Energy storage scheduling with an advanced battery model : a game–theoretic approach
- Submitting institution
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Kingston University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11-02-1336
- Type
- D - Journal article
- DOI
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10.3390/inventions2040030
- Title of journal
- Inventions
- Article number
- -
- First page
- 30
- Volume
- 2
- Issue
- -
- ISSN
- 2411-5134
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2017
- URL
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-
- Supplementary information
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- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
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- Research group(s)
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-
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work investigates the use of autonomously managed battery storage systems to shift users’ electricity loads and reduce peak consumption without affecting their consumption habits. It offers a game theoretic framework that optimises the use of these batteries, whose actual charging and discharging characteristics are modelled realistically. It is significant as both users lower their bills and utility companies see reduced peak consumption. The model developed in this work has been extended to address the shortage of personal protective equipment in the COVID-19 crisis (published in PLOS ONE in 2021).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -