A multiobjective short‐term optimal operation model for a cascade system of reservoirs considering the impact on long‐term energy production

Xu, Bin; Zhong, Ping‐an; Stanko, Z.; Zhao, Yong; Yeh, William W.‐G.

doi:10.1002/2014wr015964

Cited by 40 publications

(19 citation statements)

References 30 publications

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“…Last, we found considerable, but predictable variation in subdaily hydrologic variation according to MOP classes. However, the vast majority of reservoir operation algorithms (including those for hydropower dams) are created on the basis on daily discharge (Yazicigil et al, 1983;Xu et al, 2015; except see Shiaul and Wu, 2013). While subdaily hydrologic variation may be irrelevant to non-hydropower dams, energy production at hydropower dams relies on operational flexibility of within-day variation (Jager and Bevelhimer, 2007), in addition to variable day-to-day or seasonal operations (Shiaul and Wu, 2013).…”

Section: Discussionmentioning

confidence: 99%

Classification of US Hydropower Dams by their Modes of Operation

et al. 2016

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A key challenge to understanding ecohydrologic responses to dam regulation is the absence of a universally transferable classification framework for how dams operate. In the present paper, we develop a classification system to organize the modes of operation (MOPs) for US hydropower dams and powerplants. To determine the full diversity of MOPs, we mined federal documents, open‐access data repositories, and internet sources. We then used CART classification trees to predict MOPs based on physical characteristics, regulation, and project generation. Finally, we evaluated how much variation MOPs explained in sub‐daily discharge patterns for stream gages downstream of hydropower dams. After reviewing information for 721 dams and 597 power plants, we developed a two‐tier hierarchical classification based on (i) the storage and control of flows to powerplants, and (ii) the presence of a diversion around the natural stream bed. This resulted in nine tier‐1 MOPs representing a continuum of operations from strictly peaking, to reregulating, to run‐of‐river, and two tier‐2 MOPs, representing diversion and integral dam‐powerhouse configurations. Although MOPs differed in physical characteristics and energy production, classification trees had low accuracies (≤62%), which suggested that accurate evaluations of MOPs may require individual attention. MOPs and dam storage explained 20% of the variation in downstream subdaily flow characteristics and showed consistent alterations in subdaily flow patterns from reference streams. This standardized classification scheme is important for future research including estimating reservoir operations for large‐scale hydrologic models and evaluating project economics, environmental impacts, and mitigation. Copyright © 2016 John Wiley & Sons, Ltd.

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Section: Discussionmentioning

confidence: 99%

Classification of US Hydropower Dams by their Modes of Operation

et al. 2016

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“…When considering multi-purpose systems, the picture becomes even more intricate as operations usually need to balance shortand long-term operating targets, e.g., flood control and water supply, (e.g., Sreekanth et al, 2012;Xu et al, 2015 ). In this case, valuable forecasts may comprise several processes with inconsistent dynamics and disparate levels of predictability.…”

Section: Introductionmentioning

confidence: 99%

Informing the operations of water reservoirs over multiple temporal scales by direct use of hydro-meteorological data

Denaro

Anghileri

Giuliani

et al. 2017

Advances in Water Resources

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Water reservoir systems may become more adaptive and reliable to external changes by enlarging the information sets used in their operations. Models and forecasts of future hydro-climatic and socio-economic conditions are traditionally used for this purpose. Nevertheless, the identification of skillful forecasts and models might be highly critical when the system comprises several processes with inconsistent dynamics (fast and slow) and disparate levels of predictability. In these contexts, the direct use of observational data, describing the current conditions of the water system, may represent a practicable and zero-cost alternative. This paper contrasts the relative contribution of state observations and perfect forecasts of future water availability in improving multipurpose water reservoirs operation over short- and long-term temporal scales. The approach is demonstrated on the snow-dominated Lake Como system, operated for flood control and water supply. The Information Selection Assessment (ISA) framework is adopted to retrieve the most relevant information to be used for conditioning the operations. By explicitly distinguishing between observational dataset and future forecasts, we quantify the relative contribution of current water system state estimates and perfect streamflow forecasts in improving the lake regulation with respect to both flood control and water supply. Results show that using the available observational data capturing slow dynamic processes, particularly the snow melting process, produces a 10% improvement in the system performance. This latter represents the lower bound of the potential improvement, which may increase to the upper limit of 40% in case skillful (perfect) long-term streamflow forecasts are used

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“…Optimal reservoir operation refers to an operation mode that uses optimization methods to formulate reservoir operation strategies [1]. Under the guidance of this operation approach, the practical short-term operation procedure of a reservoir can be generally described as follows: choose an optimization criterion to develop a corresponding objective function, and establish an optimal operation model given input data and constraints [2]; use optimization algorithms to solve the model and obtain the reservoir operation strategy that makes the objective function reach its extremum, namely the optimal operation scheme [3]; implement the scheme and obtain the reservoir's actual operation process. Compared with conventional operation, optimal operation can effectively enhance power generation benefits without increasing the running cost of hydropower stations, so it is a hot research issue.…”

Section: Introductionmentioning

confidence: 99%

Formulation and Implementation of Short-Term Optimal Reservoir Operation Schemes Integrated with Operation Rules

Zhang¹,

Wu²,

Yu³

et al. 2019

Water

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To narrow the gap between theoretical research and practical application of short-term optimal reservoir power generation operation under uncertain conditions, a comprehensive study is conducted on the formulation, evaluation, and implementation of operation schemes throughout the entire procedure of optimal operation. Firstly, the three implementation modes of the optimal operation scheme are assessed with the post-evaluation method. After the optimal implementation mode is determined, the formulation and implementation of optimal operation schemes are improved by combining the advantages of conventional and optimal operation and using the concept of warning water level in operation rules. Finally, the Xiaoxuan Reservoir is taken as an example for simulation calculation under different operating conditions. The results show that the operation model integrated with operation rules has both the security of conventional operation and the profitability of optimal operation. The accordingly-formulated optimal operation schemes, when implemented with the output control mode, can provide valuable guidance for the actual operation of hydropower stations.

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A multiobjective short‐term optimal operation model for a cascade system of reservoirs considering the impact on long‐term energy production

Cited by 40 publications

References 30 publications

Classification of US Hydropower Dams by their Modes of Operation

Classification of US Hydropower Dams by their Modes of Operation

Informing the operations of water reservoirs over multiple temporal scales by direct use of hydro-meteorological data

Formulation and Implementation of Short-Term Optimal Reservoir Operation Schemes Integrated with Operation Rules

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