Solving a large energy system optimization model using an open-source solver

Open-source energy models are becoming more widely used for electric power systems planning. The solutions for these models are often computed using commercial optimization solvers, which require licensing fees that can be a potential barrier for certain organizations and researchers. This study exp...

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Autores principales:	Madeline Macmillan, Kelly Eurek, Wesley Cole, Morgan D. Bazilian
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Open-source solvers Energy models Solve time ReEDS Energy industries. Energy policy. Fuel trade HD9502-9502.5
Acceso en línea:	https://doaj.org/article/9e6156d2163c41cda7d657128491a1eb
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id	oai:doaj.org-article:9e6156d2163c41cda7d657128491a1eb
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spelling	oai:doaj.org-article:9e6156d2163c41cda7d657128491a1eb2021-11-26T04:28:30ZSolving a large energy system optimization model using an open-source solver2211-467X10.1016/j.esr.2021.100755https://doaj.org/article/9e6156d2163c41cda7d657128491a1eb2021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2211467X21001401https://doaj.org/toc/2211-467XOpen-source energy models are becoming more widely used for electric power systems planning. The solutions for these models are often computed using commercial optimization solvers, which require licensing fees that can be a potential barrier for certain organizations and researchers. This study explores the ability of the open-source COIN-OR linear programming (CLP) solver to compute solutions for the Regional Energy Deployment System (ReEDS) model—a large-scale, open-access electricity system planning model for the United States developed by the National Renewable Energy Laboratory (NREL). We find that open-source solvers, such as CLP, require some reduction of model size and detail. Although the solutions for reduced-form models may differ from full-featured models, we demonstrate that reduced-form solutions for ReEDS can still provide useful insight about drivers of power sector evolution. This research can help the modeling community better understand how open-source solvers can be applied to large-scale planning tools, and the potential steps that may be required to implement them.Madeline MacmillanKelly EurekWesley ColeMorgan D. BazilianElsevierarticleOpen-source solversEnergy modelsSolve timeReEDSEnergy industries. Energy policy. Fuel tradeHD9502-9502.5ENEnergy Strategy Reviews, Vol 38, Iss , Pp 100755- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Open-source solvers Energy models Solve time ReEDS Energy industries. Energy policy. Fuel trade HD9502-9502.5
spellingShingle	Open-source solvers Energy models Solve time ReEDS Energy industries. Energy policy. Fuel trade HD9502-9502.5 Madeline Macmillan Kelly Eurek Wesley Cole Morgan D. Bazilian Solving a large energy system optimization model using an open-source solver
description	Open-source energy models are becoming more widely used for electric power systems planning. The solutions for these models are often computed using commercial optimization solvers, which require licensing fees that can be a potential barrier for certain organizations and researchers. This study explores the ability of the open-source COIN-OR linear programming (CLP) solver to compute solutions for the Regional Energy Deployment System (ReEDS) model—a large-scale, open-access electricity system planning model for the United States developed by the National Renewable Energy Laboratory (NREL). We find that open-source solvers, such as CLP, require some reduction of model size and detail. Although the solutions for reduced-form models may differ from full-featured models, we demonstrate that reduced-form solutions for ReEDS can still provide useful insight about drivers of power sector evolution. This research can help the modeling community better understand how open-source solvers can be applied to large-scale planning tools, and the potential steps that may be required to implement them.
format	article
author	Madeline Macmillan Kelly Eurek Wesley Cole Morgan D. Bazilian
author_facet	Madeline Macmillan Kelly Eurek Wesley Cole Morgan D. Bazilian
author_sort	Madeline Macmillan
title	Solving a large energy system optimization model using an open-source solver
title_short	Solving a large energy system optimization model using an open-source solver
title_full	Solving a large energy system optimization model using an open-source solver
title_fullStr	Solving a large energy system optimization model using an open-source solver
title_full_unstemmed	Solving a large energy system optimization model using an open-source solver
title_sort	solving a large energy system optimization model using an open-source solver
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/9e6156d2163c41cda7d657128491a1eb
work_keys_str_mv	AT madelinemacmillan solvingalargeenergysystemoptimizationmodelusinganopensourcesolver AT kellyeurek solvingalargeenergysystemoptimizationmodelusinganopensourcesolver AT wesleycole solvingalargeenergysystemoptimizationmodelusinganopensourcesolver AT morgandbazilian solvingalargeenergysystemoptimizationmodelusinganopensourcesolver
_version_	1718409918579474432

Solving a large energy system optimization model using an open-source solver

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