A methodology for Electric Power Load Forecasting

• Main Authors: Eisa Almeshaiei, Hassan Soltan
• Format: Article
• Language: English
• Published: Elsevier 2011-06-01
• Series: Alexandria Engineering Journal
• Subjects: Electric Power Load Forecasting; Time series; Pattern segmentation/decomposition
• Online Access: http://www.sciencedirect.com/science/article/pii/S1110016811000330

Electricity demand forecasting is a central and integral process for planning periodical operations and facility expansion in the electricity sector. Demand pattern is almost very complex due to the deregulation of energy markets. Therefore, finding an appropriate forecasting model for a specific electricity network is not an easy task. Although many forecasting methods were developed, none can be generalized for all demand patterns. Therefore, this paper presents a pragmatic methodology that can be used as a guide to construct Electric Power Load Forecasting models. This methodology is mainly based on decomposition and segmentation of the load time series. Several statistical analyses are involved to study the load features and forecasting precision such as moving average and probability plots of load noise. Real daily load data from Kuwaiti electric network are used as a case study. Some results are reported to guide forecasting future needs of this network.