A Comprehensive Review of Residential Electricity Load Profile Models
| Autor: | Proedrou, Elisavet |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
demand forecasting
residential electricity load profile model Load modeling electricity consumption smart homes power demand load management demand-side management residential power demand lcsh:Electrical engineering. Electronics. Nuclear engineering household electricity load profile model lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 9, Pp 12114-12133 (2021) |
| ISSN: | 2169-3536 |
| Popis: | A third of the final electricity in the EU is consumed by households. The increased usage of multiple electrical devices, electromobility, self-generation and consumption of electricity as well as work-from-home will fundamentally change the residential electricity load profile, so a deep understanding of the current state of residential electricity load profile modelling is necessary. The objective of this paper is to perform a literature review, evaluate the current state of the residential electricity load profile modelling, categorise the models, propose future research directions and applications, identify the challenges the researchers face when building these models and offer possible solutions. Thirty two residential electricity load profile models are identified and a new definition of the residential electricity load profile model is proposed. A new categorisation system based on the identification of the main features of these thirty two studies is introduced. Future research directions and applications are presented and the most important challenges that modellers face when attempting to build such models are identified and discussed. The most important challenge identified is the privacy concerns of the participants or potential participants. These concerns are at least partially responsible for the existence of the rest of the challenges. The creation and implementation of an anonymisation algorithm, before any human has access to any measured datasets, the implementation of a crowd sourcing approach which addresses the privacy concerns of the citizens and increased funding for the installation of privacy-proof smart-meters by the public and measurement campaigns are identified as possible solutions to the challenges faced by modellers. |
| Databáze: | OpenAIRE |
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