Spatial analysis of electrical distribution system in obio-akpor local government area, rivers state, Nigeria

Dolly Nkere Emmanuel 1, *, Moses Olaniran Olawole 2, Ademuyiwa Oyewumi 1, Nnaemeka Michael Ihenacho 1, Sumaiyat Kpanja Abdullahi 1, Princess Ifeyinwa Ezeanya 1 and Ezekiel Ojei 1

1 National Space Research and Development Agency (NASRDA), Nigeria.
2 Africould Regional Centre for Space Science and Technology Education- English (Arcsste-E), Ile-Ife, Osun State, Nigeria.
Research Article
World Journal of Advanced Research and Reviews, 2024, 22(03), 840–850
Article DOI: 10.30574/wjarr.2024.22.3.1736


Publication history: 
Received on 30 April 2024; revised on 08 June 2024; accepted on 11 June 2024
The distributions of quality electrical energy to end users and, achieving a reasonable level of customer’s satisfaction from the electricity distribution companies servicing most area are faced with divers’ spatial problems particularly with the use of dilapidated infrastructures and poor services. This study used spatial techniques to analyze the spatial characteristics of the electrical distribution system in Obio-Akpor Local Government Area, Rivers State. It also examined the ward pattern of Port Harcourt Electricity Distribution (PHED) customer’s satisfaction and also predicted the ward level of customer’s satisfaction within the study area. Primary and secondary data were used for the study. The primary data on customer’s satisfaction of PHED services was obtained from questionnaire survey. Purposive sampling method was used for this study and the population for the study is the entire customers of PHED in the study area. The secondary data consist of ward boundary map of the study area, satellite image, PHED network spatial data and attribute data of all the 3200 (three thousand two hundred) transformers (11/0.415KVA and 33/0.415KVA) within the study area as at the time of this study. Geospatial analysis such as clip analysis, buffering were carried. The data attribute were analyzed using average nearest neighbor analysis, kernel density, zonal statistics, inverse distance weighting and geographical weighted regression to obtain the desired aim of the study. The result show that, the location pattern of PHED transformers are clustered. Result further reveal that the ward pattern of customer’s satisfaction are geography dependent with either positive, negative or mixed relationship.
GIS; Electrical Distribution; Transformer; Customer Satisfaction; PHED; Geographical Weighted Regression; Nearest Neighbor Analysis
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