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Special Graduate Schools
Graduate School of International Studies
Department of Energy Studies
3. Theses(Master)
ASSESSING THE RELIABILITY OF THE ELECTRICITY DISTRIBUTION SYSTEM IN GHANA
- Author(s)
- NTI KWAKU
- Advisor
- Jaesung Jung
- Department
- 국제대학원 융합에너지학과
- Publisher
- Graduate School of International Studies Ajou University
- Publication Year
- 2020-02
- Language
- eng
- Keyword
- Energy studies
- Alternative Abstract
- Erratic power outages in Ghana have made reliability of electricity supply a top priority to regulators, utilities and consumers alike. The term “Dumsor” became common on the lips of Ghanaians from 2009 to 2016 during the peak of the power outages[1]. This term signified the frequent nature of the outages. Consumers in emerging countries are now very sensitive to power outages. This is due to the change in their taste resulting from the increase in industries and the standard of living. The impact of power outages are now very costly, making the access to high quality and reliable electricity a crucial agendum for governments in emerging countries [2]. This study sought to evaluate the performance of the electricity system in Ghana by identifying the reliability indices of the biggest utility for the last 10 years. It also identified factors that causes variation in the identified indices. Lastly it benchmarked the performance of Ghana to peer income countries that meet Ghana’s standards. The System Average Interruption Frequency and Duration Indices (SAIFI and SAIDI) values from 2009 to 2018 were identified from reports or computed using information from log books. The CAIDI and ASAI values for the same period were also computed from the SAIFI and SAIDI values. Independent variables on which variations in SAIFI and SAIDI potentially depended were requested from experts at the Energy Commission of Ghana. Two of the variables, namely Sales of ECG and tariff set by government were confirmed to be significant in explaining variations in the SAIDI values by using correlation and multiple regression analysis. All the independent variables tested for SAIFI were shown not to be significant variables. The researcher concluded that other factors such as ageing of the equipment and technology innovations in the distribution system which could not be tested due to lack of data were likely to be the significant independent variables for SAIFI. Using a DEA model with SAIFI and SAIDI as outputs and tariff and sales of the decision making units as inputs, Bhutan and Uzbekistan were selected as the benchmarking targets for Ghana.
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