@Article{ee.2026.087021,
AUTHOR = {Quintão Fátima dos Santos, Jangkung Raharjo, Sudarmono Sasmono},
TITLE = {Electricity Load Growth Projection Based on Customer Sector in Ermera District, Timor-Leste, Using Spatial Projection Method},
JOURNAL = {Energy Engineering},
VOLUME = {},
YEAR = {},
NUMBER = {},
PAGES = {{pages}},
URL = {http://www.techscience.com/energy/online/detail/27993},
ISSN = {1546-0118},
ABSTRACT = {This study presents an analysis of electricity load growth projections in Ermera District, Timor-Leste, using spatial projection methods. Accurate electricity load growth projection is a vital component of long-term power system planning, infrastructure investment, and resource allocation. In developing countries like Timor-Leste, increasing population and economic expansion drive a continuous rise in energy demand. This study develops an electricity load growth projection model based on specific customer sectors (domestic, commercial, industrial, social, and government) in the Ermera District, Timor-Leste, utilizing spatial projection methods integrated with Geographic Information Systems (GIS) and the Gompertz growth equation. Ermera District, characterized by its mountainous topography and prominent coffee production sector, currently faces electrification challenges with a regional electrification ratio of approximately 75%, falling below the national average of 83.4%. Historical data from 2021 to 2024 reveals a significant and synchronized expansion of the electricity customer base, surging from 3367 to 8532 customers. The domestic sector consistently represents the primary driver of total energy consumption, accounting for approximately 85% of the total customer base. Spatial analysis identifies the sub-districts of Ermera, Railaco, and Atsabe as the highest customer-density zones and future socio-economic hotspots. By employing a spatial projection method tuned to the regional context, the mathematical models successfully minimized validation deviations against recorded Electricidade de Timor-Leste (EDTL) data to a Mean Absolute Percentage Error (MAPE) threshold below 10%, highlighting the superior accuracy of spatial modeling over conventional methods in handling topographical variability. The Gompertz equation was applied to model long-term trends, projecting a rapid acceleration phase for the 2025–2030 planning cycle, with predicted cumulative demand escalating from 595,365 kW in 2025 to 1,120,610 kW by 2030. To evaluate network implications, peak demand scenarios were simulated using the Electrical Transient Analyzer Program (ETAP). The power flow simulations exposed recurrent technical limitations across the distribution network, particularly marginal under-voltage conditions (0.38–0.39 kV on the low-voltage side) on peripheral buses along the extended Ermera and Letefoho feeders, alongside transformer loading risks during peak hours. To mitigate these issues and optimize grid reliability, this thesis proposes critical engineering interventions, including the strategic activation of capacitor banks, distribution transformer tap changer optimizations, phase load balancing, and network reconductoring to lower line impedance. Ultimately, these findings offer a comprehensive, spatially explicit framework to support sustainable infrastructure expansion and energy policy formulation in the Ermera District.},
DOI = {10.32604/ee.2026.087021}
}