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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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) |
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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 |
_version_ |
1766181623583211520 |