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Multi-Method Approach to Compare the Socio-Demographic Typology of Residents and Clusters of Electricity Load Curves in a Swiss Sustainable Neighbourhood

Francesco Cimmino ; University of Applied Science Western Switzerland, Entrepreneurship & Management Institute, Switzerland
Joëlle Mastelic ; University of Applied Science Western Switzerland, Entrepreneurship & Management Institute, Switzerland
Stéphane Genoud ; University of Applied Science Western Switzerland, Entrepreneurship & Management Institute, Switzerland


Puni tekst: engleski PDF 136 Kb

str. 77-81

preuzimanja: 169

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Sažetak

A sustainable neighbourhood was built Switzerland by one of the leaders in this field. Half of the 400 apartments have been equipped with smart meters delivering big data on energy consumption (electricity, water, heating…). The company would like to know if it is possible to link socio-demographic typology of residents with energy consumption patterns. To answer this question we present in this article a multi-method approach combining qualitative analysis, frequently used in marketing (multiple correspondence analyses), and quantitative analysis from applied statistics to answer this question. First, we have conducted a survey among the residents of the sustainable neighbourhood to gather socio-demographic data, and then we have proposed a marketing typology of residents. In parallel, we have analysed load curves with statistical models (clustering factors, hermano beta models, coincidence factors, som, expert practice) to see if there are patterns of energy consumption and to determine groups of similar load curves. Then we have compared the discrepancies in the composition of the groups between both methods. This study is based on a single case study generating a new research hypothesis: the typology of residents based on socio-demographic data can be linked to energy consumption pattern of a household.



This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Ključne riječi

Hrčak ID:

251166

URI

https://hrcak.srce.hr/251166

Datum izdavanja:

31.10.2016.

Posjeta: 330 *