Lai, CS, Li, X, Locatelli, G orcid.org/0000-0001-9986-2249 et al. (1 more author)
(2020)
Cost benefit analysis and data analytics for renewable energy and electrical energy storage.
In:
Proceedings of 11th IET International Conference on Advances in Power System Control, Operation and Management.
11th IET International Conference on Advances in Power System Control, Operation and Management, 11-15 Nov 2018, Hong Kong, China.
IET
ISBN 978-1-78561-942-7
Abstract
To accommodate with the global increase in the deployment of solar photovoltaic (PV) and energy storage system (ESS), a deterministic approach for sizing PV and ESS with anaerobic digestion biogas power plant; to meet a load demand will be presented in this plenary session. This aim is to maximize the sizing of PV to increase the security of energy supply. Energy economics for ESS will be a focus. Case study based on real-life data will be used to demonstrate the validity of the new approach.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 Institution of Engineering and Technology. All rights reserved. This is an author produced version of a conference paper published in Proceedings of the 11th IET International Conference on Advances in Power System Control, Operation and Management. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Cost benefit analysis , data analytics , clearness index , optimal sizing |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Civil Engineering (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/P022049/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 06 Apr 2020 09:01 |
Last Modified: | 06 Apr 2020 09:01 |
Status: | Published |
Publisher: | IET |
Identification Number: | 10.1049/cp.2018.1737 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:158955 |