Lessons Learnt from Mining Meter Data of Residential Consumers
| Autor: | Sima Davarzani, Konstantinos Blazakis, Ioana Pisica, Georgios Stavrakakis |
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| Rok vydání: | 2016 |
| Předmět: |
Engineering
Computer Networks and Communications Smart meter Non-technical losses Computer security computer.software_genre Load profile Demand response Electricity market Electrical and Electronic Engineering Cluster analysis Data mining Electric load clustering business.industry Demand forecasting Environmental economics Computer Science Applications Smart metering Distributed generation Signal Processing Power theft Electricity business computer Software Information Systems |
| Zdroj: | Periodica Polytechnica Electrical Engineering and Computer Science. 60:266-272 |
| ISSN: | 2064-5279 2064-5260 |
| Popis: | Summarization: Tracking end-users' usage patterns can enable more accurate demand forecasting and the automation of demand response execution. Accordingly, more advanced applications, such as electricity market design, integration of distributed generation and theft detection can be developed. By employing data mining techniques on smart meter recordings, the suppliers can efficiently investigate the load patterns of consumers. This paper presents applications where data mining of energy usage can derive useful information. Higher demands, on one side, and the energy price increase on the other side, have caused serious issues with regards to electricity theft, especially among developing countries. This phenomenon leads to considerable operational losses within the electrical network. In order to identify illegal residential consumers, a new method of analysing and identifying electricity consumption patterns of consumers is proposed in this paper. Moreover, the importance of data mining for analysing the consumer's usage curves was investigated. This helps to determine the behaviour of end-users for demand response purposes and improve the reliability and security of the electricity network. Clustering load profiles for large scale energy datasets are discussed in detail. Παρουσιάστηκε στο: Periodica polytechnica Electrical engineering and computer science |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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