Approach for smart meter load profiling in Monte Carlo simulation applications
- Submitting institution
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The University of Birmingham
- Unit of assessment
- 12 - Engineering
- Output identifier
- 43362794
- Type
- D - Journal article
- DOI
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10.1049/iet-gtd.2016.2084
- Title of journal
- IET Generation, Transmission and Distribution
- Article number
- -
- First page
- 1856
- Volume
- 11
- Issue
- 7
- ISSN
- 1751-8687
- Open access status
- Compliant
- Month of publication
- April
- Year of publication
- 2017
- URL
-
-
- Supplementary information
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-
- 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
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1
- Research group(s)
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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper proposes an innovative approach to stochastically model the load demands of smart meter customers in cities using energy data taken through the advanced metering infrastructure. The approach is the first of its kind and revolutionises the stochastic load modelling in smart power grids. It presents a solution to the big-data problem and impacts the whole research community in smart power grid assessments. A PhD project based on the research is advancing the approach to the dynamic and deterministic load modelling levels. This will further widen the application’s levels and the innovation.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -