Optimizing Spatial Input Data for Techno-Economic Modeling of Least-Cost Electrification Pathways in Zambia

Zambia’s current population is approximately 19.4 million, growing at an annual rate of about 2.9%. Only 40% of Zambia’s population has access to electricity, leaving roughly 11.7 million people without modern energy services. Since 2008, the Rural Electrification Authority of Za...

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Main Authors: Katundu Imasiku, Gregory Ireland, Alison Hughes
Format: Article
Language:English
Published: SDEWES Centre 2025-03-01
Series:Journal of Sustainable Development of Energy, Water and Environment Systems
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Online Access: http://www.sdewes.org/jsdewes/pid13.0549
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author Katundu Imasiku
Gregory Ireland
Alison Hughes
author_facet Katundu Imasiku
Gregory Ireland
Alison Hughes
author_sort Katundu Imasiku
collection DOAJ
description Zambia’s current population is approximately 19.4 million, growing at an annual rate of about 2.9%. Only 40% of Zambia’s population has access to electricity, leaving roughly 11.7 million people without modern energy services. Since 2008, the Rural Electrification Authority of Zambia embarked on an ambitious program to increase the rural electrification rate from 11% to about 51% by 2030. However, this goal may not be realized at the current electrification rate. This article presents an analysis of techno-economic electrification pathways for Zambia using the Open-Source Spatial Electrification Toolkit. While the Rural Electrification Authority of Zambia aims to increase electrification from 11% to 51%, this research targets achieving 100% access to electricity by 2030 to meet the United Nations Sustainable Development Goal 7.1. The study involves national-scale modeling of lowest-cost technology options for 750,000 distinct population settlement clusters, based on the least cost of electricity to supply electricity to settlements using a range of technologies while benchmarking the study with the Global Electrification Platform. In this study, data for Zambia was improved and validated by enhancing the accuracy of population clusters and the electricity grid network. This was achieved by combining several new datasets from gridfinder.org, Geo-Referenced Infrastructure, and Demographic Data for Development - three, WorldPop, the United States Agency for International Development Demographic and Health Surveys and engaging with the national Zambian Electricity Supply Company. The results are benchmarked against the latest publicly available scenarios in the Global Electrification Platform using the same version of the Open-Source Spatial Electrification code, thus only testing the effects of the population and grid datasets on the results. Remarkably great similarity of about 99.95% of the total investment cost requirement between the standalone solar system and the grid extension was realized by 2030 but with a 10% decrease in investments in grid extension. Standalone solar systems have seen a corresponding rise, primarily because the gridfinder.org dataset identified numerous false positive grids which refer to instances where a dataset incorrectly identifies areas as having existing electrical grid infrastructure when, in reality, they do not. Standalone solar systems are found to be less costly than grid extensions by a factor of 10, saving almost USD 33 million.
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spelling doaj-art-3a427697e02f47518489f0ec3953afef2025-08-20T02:06:27ZengSDEWES CentreJournal of Sustainable Development of Energy, Water and Environment Systems1848-92572025-03-0113111310.13044/j.sdewes.d13.05491130549Optimizing Spatial Input Data for Techno-Economic Modeling of Least-Cost Electrification Pathways in ZambiaKatundu Imasiku0Gregory Ireland1Alison Hughes2 Georgia Institute of Technology, Atlanta, United States University of cape town, Cape Town, South Africa University of cape town, Cape Town, South Africa Zambia’s current population is approximately 19.4 million, growing at an annual rate of about 2.9%. Only 40% of Zambia’s population has access to electricity, leaving roughly 11.7 million people without modern energy services. Since 2008, the Rural Electrification Authority of Zambia embarked on an ambitious program to increase the rural electrification rate from 11% to about 51% by 2030. However, this goal may not be realized at the current electrification rate. This article presents an analysis of techno-economic electrification pathways for Zambia using the Open-Source Spatial Electrification Toolkit. While the Rural Electrification Authority of Zambia aims to increase electrification from 11% to 51%, this research targets achieving 100% access to electricity by 2030 to meet the United Nations Sustainable Development Goal 7.1. The study involves national-scale modeling of lowest-cost technology options for 750,000 distinct population settlement clusters, based on the least cost of electricity to supply electricity to settlements using a range of technologies while benchmarking the study with the Global Electrification Platform. In this study, data for Zambia was improved and validated by enhancing the accuracy of population clusters and the electricity grid network. This was achieved by combining several new datasets from gridfinder.org, Geo-Referenced Infrastructure, and Demographic Data for Development - three, WorldPop, the United States Agency for International Development Demographic and Health Surveys and engaging with the national Zambian Electricity Supply Company. The results are benchmarked against the latest publicly available scenarios in the Global Electrification Platform using the same version of the Open-Source Spatial Electrification code, thus only testing the effects of the population and grid datasets on the results. Remarkably great similarity of about 99.95% of the total investment cost requirement between the standalone solar system and the grid extension was realized by 2030 but with a 10% decrease in investments in grid extension. Standalone solar systems have seen a corresponding rise, primarily because the gridfinder.org dataset identified numerous false positive grids which refer to instances where a dataset incorrectly identifies areas as having existing electrical grid infrastructure when, in reality, they do not. Standalone solar systems are found to be less costly than grid extensions by a factor of 10, saving almost USD 33 million. http://www.sdewes.org/jsdewes/pid13.0549 electrification; pathways; population; onsset; modeling; technologies; investment
spellingShingle Katundu Imasiku
Gregory Ireland
Alison Hughes
Optimizing Spatial Input Data for Techno-Economic Modeling of Least-Cost Electrification Pathways in Zambia
Journal of Sustainable Development of Energy, Water and Environment Systems
electrification; pathways; population; onsset; modeling; technologies; investment
title Optimizing Spatial Input Data for Techno-Economic Modeling of Least-Cost Electrification Pathways in Zambia
title_full Optimizing Spatial Input Data for Techno-Economic Modeling of Least-Cost Electrification Pathways in Zambia
title_fullStr Optimizing Spatial Input Data for Techno-Economic Modeling of Least-Cost Electrification Pathways in Zambia
title_full_unstemmed Optimizing Spatial Input Data for Techno-Economic Modeling of Least-Cost Electrification Pathways in Zambia
title_short Optimizing Spatial Input Data for Techno-Economic Modeling of Least-Cost Electrification Pathways in Zambia
title_sort optimizing spatial input data for techno economic modeling of least cost electrification pathways in zambia
topic electrification; pathways; population; onsset; modeling; technologies; investment
url http://www.sdewes.org/jsdewes/pid13.0549
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AT gregoryireland optimizingspatialinputdatafortechnoeconomicmodelingofleastcostelectrificationpathwaysinzambia
AT alisonhughes optimizingspatialinputdatafortechnoeconomicmodelingofleastcostelectrificationpathwaysinzambia