Publication2025
Advanced Forecasting Models for Electricity Demand and Price to Enhance Grid Stability and Market Efficiency
The record
- Type
- Publication
- Date
- 1 January 2025
- Level
- National
- Journal
- 5th IEEE International Conference on Sustainable Energy and Future Electric Transportation Sefet 2025
- Published
- 1 January 2025
- DOI
- 10.1109/sefet65155.2025.11255471
- Scopus ID
- 105030325160
- Authors
- 2
- 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
7.3 Double the global rate of improvement in energy efficiency
Develops machine learning models (LSTM, Bi-LSTM) for electricity demand and price forecasting achieving high accuracy improving grid stability, energy market efficiency and demand management
- 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
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Proposes advanced deep learning algorithms with hyperparameter tuning for optimization of renewable energy grid operations and smart meter data analysis
- 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
Electricity forecasting research enhances modern grid management and integration of renewable energy sources into sustainable energy systems
- 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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- 1
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Citing this record
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KIIT Deemed to be University. “Advanced Forecasting Models for Electricity Demand and Price to Enhance Grid Stability and Market Efficiency”. Kortex.