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Development of Micro-Spatial Electricity Load Forecasting Methodology Using Multivariate Analysis for Dynamic Area in Tangerang, Indonesia

Dynamic population and land use significantly affect future energy demand. This paper proposes a suitable method to forecast load growth in a dynamic area in Tangerang, Indonesia. This research developed micro-spatial load forecasting, which can show load centres in microgrids, estimate the capacity and locate the distribution station precisely. Homogenous grouping implemented the method into clusters consisted of microgrids. It involves multivariate variables containing 12 electric and non-electric variables. Multivariate analysis is conducted by carrying out Principal Component Analysis (PCA) and Factor Analysis. The forecasting results can predict load growth, time, and location, which can later be implemented as the basis of a master electricity distribution plan because it provides an accurate long-term forecast.