Electricity demand modelling is the central and integral issue for the planning and operation of power systems. Load projection provides important information for electricity network planning, and it is essential for the electricity system development. This work investigates the impact of specific economic, technical and climate characteristics on the shape of the electricity demand and introduces a methodology to project electricity demand in hourly resolution within a single framework for all countries. The method used is a multiple linear regression in terms of spectral analysis. 57 real load data profiles of diverse countries were decomposed into a set of sine functions to analyse the cyclical pattern of the data. Fourier coefficients contain information about frequencies and amplitudes in these sinusoids. The sum of various sine functions can be used to calibrate and project hourly electricity demand for any country with available input data for any year in the addressed period. The accuracy of proposed model function is represented in terms of R-squared error. The proposed model is flexible to be applied to different socio-economic scenarios based on alternative assumptions regarding both long-term trends as well as short-term projections.
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