An Analysis and Forecasting of Electricity Demand Using the Triple Exponential Smoothing Method - Aulia Nur Aini; Hakim, Dimara Kusuma; Feri Wibowo; Elindra Ambar Pambudi (Jurnal E-Komtek (Elektro-Komputer-Teknik), 2025)
Electricity is a basic necessity required in daily life, supporting various activities, including economic development. The growing demand for electricity requires reliable and efficient planning and management of the power system. Electricity demand forecasting is essential due to its fluctuating nature and seasonal patterns. This study aims to forecast electricity demand using the Triple Exponential Smoothing method with data from the Australian Energy Market Operator (AEMO) for the New South Wales region, Australia, covering the period from January 2015 to February 2025. This method is chosen because it effectively handles time series data patterns consisting of level, trend, and seasonal components. The forecasting results show that this method is capable of closely following the actual data patterns and produces a Mean Absolute Percentage Error (MAPE) of 2.89%, indicating a very good performance. This model is expected to serve as a basis for decision-making in anticipating future fluctuations in electricity demand.