Abstract
Achieving universal access to electricity is a development challenge many countries are currently battling with. The advancement of information technology has, among others, vastly improved the availability of geographic data and information. That, in turn, has had a considerable impact on tracking progress as well as better informing decision making in the field of electrification. This paper provides an overview of open access geospatial data and GIS based electrification models aiming to support SDG7, while discussing their role in answering difficult policy questions. Upon those, an updated version of the Open Source Spatial Electrification Toolkit (OnSSET-2018) is introduced and tested against the case study of Malawi. At a cost of $1.83 billion the baseline scenario indicates that off-grid PV is the least cost electrification option for 67.4% Malawians, while grid extension can connect about 32.6% of population in 2030. Sensitivity analysis however, indicates that the electricity demand projection determines significantly both the least cost technology mix and the investment required, with the latter ranging between $1.65–7.78 billion.
Highlights
The 2030 Agenda for Sustainable Development has set the goal of universal access to electricity by 2030 (SDG7) [1]
Plan and the rural electrification plan (MAREP), grid generation capacity will gradually increase to Master Plan and the rural electrification plan (MAREP), grid generation capacity will gradually
We find that the to electricity target generated and in analysed that the total investment requirements achieve demand universal access the strongest determinant both electrification investment andthat gridthe penetration the totaltarget mix is to is electricity in Malawi ranges of between
Summary
The 2030 Agenda for Sustainable Development has set the goal of universal access to electricity by 2030 (SDG7) [1]. Coping with dilemmas of this nature—involving the deployment of big technological systems—requires thorough analysis of the social, technical, economic and political characteristics of the studied area or country [3]. This in turn, requires access to reliable data and information [4,5]; e.g., distribution and density of population settlements, electricity demand levels, resource availability, poverty rate and economic activity, distance from functional infrastructure (e.g., transmission and distribution network, roads, power stations) to name a few. MW [110], whereas the country’s current (actual and latent) import capacity estimated less than 30 MW [110], whereas the country’s current (actual and latent) demand as as much as 700. Grid extension currently provide to 31.6% oftorural population by 2030 [108]
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