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Published (Version of Record)CC BY V4.0, Open Access
Journal article
Homogenising the design criteria of a community battery energy storage for better grid integration
Sustainability, Vol.14(2), Article 733
2022
Abstract
Historically, minimum system demand has usually occurred overnight. However, in recent years, the increased penetration of rooftop photovoltaic systems (RPVs) has caused an even lower demand at midday, forcing some of the conventional generators to shut down only hours before the evening peak demand period. This further complicates the job of power system operators, who need to run the conventional generator at the minimum stable level at the midday low-demand period so that they can reliably supply power during the peak periods. Employing a community battery storage system can alleviate some of the technical issues caused by the high penetration of RPVs. This paper proposed a design criterion for community battery energy storage systems and employed the battery for the improvement of the duck curve profile and providing the desired level of peak-shaving. Furthermore, remote communities with high penetration of RPVs with a community battery energy storage can achieve the desired level of self-sufficiency. To this end, this study recommends and confirms an applicable design criterion for community battery energy storage. The study shows that the suitable size of community battery storage should be based on the community’s daily excess generation and consumption requirements. The results of various scenarios performed on the proposed design criterion show the extent to which the desired objectives of peak-shaving, duck curve mitigation, and self-sufficiency can be achieved.
Details
- Title
- Homogenising the design criteria of a community battery energy storage for better grid integration
- Authors/Creators
- M.A. Hayat (Author/Creator)F. Shahnia (Author/Creator)GM. Shafiullah (Author/Creator)R. Samu (Author/Creator)
- Publication Details
- Sustainability, Vol.14(2), Article 733
- Publisher
- MDPI
- Identifiers
- 991005541358607891
- Copyright
- © 2022 by the authors
- Murdoch Affiliation
- School of Engineering and Energy
- Language
- English
- Resource Type
- Journal article
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- Citation topics
- 4 Electrical Engineering, Electronics & Computer Science
- 4.18 Power Systems & Electric Vehicles
- 4.18.204 Smart Grid Optimization
- Web Of Science research areas
- Environmental Sciences
- Environmental Studies
- Green & Sustainable Science & Technology
- ESI research areas
- Environment/Ecology