Publication2026
AI-Driven Design and Optimization of Grid-Connected Solar PV-Battery Hybrid Systems for Educational Campuses: A Techno-Economic and Sustainability Perspective
The record
- Type
- Publication
- Date
- 1 June 2026
- Level
- National
- Journal
- High Energy Chemistry
- Volume
- 60
- Issue
- 3
- Pages
- 283-298
- Published
- 1 June 2026
- DOI
- 10.1134/s0018143925601277
- Scopus ID
- 105041336899
- ISSN
- 00181439
- Authors
- 4
- Open access
- No
- Citations
- 0
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
7 Ensure access to affordable, reliable, sustainable and modern energy for all
Proposes AI-driven framework for optimizing grid-connected solar PV-battery hybrid systems on educational campuses using graph neural networks and reinforcement learning
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
4 Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all
Educational campus energy systems implementation demonstrates sustainability within academic institutions
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-2.5 Green economy, energy transition and climate resilience
Renewable solar energy integration and smart grid optimization support energy transition and climate resilience
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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Provenance
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “AI-Driven Design and Optimization of Grid-Connected Solar PV-Battery Hybrid Systems for Educational Campuses: A Techno-Economic and Sustainability Perspective”. Kortex.