Application of Volterra Equations to Solve Unit Commitment Problem of Optimised Energy Storage and Generation

Development of reliable methods for optimised energy storage and generation is one of the most imminent challenges in moder power systems. In this paper an adaptive approach to load leveling problem using novel dynamic models based on the Volterra integral equations of the first kind with piecewise...

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Main Authors: Muftahov, Ildar, Sidorov, Denis, Zhukov, Aleksei, Panasetsky, Daniil, Foley, Aoife, Li, Yong, Tynda, Aleksandr
Format: Report
Language:unknown
Published: arXiv 2016
Subjects:
Online Access:https://dx.doi.org/10.48550/arxiv.1608.05221
https://arxiv.org/abs/1608.05221
id ftdatacite:10.48550/arxiv.1608.05221
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spelling ftdatacite:10.48550/arxiv.1608.05221 2023-05-15T18:09:10+02:00 Application of Volterra Equations to Solve Unit Commitment Problem of Optimised Energy Storage and Generation Muftahov, Ildar Sidorov, Denis Zhukov, Aleksei Panasetsky, Daniil Foley, Aoife Li, Yong Tynda, Aleksandr 2016 https://dx.doi.org/10.48550/arxiv.1608.05221 https://arxiv.org/abs/1608.05221 unknown arXiv arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Systems and Control eess.SY Functional Analysis math.FA Numerical Analysis math.NA FOS Electrical engineering, electronic engineering, information engineering FOS Mathematics 65R32, 45D05, 65R20 Preprint Article article CreativeWork 2016 ftdatacite https://doi.org/10.48550/arxiv.1608.05221 2022-04-01T11:18:20Z Development of reliable methods for optimised energy storage and generation is one of the most imminent challenges in moder power systems. In this paper an adaptive approach to load leveling problem using novel dynamic models based on the Volterra integral equations of the first kind with piecewise continuous kernels. These integral equations efficiently solve such inverse problem taking into account both the time dependent efficiencies and the availability of generation/storage of each energy storage technology. In this analysis a direct numerical method is employed to find the least-cost dispatch of available storages. The proposed collocation type numerical method has second order accuracy and enjoys self-regularization properties, which is associated with confidence levels of system demand. This adaptive approach is suitable for energy storage optimisation in real time. The efficiency of the proposed methodology is demonstrated on the Single Electricity Market of Republic of Ireland and Sakhalin island in the Russian Far East. : arXiv admin note: text overlap with arXiv:1507.06484 Report Sakhalin DataCite Metadata Store (German National Library of Science and Technology) Moder ENVELOPE(-62.533,-62.533,-76.100,-76.100)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Systems and Control eess.SY
Functional Analysis math.FA
Numerical Analysis math.NA
FOS Electrical engineering, electronic engineering, information engineering
FOS Mathematics
65R32, 45D05, 65R20
spellingShingle Systems and Control eess.SY
Functional Analysis math.FA
Numerical Analysis math.NA
FOS Electrical engineering, electronic engineering, information engineering
FOS Mathematics
65R32, 45D05, 65R20
Muftahov, Ildar
Sidorov, Denis
Zhukov, Aleksei
Panasetsky, Daniil
Foley, Aoife
Li, Yong
Tynda, Aleksandr
Application of Volterra Equations to Solve Unit Commitment Problem of Optimised Energy Storage and Generation
topic_facet Systems and Control eess.SY
Functional Analysis math.FA
Numerical Analysis math.NA
FOS Electrical engineering, electronic engineering, information engineering
FOS Mathematics
65R32, 45D05, 65R20
description Development of reliable methods for optimised energy storage and generation is one of the most imminent challenges in moder power systems. In this paper an adaptive approach to load leveling problem using novel dynamic models based on the Volterra integral equations of the first kind with piecewise continuous kernels. These integral equations efficiently solve such inverse problem taking into account both the time dependent efficiencies and the availability of generation/storage of each energy storage technology. In this analysis a direct numerical method is employed to find the least-cost dispatch of available storages. The proposed collocation type numerical method has second order accuracy and enjoys self-regularization properties, which is associated with confidence levels of system demand. This adaptive approach is suitable for energy storage optimisation in real time. The efficiency of the proposed methodology is demonstrated on the Single Electricity Market of Republic of Ireland and Sakhalin island in the Russian Far East. : arXiv admin note: text overlap with arXiv:1507.06484
format Report
author Muftahov, Ildar
Sidorov, Denis
Zhukov, Aleksei
Panasetsky, Daniil
Foley, Aoife
Li, Yong
Tynda, Aleksandr
author_facet Muftahov, Ildar
Sidorov, Denis
Zhukov, Aleksei
Panasetsky, Daniil
Foley, Aoife
Li, Yong
Tynda, Aleksandr
author_sort Muftahov, Ildar
title Application of Volterra Equations to Solve Unit Commitment Problem of Optimised Energy Storage and Generation
title_short Application of Volterra Equations to Solve Unit Commitment Problem of Optimised Energy Storage and Generation
title_full Application of Volterra Equations to Solve Unit Commitment Problem of Optimised Energy Storage and Generation
title_fullStr Application of Volterra Equations to Solve Unit Commitment Problem of Optimised Energy Storage and Generation
title_full_unstemmed Application of Volterra Equations to Solve Unit Commitment Problem of Optimised Energy Storage and Generation
title_sort application of volterra equations to solve unit commitment problem of optimised energy storage and generation
publisher arXiv
publishDate 2016
url https://dx.doi.org/10.48550/arxiv.1608.05221
https://arxiv.org/abs/1608.05221
long_lat ENVELOPE(-62.533,-62.533,-76.100,-76.100)
geographic Moder
geographic_facet Moder
genre Sakhalin
genre_facet Sakhalin
op_rights arXiv.org perpetual, non-exclusive license
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
op_doi https://doi.org/10.48550/arxiv.1608.05221
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