Peak Load Forecasting Methods of Sulbagsel Electrical Systems

Abstract

Abstract. This research is an ex post facto study using a descriptive approach and an exploratory nature which aims to determine the peak load growth from 2019 to 2023 and the appropriate peak load forecasting method is used. Data collection techniques are carried out by using observation and documentation to obtain data and information about this research by recording and observing documents related to research. The results showed that the average peak load growth of Sulbagsel electrical system from 2019 to 2023 for the six peak load forecasting methods used, namely 1.19 for the demand forecast (DF) method with an average percentage level of confidence in the peak load forecasting results of 97.97%, for the linear regression method of 1.21 with an average percentage of the confidence level of the peak load forecasting results of 99.39%, the quadratic regression method of 0.99 with an average percentage of the confidence level of the peak load forecasting results of 97.27%, the single moving average method (SMA ) of 1.12 with an average percentage of the confidence level of the peak load forecasting results of 98.14%, the double moving average (DMA) method of 1.17 with an average percentage of the confidence level of the peak load forecasting results of 97.55%, and using the load growth average method ( LGA) of 1.39 with an average percentage level at the confidence of the peak load forecasting results of 103.5%.

Keywords: Sulbagsel electrical system, load forecasting method