Reducing energy consumption by using self-organizing maps to create more personalized electricity use information

Teemu Räsänen, Juhani Ruuskanen and Mikko Kolehmainen

Applied Energy, 2008, vol. 85, issue 9, 830-840

Abstract: Identification of electricity use is one of the key elements to motivate customers to promote activities leading more efficient use of energy. Furthermore, electricity use comparisons with other similar customers give more interesting and concrete point of view to examine own consumption habits. In future, electricity providers and retailers are willing and probably forced by legislation to provide such information by the means of energy conservation and efficiency improvement. On the other hand, high number of customers set challenges to handle electricity use data and to create proper comparison information. In this study we present efficient and highly automated way to create comparison groups based on customers building characteristics. The main advantages of the data-based approach are that customer location is noticed, comparison groups are created using concrete building information, data processing is highly automated and also method is computationally efficient. Additionally, presented method provide tool to target and to create customer specific electricity saving guidance. The performance of suggested approach was tested using data set which contained electricity use and building information concerning almost 8000 customers.

Keywords: Electricity; use; Energy; efficiency; Clustering; Self-organizing; map; K-means (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (21)

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