Data analysis approach for characterizing residential energy consumption based on statistics of household appliances ownership

Abstract

Worldwide, residential electricity demand has increased constantly, expecting to double in 2050 the demand of 2010. Different policies have been proposed to achieve a smart use of electricity. This article presents a data-analysis approach to evaluate the potential household electricity consumption from statistical data. The main axis of the study are statistics of appliance ownership and information of the appliance characteristics, gathered from census surveys and local shops. An index to estimate the electricity consumption is performed. The validation of the proposed index is carried out using real consumption data from the Electricity Consumption Data set of Uruguay and Ordinary Least Square linear regressions. Jupyter notebooks, Python language and well-know libraries such as Pandas and Numpy were used during the implementation. The main results show that administrative regions located on the West/Southwest coastlines present the highest index scores. In turn, census sections/segments on the West/Southwest coastlines of Montevideo performed the highest scores while the lowest scores can be found at the outskirts of the city. The proposed methodology can be applied for electricity consumption estimation in other regions/countries where census data is publicly available.