Incorporation of wind power probabilities into long-term energy system development analysis using bottom-up models

For future low-carbon energy systems with high shares of renewable energy, temporal representation becomes the dominant factor that impacts the model outputs and analysis conclusions; therefore, relevant and complex modelling approaches are required. We present and apply specific methodology for mod...

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Autores principales:	Egidijus Norvaiša, Arvydas Galinis, Eimantas Neniškis
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Variable renewable source Wind power plant Wind power probability Temporal representation Time slice Long-term decarbonization scenario Energy industries. Energy policy. Fuel trade HD9502-9502.5
Acceso en línea:	https://doaj.org/article/e5866769a83a4be29c3ef90a09497cee
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id	oai:doaj.org-article:e5866769a83a4be29c3ef90a09497cee
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spelling	oai:doaj.org-article:e5866769a83a4be29c3ef90a09497cee2021-11-20T05:05:48ZIncorporation of wind power probabilities into long-term energy system development analysis using bottom-up models2211-467X10.1016/j.esr.2021.100770https://doaj.org/article/e5866769a83a4be29c3ef90a09497cee2021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2211467X21001541https://doaj.org/toc/2211-467XFor future low-carbon energy systems with high shares of renewable energy, temporal representation becomes the dominant factor that impacts the model outputs and analysis conclusions; therefore, relevant and complex modelling approaches are required. We present and apply specific methodology for modelling wind power plants in long-term planning models. It is based on wind power probability curves for each time slice and use of the semi-dynamic method for temporal aspect. Benefits of this approach include the representation of wind power extremes, correct address of balancing capacities and costs, partially retained chronology. We also evaluated the quantitative effect of this methodology on the results of the energy model. In determining the reasonable number of approximation steps for wind power probability curves, we found that a three-step approximation is sufficient to ensure the accuracy of model results.Egidijus NorvaišaArvydas GalinisEimantas NeniškisElsevierarticleVariable renewable sourceWind power plantWind power probabilityTemporal representationTime sliceLong-term decarbonization scenarioEnergy industries. Energy policy. Fuel tradeHD9502-9502.5ENEnergy Strategy Reviews, Vol 38, Iss , Pp 100770- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Variable renewable source Wind power plant Wind power probability Temporal representation Time slice Long-term decarbonization scenario Energy industries. Energy policy. Fuel trade HD9502-9502.5
spellingShingle	Variable renewable source Wind power plant Wind power probability Temporal representation Time slice Long-term decarbonization scenario Energy industries. Energy policy. Fuel trade HD9502-9502.5 Egidijus Norvaiša Arvydas Galinis Eimantas Neniškis Incorporation of wind power probabilities into long-term energy system development analysis using bottom-up models
description	For future low-carbon energy systems with high shares of renewable energy, temporal representation becomes the dominant factor that impacts the model outputs and analysis conclusions; therefore, relevant and complex modelling approaches are required. We present and apply specific methodology for modelling wind power plants in long-term planning models. It is based on wind power probability curves for each time slice and use of the semi-dynamic method for temporal aspect. Benefits of this approach include the representation of wind power extremes, correct address of balancing capacities and costs, partially retained chronology. We also evaluated the quantitative effect of this methodology on the results of the energy model. In determining the reasonable number of approximation steps for wind power probability curves, we found that a three-step approximation is sufficient to ensure the accuracy of model results.
format	article
author	Egidijus Norvaiša Arvydas Galinis Eimantas Neniškis
author_facet	Egidijus Norvaiša Arvydas Galinis Eimantas Neniškis
author_sort	Egidijus Norvaiša
title	Incorporation of wind power probabilities into long-term energy system development analysis using bottom-up models
title_short	Incorporation of wind power probabilities into long-term energy system development analysis using bottom-up models
title_full	Incorporation of wind power probabilities into long-term energy system development analysis using bottom-up models
title_fullStr	Incorporation of wind power probabilities into long-term energy system development analysis using bottom-up models
title_full_unstemmed	Incorporation of wind power probabilities into long-term energy system development analysis using bottom-up models
title_sort	incorporation of wind power probabilities into long-term energy system development analysis using bottom-up models
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/e5866769a83a4be29c3ef90a09497cee
work_keys_str_mv	AT egidijusnorvaisa incorporationofwindpowerprobabilitiesintolongtermenergysystemdevelopmentanalysisusingbottomupmodels AT arvydasgalinis incorporationofwindpowerprobabilitiesintolongtermenergysystemdevelopmentanalysisusingbottomupmodels AT eimantasneniskis incorporationofwindpowerprobabilitiesintolongtermenergysystemdevelopmentanalysisusingbottomupmodels
_version_	1718419630377140224

Incorporation of wind power probabilities into long-term energy system development analysis using bottom-up models

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