Intelligent optimisation for sustainable development of onshore wind farm battery energy storage systems : a systematic review

dc.contributor.authorGwabavu, Mandisi
dc.contributor.authorBansal, Ramesh C.
dc.contributor.authorShakantu, Winston
dc.contributor.authorNyandeni, Lethaba
dc.contributor.authorOwolawi, Pius Adewale.
dc.contributor.authorMadwe, Mziwendoda C.
dc.date.accessioned2026-05-07T09:31:42Z
dc.date.available2026-05-07T09:31:42Z
dc.date.issued2026-03
dc.descriptionDATA AVAILABILITY : No data was used for the research described in the article.
dc.description.abstractThe global shift toward renewable energy is driven by the urgent need to combat climate change and achieve net-zero emissions, with wind power emerging as a key pillar due to its scalability and cost-effectiveness amid rising energy demands and fossil fuel volatility. This systematic review investigates the role of intelligent optimisation techniques in facilitating the sustainable development of onshore wind farms integrated with Battery Energy Storage Systems (BESS). It synthesises advanced methods, including machine learning, evolutionary algorithms, and hybrid meta-heuristics, to enhance reliability, efficiency, and lifecycle performance of wind-BESS systems, addressing wind intermittency challenges in low-carbon transitions. Employing a systems-based approach and the PRISMA methodology, the review analyses 1295 studies, of which 152 meet eligibility criteria, encompassing technological innovation, facilities management (FM), and social, economic, and environmental factors. The primary contribution is the integration of FM perspectives into intelligent optimisation, proposing a novel framework that links predictive analytics, asset management, and sustainability metrics. Results highlight the efficacy of intelligent optimisation in improving grid stability, reducing costs, and enhancing resilience. The review proposes a conceptual framework that aligns optimisation with global sustainability goals and calls for empirical validation to guide policy, investment, and practice, particularly in developing economies. HIGHLIGHTS • This review's bibliometric analysis evaluated 1295 studies, with 152 meeting strict eligibility criteria. • Life cycle stages of intelligent optimisation for sustainable development of an onshore wind farm BESS. • Identifying critical factors for the sustainable development of an onshore wind farm BESS. • The integration of FM perspectives into intelligent optimisation of wind farm BESS. • A theoretical and conceptual framework guiding intelligent optimisation in sustainable development of onshore wind farm BESS.
dc.description.departmentElectrical, Electronic and Computer Engineering
dc.description.librarianhj2026
dc.description.sdgSDG-03: Good health and well-being
dc.description.sdgSDG-07: Affordable and clean energy
dc.description.sdgSDG-07: Affordable and clean energy
dc.description.sdgSDG-08: Decent work and economic growth
dc.description.sdgSDG-10: Reduces inequalities
dc.description.sdgSDG-11: Sustainable cities and communities
dc.description.sdgSDG-13: Climate action
dc.description.sdgSDG-12: Responsible consumption and production
dc.description.sdgSDG-13: Climate action
dc.description.sdgSDG-14: Life below water
dc.description.sdgSDG-15: Life on land
dc.description.urihttps://www.elsevier.com/locate/esr
dc.identifier.citationGwabavu, M., Bansal, R.C., Shakantu, W. et al. 2026, 'Intelligent optimisation for sustainable development of onshore wind farm battery energy storage systems : a systematic review', Energy Strategy Reviews, vol. 64, art. 102109, pp. 1-21, doi : 10.1016/j.esr.2026.102109.
dc.identifier.issn2211-467X (print)
dc.identifier.issn2211-4688 (online)
dc.identifier.other10.1016/j.esr.2026.102109
dc.identifier.urihttp://hdl.handle.net/2263/109857
dc.language.isoen
dc.publisherElsevier
dc.rights© 2026 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
dc.subjectBattery energy storage systems (BESS)
dc.subjectFacilities management
dc.subjectIntelligent optimisation
dc.subjectOnshore wind farm
dc.subjectSustainable development
dc.subjectRenewable energy transition
dc.titleIntelligent optimisation for sustainable development of onshore wind farm battery energy storage systems : a systematic review
dc.typeArticle

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Gwabavu_Intelligent_2026.pdf
Size:
7.44 MB
Format:
Adobe Portable Document Format
Description:
Article

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: