Mapping and Spatial Analysis of Electricity Load Shedding Experiences: A Case Study of Communities in Accra, Ghana

Nduhuura, Paul, Garschagen, Matthias and Zerga, Abdellatif, (2020). Mapping and Spatial Analysis of Electricity Load Shedding Experiences: A Case Study of Communities in Accra, Ghana. Energies, 13(4280), 1-26

Document type:
Article
Collection:
UNU-EHS Articles

Metadata
Documents
Links
Versions
Statistics
  • Attached Files (Some files may be inaccessible until you login with your UNU Collections credentials)
    Name Description MIMEType Size Downloads
    energies-13-04280_META.pdf energies-13-04280_META.pdf application/pdf 1.52MB
  • Sub-type Journal article
    Author Nduhuura, Paul
    Garschagen, Matthias
    Zerga, Abdellatif
    Title Mapping and Spatial Analysis of Electricity Load Shedding Experiences: A Case Study of Communities in Accra, Ghana
    Appearing in Energies
    Volume 13
    Issue No. 4280
    Publication Date 2020-08-19
    Place of Publication Basel
    Publisher MDPI
    Start page 1
    End page 26
    Language eng
    Abstract In many developing countries, electricity outages occur frequently with consequences for sustainable development. Moreover, within a country, region or city, the distribution of outages and their resultant impacts often vary from one locality to another. However, due to data constraints, local-scale variations in outage experiences have seldom been examined in African countries. In this study, a spatial approach is used to estimate and compare exposure to electricity load shedding outages across communities in the city of Accra, Ghana. Geographic Information System and statistics from the 2015 rolling blackouts are used to quantify neighborhood-level load shedding experiences and examine for spatial patterns. The results show that annual load shedding exposure varied greatly, ranging from 1117 to 3244 h. The exposure values exhibit statistically significant spatial clustering (Moran’s I = 0.3329, p < 0.01). Several neighborhoods classified as load shedding hot or cold spots, clusters and outliers are also identified. Using a spatial approach to quantify load shedding exposure was helpful for overcoming the limitations of lack of fine-grained, micro-level outage data that is often necessary for such an analysis. This approach can therefore be used in other data-constrained cities and regions. The significant global spatial autocorrelation of load-shedding exposure values also suggests influence by underlying spatial processes in shaping the distribution of load shedding experiences. The resultant exposure maps provide vital information on spatial disparities in load shedding implementation, which can be used to influence decisions and policies towards all-inclusive and sustainable electrification.
    UNBIS Thesaurus GHANA
    Keyword Electricity outage
    Spatial analysis
    Neighborhoods
    Load shedding
    Copyright Holder The Authors
    Copyright Year 2020
    Copyright type Creative commons
    DOI 10.3390/en13174280
  • Versions
    Version Filter Type
  • Citation counts
    Google Scholar Search Google Scholar
    Access Statistics: 483 Abstract Views, 1234 File Downloads  -  Detailed Statistics
    Created: Wed, 16 Sep 2020, 22:55:15 JST by Aarti Basnyat on behalf of UNU EHS