Wavelet Analysis of Electricity Demand Patterns in Abuja: Implications for Grid Management

Efficient management of the electricity grid serving the Federal Capital Territory, Abuja, in the North Central zone of Nigeria requires detailed understanding of demand patterns at multiple time scales, from intra-day peaks to seasonal cycles. This study applies discrete wavelet transform analysis to decompose hourly electricity demand data from the Abuja Electricity Distribution Company over a three-year period spanning 2021 to 2023. The Daubechies wavelet family is selected based on its suitability for non-stationary energy signals, and decomposition is performed at five resolution levels corresponding to intra-day, daily, weekly, monthly, and seasonal time scales. Each scale's contribution to total demand variance is quantified, and dominant periodicity patterns are identified. Results indicate that the daily cycle (24-hour periodicity) accounts for 41 percent of total demand variance, while the weekly cycle contributes 19 percent. Clear seasonal amplitude modulation is observed, with Harmattan season (December to February) exhibiting 14 percent lower peak demand compared to the long rainy season. The wavelet multi-resolution analysis identifies demand surge events attributable to political gatherings in the FCT as high-frequency anomalies at the two-day resolution level. The study recommends wavelet-based forecasting models for short-term generation dispatch scheduling at the national grid control centre. Keywords: wavelet analysis, electricity demand, Abuja, grid management, Daubechies wavelet.