A High-Resolution Analysis of Electricity Demand for Informed Electrification Planning

Electrification planning necessitates a nuanced understanding of electricity demand. However, previous studies have largely overlooked regional differences and relied on a one-size-fits-all approach to demand estimation. This study aims to examine the spatial distribution of electricity demand across households and community institutions in a developing country context, using Ethiopia as a case for the study. The study employed a multifaceted approach: household demand was estimated using the Multi-Tier Framework (MTF), while the demand for community institutions (healthcare, education facilities, places of worship, and government offices) was estimated using the Remote-Areas Multi-energy systems load Profiles (RAMP) stochastic model. The spatial distribution was visualized using the OnSSET methodology. The findings reveal significant demand heterogeneity, with 64% of households falling within Tier 1 and Tier 2 demand levels assuming all households have electricity access, but 61.3% of currently electrified households exhibit Tier 3 in 2020. Additionally, community institutions exhibited electricity demand patterns, with health facilities requiring the highest average demand (around 2,100 kWh/year), followed by education facilities (400 kWh/year). Insights from these high-resolution demand assessments can inform the selection of cost-optimal electrification technologies (e.g., grid extension, mini-grids, standalone systems) based on the demand patterns of specific communities at local level in Ethiopia.

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Publication Details

Published
2024-10-07
DOI
https://doi.org/10.1109/powerafrica61624.2024.10759429
Citations
2
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.42
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article

A High-Resolution Analysis of Electricity Demand for Informed Electrification Planning

Adugnaw Lake Temesgen, Erik O. Ahlgren, Basilio Zeloso S. Tamele
2 citations
Electric Vehicles and Infrastructure
0.42
article

A High-Resolution Analysis of Electricity Demand for Informed Electrification Planning

Adugnaw Lake Temesgen, Erik O. Ahlgren, Basilio Zeloso S. Tamele
article en
2 citations

Abstract

Electrification planning necessitates a nuanced understanding of electricity demand. However, previous studies have largely overlooked regional differences and relied on a one-size-fits-all approach to demand estimation. This study aims to examine the spatial distribution of electricity demand across households and community institutions in a developing country context, using Ethiopia as a case for the study. The study employed a multifaceted approach: household demand was estimated using the Multi-Tier Framework (MTF), while the demand for community institutions (healthcare, education facilities, places of worship, and government offices) was estimated using the Remote-Areas Multi-energy systems load Profiles (RAMP) stochastic model. The spatial distribution was visualized using the OnSSET methodology. The findings reveal significant demand heterogeneity, with 64% of households falling within Tier 1 and Tier 2 demand levels assuming all households have electricity access, but 61.3% of currently electrified households exhibit Tier 3 in 2020. Additionally, community institutions exhibited electricity demand patterns, with health facilities requiring the highest average demand (around 2,100 kWh/year), followed by education facilities (400 kWh/year). Insights from these high-resolution demand assessments can inform the selection of cost-optimal electrification technologies (e.g., grid extension, mini-grids, standalone systems) based on the demand patterns of specific communities at local level in Ethiopia.

Eduardo Mondlane University (MZ), Addis Ababa University (ET), Chalmers University of Technology (SE)
Openalex Percentile: Top 36%
Electric Vehicles and Infrastructure
0.42
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A High-Resolution Analysis of Electricity Demand for Informed Electrification Planning — Adugnaw Lake Temesgen, Erik O. Ahlgren, et al. · (2024) | TGRS Research Map | TGRS