Consumption-Aware Data Analytical Demand Response Scheme for Peak Load Reduction in Smart Grid
- Submitting institution
-
The University of Essex
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1431
- Type
- D - Journal article
- DOI
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10.1109/tie.2018.2813990
- Title of journal
- IEEE Transactions on Industrial Electronics
- Article number
- -
- First page
- 8993
- Volume
- 65
- Issue
- 11
- ISSN
- 0278-0046
- Open access status
- Deposit exception
- Month of publication
- March
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
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A - Artificial Intelligence (AI)
- Citation count
- 25
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper, published in IEEE-TIE, a top-ranked journal, formalizes novel data-driven factors for solving the complex problem of reducing peak-load demand on the electricity grid. Algorithms were proposed for managing the load of residential users and a new customer incentive scheme was devised to attract wider participation. This significant, innovative paper was influential in Jindal winning two awards: IEEE TCSC Outstanding Ph.D. Dissertation Award'19 and IEEE ComSoc's Outstanding Young Researcher Award'19 (EMEA) and an invited-lecture at TU Berlin. It has influenced demand response, electricity price forecasting and user-incentive mechanisms researchers in Iran (2019), Pakistan (2019), Portugal (2020) and Egypt (2021).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -