results for the multi-objective calibration of complex water quality models. In general, the proposed approach can provide accurate and efficient parameter estimation in water quality models. Full article
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2582 KiB  
Article
Studying Operation Rules of Cascade Reservoirs Based on Multi-Dimensional Dynamics Programming
by Zhiqiang Jiang, Hui Qin, Wenjie Wu and Yaqi Qiao
Water 2018, 10(1), 20; https://doi.org/10.3390/w10010020 - 27 Dec 2017
Cited by 19 | Viewed by 4150
Abstract
Although many optimization models and methods are applied to the optimization of reservoir operation at present, the optimal operation decision that is made through these models and methods is just a retrospective review. Due to the limitation of hydrological prediction accuracy, it is [...] Read more.
Although many optimization models and methods are applied to the optimization of reservoir operation at present, the optimal operation decision that is made through these models and methods is just a retrospective review. Due to the limitation of hydrological prediction accuracy, it is practical and feasible to obtain the suboptimal or satisfactory solution by the established operation rules in the actual reservoir operation, especially for the mid- and long-term operation. In order to obtain the optimized sample data with global optimality; and make the extracted operation rules more reasonable and reliable, this paper presents the multi-dimensional dynamic programming model of the optimal joint operation of cascade reservoirs and provides the corresponding recursive equation and the specific solving steps. Taking Li Xianjiang cascade reservoirs as a case study, seven uncertain problems in the whole operation period of the cascade reservoirs are summarized after a detailed analysis to the obtained optimal sample data, and two sub-models are put forward to solve these uncertain problems. Finally, by dividing the whole operation period into four characteristic sections, this paper extracts the operation rules of each reservoir for each section respectively. When compared the simulation results of the extracted operation rules with the conventional joint operation method; the result indicates that the power generation of the obtained rules has a certain degree of improvement both in inspection years and typical years (i.e., wet year; normal year and dry year). So, the rationality and effectiveness of the extracted operation rules are verified by the comparative analysis. Full article
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1418 KiB  
Article
A Multi-Dimensional Equilibrium Allocation Model of Water Resources Based on a Groundwater Multiple Loop Iteration Technique
by Ting Wang, Guohua Fang, Xinmin Xie, Yu Liu and Zhenzhen Ma
Water 2017, 9(9), 718; https://doi.org/10.3390/w9090718 - 19 Sep 2017
Cited by 7 | Viewed by 4850
Abstract
In this paper, a multi-dimensional equilibrium allocation model of water resources was developed based on the groundwater multiple loop iteration technique. The proposed model is an integrated framework of three modules respectively corresponding to the input layer, operation layer, and feedback layer in [...] Read more.
In this paper, a multi-dimensional equilibrium allocation model of water resources was developed based on the groundwater multiple loop iteration technique. The proposed model is an integrated framework of three modules respectively corresponding to the input layer, operation layer, and feedback layer in the allocation process. Firstly, a prediction model integrating the genetic algorithm-back propagation (GA-BP) model, the general regression neural network (GRNN) model, and the support vector machine (SVM) model was built to predict the future reservoir runoff, and the results were entered into the database of an optimal allocation model. Furthermore, taking exploitable groundwater as the feedback factor, the water resource optimal allocation model was continuously optimized. Also, the groundwater multiple loop iteration technique was applied to the feedback process. The proposed model was successfully applied to a typical region in Jinan, Eastern China. The uncertainties of future reservoir runoff and exploitable groundwater were taken into account. The results revealed that groundwater represented 36.6% of water supply in the base year, indicating that it is the main water source in Jinan. However, the amount of groundwater mining was decreased after considering the exploitable groundwater. The developed framework provides a comprehensive approach towards optimal future allocation of water resources, especially for the regions with overexploited groundwater. Full article
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2882 KiB  
Article
Two Dimension Reduction Methods for Multi-Dimensional Dynamic Programming and Its Application in Cascade Reservoirs Operation Optimization
by Zhiqiang Jiang, Hui Qin, Changming Ji, Zhongkai Feng and Jianzhong Zhou
Water 2017, 9(9), 634; https://doi.org/10.3390/w9090634 - 24 Aug 2017
Cited by 51 | Viewed by 5595
Abstract
An efficient reservoir operation technique plays a very important role in improving the water resources and energy efficiency of reservoirs. In order to effectively avoid or alleviate the “curse of dimensionality” of Multi-dimensional Dynamic Programming (MDP) in the application of cascade reservoirs operation [...] Read more.
An efficient reservoir operation technique plays a very important role in improving the water resources and energy efficiency of reservoirs. In order to effectively avoid or alleviate the “curse of dimensionality” of Multi-dimensional Dynamic Programming (MDP) in the application of cascade reservoirs operation optimization (CROO) and keep a global convergence at the same time, two dimension reduction methods are proposed in this paper. One is a hybrid algorithm of MDP and a Progressive Optimality Algorithm (POA), named MDP-POA, which combines the global convergence of MDP and the strong local search ability of POA. MDP-POA first takes the global optimal trajectory of MDP in a low discrete degree as the initial trajectory of the POA, and then implements further optimization to the obtained initial trajectory by the POA with a high discrete degree, so as to avoid the “curse of dimensionality” of MDP in high discrete degree and the dependency of the POA for the initial trajectory. The other is an improved MDP (IMDP), which first constructs a corridor by the optimal trajectory of MDP in a lower discrete degree, and then implements further optimization in the corridor by MDP with a relatively high discrete degree, so as to avoid a large number of unnecessary calculations, and shorten the run-time effectively. In a case study, the results of MDP-POA, IMDP, and MDP are compared and analyzed from the aspects of power generation and run-time. The analysis indicates that the proposed MDP-POA and IMDP both have a good application effect and are worthy of further promotion. Full article
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2037 KiB  
Article
Simulation and Regulation of Market Operation in Hydro-Dominated Environment: The Yunnan Case
by Fu Chen, Benxi Liu, Chuntian Cheng and Ali Mirchi
Water 2017, 9(8), 623; https://doi.org/10.3390/w9080623 - 20 Aug 2017
Cited by 15 | Viewed by 4538
Abstract
This paper presents an integrated method to obtain optimal market operation and regulation with the objective of reducing the market price and increasing the electricity consumption in hydro-dominated electricity markets, in which giant cascaded hydropower facilities along different rivers are main power suppliers. [...] Read more.
This paper presents an integrated method to obtain optimal market operation and regulation with the objective of reducing the market price and increasing the electricity consumption in hydro-dominated electricity markets, in which giant cascaded hydropower facilities along different rivers are main power suppliers. To this end, a comprehensive indicator composed of market prices and electricity consumption is proposed to evaluate the situation of hydro-dominated market operation. Moreover, an iterative algorithm is proposed to investigate the strategic behaviors of power suppliers and to simulate the operation of the market. Furthermore, an integrated solution methodology based on a multi-core parallel tabu genetic algorithm (MPTGA) is proposed to provide the optimal assignment of bilateral contracts, considering the market simulation, in order to achieve the optimal market regulation. The results from the case study, with real data based on Yunnan’s electricity market, demonstrate that the proposed indicator and method are effective and efficient to simulate and regulate the market operation, and the effects of MPTGA are discussed last. Full article
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