  In this paper, the relationship between the Gross Domestic Product (GDP), air
temperature variations and power consumption is evaluated using the linear
regression and Wavelet Coherence (WTC) approach on a 1971-2011 time series for
the United Kingdom (UK). The results based on the linear regression approach
indicate that some 66% variability of the UK electricity demand can be
explained by the quarterly GDP variations, while only 11% of the quarterly
changes of the UK electricity demand are caused by seasonal air temperature
variations. WTC however, can detect the period of time when GDP and air
temperature significantly correlate with electricity demand and the results of
the wavelet correlation at different time scales indicate that a significant
correlation is to be found on a long-term basis for GDP and on an annual basis
for seasonal air-temperature variations. This approach provides an insight into
the properties of the impact of the main factors on power consumption on the
basis of which the power system development or operation planning and
forecasting the power consumption can be improved.
