A combined 2-dimensional fuzzy regression model to study effect of climate change on the electrical peak load.

This paper studies the impact of climate change on the electricity consumption by means of a fuzzy regression approach. The climate factors which have been considered in this paper are humidity and temperature, whereas the simultaneous effect of these two climate factors is considered. The impacts of other climate variables, like the wind, with a minor effect on energy consumption are ignored. The innovation which applies in this paper is the division of the year into two parts by using the temperature-day graph in the year. To index the humidity, data of the minimum humidity per day are used. For temperature, the maximum temperature of the first part of the year (warm days) and the minimum of the second part (cold days) are used. The indicator for the consumption is the daily peak load. The model results show high sensitivity to the temperature but low sensitivity to the humidity. Moreover, it is concluded that the model structure cannot be the same and for the cold par additional variables such as gas consumption should be considered. [ABSTRACT FROM AUTHOR]