Electrical Load Estimation and Management Approach of a Small Rural Community in Saudi Arabia

International Journal of Electrical and Electronics Engineering

© 2025 by SSRG - IJEEE Journal

Volume 12 Issue 10

Year of Publication : 2025

Authors : Mubarak Alanazi

10.14445/23488379/IJEEE-V12I10P101

How to Cite?

Mubarak Alanazi, "Electrical Load Estimation and Management Approach of a Small Rural Community in Saudi Arabia," SSRG International Journal of Electrical and Electronics Engineering, vol. 12,  no. 10, pp. 1-12, 2025. Crossref, https://doi.org/10.14445/23488379/IJEEE-V12I10P101

Abstract:

Global difficulties include problems with environmental, energy, and economic issues. Increasing energy capacity, especially electric power and its reliability, is motivated by people’s desire to raise their standard of living. One of the most important components of the electric power supply system is the electrical distribution system of residential buildings. The estimated electrical demand is a key factor affecting the design and construction of electrical energy systems. Houses’ functioning and design have always depended on the difficulty of precisely estimating electricity consumption and the highest possible electrical load. Due to the random nature of fluctuations in electrical consumption caused by population expansion and an increase in the number of electrical equipment in use, it is difficult to determine residential loads with any degree of accuracy. Renewable energy sources offer a competitive alternative for off-grid regions because fossil fuels are becoming scarce and extending the national grid is expensive. An electrical load estimation and management strategy for a small remote area with ten families in Hafar Al Batin, Northern Saudi Arabia, will be discussed in this paper. HOMER software was used to evaluate solar Photovoltaic (PV) and Wind Turbine (WT) systems in order to identify the best combinations. The study focuses on daily consumption patterns, seasonal load profiles, and load management techniques aimed at lowering peak demand. According to the results, efficient load shifting can lower the maximum load by up to 15.69%, increasing system efficiency and reducing energy costs.

Keywords:

Hybrid Renewable Energy System (HRES), Electrical Load Estimation, Load Management, Shifting Loads, Off-Grid Communities.

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