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                <identifier>oai:data.mendeley.com/h4j4cd8b66.1</identifier>
                <datestamp>2020-11-19T01:22:01Z</datestamp>
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    <dc:creator>Abdelhady, Hazem</dc:creator>
    <dc:title>Data for: Parallelized Multi-level Optimization Model with Continuous Search Domain for Selection of Run-of-river Hydropower Projects</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>This folder contains the code for the Run-of-River Project Optimization (RoRPO) model described in the manuscript. The RoRPO model is coded in MatLab and is designed to be used on high-performance computing (HPC) facilities. The code that is provided here applies the RoRPO model to the Guder River case study. Flow data for Guder River is in the file &quot;GuderRiverFlow.mat&quot;. The profile of Guder River is in the file &quot;GuderRiverProfile.mat&quot;. The RoRPO model selects turbines from a predefined set. Characteristics of turbines defined for the Guder River case study are given I the file &quot;turbineData.mat&quot;.
To run the model on an HPC, execute &quot;ror_main.m&quot; with &quot;ror_0.mat&quot; as an input file. The model should automatically run in parallel and generate new instances on the HPC. Results are written to the file &quot;ror_out.mat&quot;. After running the code, you can use this command to open the output file &quot;dlmread(&apos;ror_out.mat&apos;)&quot;.</dc:description>
    <dc:subject>Hydroelectric Energy</dc:subject>
    <dc:subject>Constrained Optimization</dc:subject>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/h4j4cd8b66.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/h4j4cd8b66.1</dc:identifier>
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    <dc:date>2020-11-19T01:22:01Z</dc:date>
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