Practical Estimation of Inflows into Multireservoir System

Peng, Cheng-shuang; Buras, Nathan

doi:10.1061/(asce)0733-9496(2000)126:5(331)

Cited by 19 publications

(7 citation statements)

References 1 publication

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“…Unlike traditional single-objective optimization problems, multi-objective optimization problems involve multiple conflicting objective functions, which cannot be simply transformed into the form of a single objective function. Therefore, traditional single-objective optimization algorithms, such as linear programming [24] and nonlinear programming [25], cannot be directly applied to multi-objective solving. Instead, multi-objective problems need to be transformed into single-objective problems for processing using objective weighting, which will increase the subjectivity of model optimization.…”

Section: Introductionmentioning

confidence: 99%

Research on the Carbon Reduction Technology Path of the Iron and Steel Industry Based on a Multi-Objective Genetic Algorithm

Xie,

Ma,

Wang

et al. 2024

Sustainability

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This paper establishes a multi-objective optimization model based on an improved NSGA-II algorithm, aiming to study the carbon reduction technology path of specific enterprises in the steel industry under the background of China’s dual-carbon goal and fill the research gap in the carbon reduction technology path of steel enterprises, which has certain guiding significance for the realization of China’s dual-carbon goal and the low-carbon development of steel enterprises. Firstly, through the analysis of the list of extreme energy efficiency technologies in the steel industry and the main process flow of steel industry production, the multi-objective optimization model is constructed from the two objective dimensions of maximum CO2 emission reduction and maximum enterprise economic benefit. Then the improved NSGA-II algorithm is used to solve the model. And the empirical analysis of a Hebei iron and steel enterprise, based on the technology application of enterprises before the release of the technology list, the technology path of enterprises to reduce carbon is predicted. The actual application data of the enterprise is used for verification and analysis, and suggestions on the technical path for the future low-carbon development of the enterprise are provided. The experimental results show that: (1) The optimal solution set of Pareto is consistent with the practical application of enterprises, and the constructed model is accurate and efficient, which can be used for the research of carbon reduction technology path. (2) When introducing technology, enterprises can give priority to the solution of common set technology based on their own needs.

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Section: Introductionmentioning

confidence: 99%

Research on the Carbon Reduction Technology Path of the Iron and Steel Industry Based on a Multi-Objective Genetic Algorithm

Xie,

Ma,

Wang

et al. 2024

Sustainability

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“…Even if some efforts have been made in using satellite data and radar data to implement reservoir inflow estimates [11][12][13][14] there is still need to invest more money into field survey data and more ground truth measurements. Knowing these limitations, the field of hydrology has begun to shift more emphasis toward large scale hydrologic modelling [15][16][17][18][19], which can take advantage of remote sensing estimates for unmeasured quantities.…”

Section: Introductionmentioning

confidence: 99%

General Assessment of the Operational Utility of National Water Model Reservoir Inflows for the Bureau of Reclamation Facilities

Viterbo

Read

Nowak

et al. 2020

Water

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This work investigates the utility of the National Oceanic and Atmospheric Administration’s National Water Model (NWM) for water management operations by assessing the total inflow into a select number of reservoirs across the Central and Western U.S. Total inflow is generally an unmeasured quantity, though critically important for anticipating both floods and shortages in supply over a short-term (hourly) to sub-seasonal (monthly) time horizon. The NWM offers such information at over 5000 reservoirs across the U.S., however, its skill at representing inflow processes is largely unknown. The goal of this work is to understand the drivers for both well performing and poor performing NWM inflows such that managers can get a sense of the capability of NWM to capture natural hydrologic processes and in some cases, the effects of upstream management. We analyzed the inflows for a subset of Bureau of Reclamation (BoR) reservoirs within the NWM over the long-term simulations (retrospectively, seven years) and for short, medium and long-range operational forecast cycles over a one-year period. We utilize ancillary reservoir characteristics (e.g., physical and operational) to explain variation in inflow performance across the selected reservoirs. In general, we find that NWM inflows in snow-driven basins outperform those in rain-driven, and that assimilated basin area, upstream management, and calibrated basin area all influence the NWM’s ability to reproduce daily reservoir inflows. The final outcome of this work proposes a framework for how the NWM reservoir inflows can be useful for reservoir management, linking reservoir purposes with the forecast cycles and retrospective simulations.

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“…The optimization techniques for solving the problem of reservoir optimal operation are experiencing a process from classical to intelligent. Classical optimization methods include those of dynamic programming (DP) [6], large-scale system analysis [8], linear programming (LP) [9], and non-linear programming (NLP) [10], as well as those of discrete differential dynamic programming (DDDP) [11], dynamic programming with successive approximation (DPSA) [12], and progressive optimality algorithm (POA) [13]. With the development of computer technology, intelligent algorithms have developed rapidly.…”

Section: Introductionmentioning

confidence: 99%

Integrated Software Development and Case Studies for Optimal Operation of Cascade Reservoir within the Environmental Flow Constraints

Fang

Liao

et al. 2020

Sustainability

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Reservoir optimal operation considering aquatic ecological protection is a hot topic in current research. This paper proposes an improved minimum monthly average runoff method (IMMR) for calculating environmental flow and an improved invasive weed optimization algorithm (IIWO) for optimizing complex problems. An integrated software consists of three modules, which is developed in this paper, i.e., IIWO convergence test module, environmental flow calculation module, and cascade reservoir operation module. Three test functions are included in the IIWO convergence test module. The minimum monthly average runoff method (MMR), IMMR, Tennant Method, Q90, and Q95 are included in the environmental flow calculation module. The IIWO and invasive weed optimization algorithm (IWO) are included in the cascade reservoir operation module. Wujiang River Basin in China is studied as a case in this paper. The results show that the environmental flow of cascade reservoir calculated by IMMR is 1871 m3/s, the maximum and the minimum are calculated by T-O and T-M, respectively. The power generation of cascade reservoir calculated by IWO is less than IIWO. The conclusions that IIWO has better convergence than IWO in solving cascade reservoir model, and the water volume of environmental flow has no obvious influence on cascade reservoir operation are drawn.

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Practical Estimation of Inflows into Multireservoir System

Cited by 19 publications

References 1 publication

Research on the Carbon Reduction Technology Path of the Iron and Steel Industry Based on a Multi-Objective Genetic Algorithm

Research on the Carbon Reduction Technology Path of the Iron and Steel Industry Based on a Multi-Objective Genetic Algorithm

General Assessment of the Operational Utility of National Water Model Reservoir Inflows for the Bureau of Reclamation Facilities

Integrated Software Development and Case Studies for Optimal Operation of Cascade Reservoir within the Environmental Flow Constraints

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