Engineering Commons^™

Characterising Domestic Electricity Demand For Customer Load Profile Segmentation, Fintan Mcloughlin

Doctoral

The aim of this research was to characterise domestic electricity patterns of use on a diurnal, intra-daily and seasonal basis as a function of customer characteristics. This was done in order to produce a library of representative electricity demand load profiles that are characteristic of how households consume electricity. In so doing, a household’s electricity demand can be completely characterised based solely on their individual customer characteristics.

A number of different approaches were investigated as to their ability to characterise domestic electricity use. A statistical regression approach was evaluated which had the advantage of identifying key dwelling, occupant and appliance …

Evaluation Of Time Series Techniques To Characterise Domestic Electricity Demand, Fintan Mcloughlin, Aidan Duffy, Michael Conlon

Articles

This paper discusses time series approaches, often used by Transmission System Operators (TSOs) to forecast system demand, and applies them at an individual dwelling level. In particular, two techniques, Fourier transforms and Gaussian processes were evaluated and used to characterise individual household electricity demand. The performance of the characterisation approaches were evaluated based on Pearson correlation coefficient, descriptive statistics and paired sample t-tests for electrical parameters: Total Electricity Consumption, Maximum Demand, Load Factor and Time of Use of maximum electricity demand. Finally, a number of time series tests were carried out to ensure certain properties remained between the original and …