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Dataset for case studies of hydropower unit commitment.

ABSTRACT: This paper presents the data all needed for nine case studies of hydropower unit commitment, which determines the optimal operating zones and generating discharges of units after the quarter-hourly releases and water heads are derived by the operation of cascaded hydropower reservoirs. The power output function and feasible operating zones of units are provided, and optimization solvers are used to acquire the results in detail for the case studies, including the quarter-hourly generating discharges, power generations, as well as operating zones of individual units. Performance indices, including the spillage, energy production, and the low-efficiency generating rate, are summarized for all case studies and can be readily used for comparison between algorithms in future.

SUBMITTER: Wang J

PROVIDER: S-EPMC5996229 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Dataset for case studies of hydropower unit commitment.

Wang Jinwen J Zheng Hao H Li Yan Y Ma Teng T

Data in brief 20180308

This paper presents the data all needed for nine case studies of hydropower unit commitment, which determines the optimal operating zones and generating discharges of units after the quarter-hourly releases and water heads are derived by the operation of cascaded hydropower reservoirs. The power output function and feasible operating zones of units are provided, and optimization solvers are used to acquire the results in detail for the case studies, including the quarter-hourly generating discha ...[more]

PMID: 29896502

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Project description:The datasets described herein provide the foundation for a decision support prototype (DSP) toolkit aimed at assisting stakeholders in determining evidence of which aspects of river ecosystems have been impacted by hydropower. The DSP toolkit and its application are presented and described in the article "Evidence-based indicator approach to guide preliminary environmental impact assessments of hydropower development" [1]. Development of the DSP and the output for decision support centralize around 42 river function indicators describing the dimensionality of river ecosystems through six main categories: biota and biodiversity, water quality, hydrology, geomorphology, land cover, and river connectivity. Three main tools are represented in the DSP: A science-based questionnaire (SBQ), an environmental envelope model (EEM), and a river function linkage assessment tool (RFLAT). The SBQ is a structured survey-style questionnaire whose objective is to provide evidence of which indicators have been impacted by hydropower. Based on a global literature review, 140 questions were developed from general hypotheses regarding the impacts of dams on rivers. The EEM is a model to predict the likelihood of hydropower impacting indicators based on a several variables. The intended use of the EEM is for situations of new hydropower development where results of the SBQ are incomplete or highly uncertain. The EEM was developed through the compilation of a dataset containing attributes of dams, reservoirs, and geospatial information on environmental concerns, which was combined with data on ecological indicators documented at those sites through literature review. The model operates through 247 "envelopes" and weighting factors, representing the individual effect of each variable on each indicator, all available through spreadsheets. Finally, the RFLAT is a tool to examine causal relationships amongst indicators. Inter-indicator relationships were hypothesized based on literature review and summarized into node and edge datasets to represent the structure of a graphical network. Bayes theorem was used estimate conditional probabilities of inter-indicator relationships based on the output of the SBQ. Nodes and edges were imported into R programming environment to visualize ecological indicator networks. The datasets can be expanded upon and enriched with more detailed questions for the SBQ, building upon the EEM with to develop more sophisticated models, and identifying new relationships for the RFALT. Additionally, once the tools are applied to numerous hydropower developments, the output of the tools (e.g. evidence of impacted indicators) becomes a very useful dataset for meta-analyses of hydropower impacts.

Dataset Information

Dataset for case studies of hydropower unit commitment.

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Dataset for case studies of hydropower unit commitment.

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