Data-driven robust extended computer-aided harmonic power flow analysis
- Submitting institution
-
Royal Holloway and Bedford New College
- Unit of assessment
- 12 - Engineering
- Output identifier
- 39360369
- Type
- D - Journal article
- DOI
-
10.1049/iet-gtd.2020.0922
- Title of journal
- IET Generation, Transmission and Distribution
- Article number
- -
- First page
- 4398
- Volume
- 14
- Issue
- 20
- ISSN
- 1751-8695
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2020
- 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
-
1
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper proposes a powerful computational tool for understanding harmonics in 21st century medium and low-voltage electricity networks which unveiled the contributions of neglected complexities in harmonics behaviour of practical distribution networks. The knowledge has contributed to the writing of work packages in an EPSRC grant application in collaboration with Imperial College London, John Moores Liverpool University and Newcastle University (total FEC of proposal ~£1M, RHUL share ~£176k) which is currently under review. The work also created opportunity for technical discussions with University of Alberta, Canada, and Imperial College London, UK.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
