Publication2020
Risk Analysis based on Gaussian Mixture Model for GENCOs in Short Term Market
The record
- Type
- Publication
- Date
- 1 February 2020
- Level
- National
- Journal
- Proceedings of the 2020 International Conference on Renewable Energy Integration into Smart Grids A Multidisciplinary Approach to Technology Modelling and Simulation Icreisg 2020
- Pages
- 249-253
- Published
- 1 February 2020
- DOI
- 10.1109/icreisg49226.2020.9174198
- Scopus ID
- 85092049006
- Authors
- 3
- 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
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Gaussian mixture modeling for electricity market risk assessment under generator outages and price uncertainties improves grid planning and operational decision-making.
- 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
Viksit Bharat @2047
vb-2.5 Green economy, energy transition and climate resilience
Energy systems research improving market efficiency and renewable energy integration planning.
- 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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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Risk Analysis based on Gaussian Mixture Model for GENCOs in Short Term Market”. Kortex.