The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-4/W16
https://doi.org/10.5194/isprs-archives-XLII-4-W16-729-2019
https://doi.org/10.5194/isprs-archives-XLII-4-W16-729-2019
01 Oct 2019
 | 01 Oct 2019

BOUNDARY RE-ASSESSMENT OF THE METER READING UNIT (MRU) FOR TENAGA NASIONAL BERHAD, TNB CHERAS

A. Zulkflee, M. F. Abdul Khanan, H. A. Umar, M. Z. Abdul Rahman, and F. Nik Mohd Kamil

Keywords: boundary, meter reading unit (MRU), GIS, clustering analysis, network analysis

Abstract. The propensity of Geographic information systems (GIS) as a modelling tool for problems solving and spatial data analysis is remarkable and has been widely used in recent times. GIS applications has been utilized by Tenaga Nasional Berhad (TNB) in solving numerous problems. However, there are other units within the TNB where GIS can be extended and incorporated in order to improve service efficiency, reliability and operational success. Remote meter reading (RMR) technology has been successfully extended and maintain by TNB to more than 70% of highly consumed customers, which tremendously assist in improving meter reading processes and curtailed technical losses. But growing population within the cities and surrounding villages has been the major issue regarding bill distribution which the giant electrical distribution company must address squarely and timely. This paper therefore, employed the application of Geographic Information System in re-assessing the boundaries for meter reading units (MRU) using spatial analysis in order to reduced cost, travel time as well as other logistic requirements regarding billing distribution by TNB personnel. Clustering and network analysis has been employed to generate the new MRU boundary for TNB. The result of clustering analysis has been used to consider the location of customers in new suggested group of clusters, while the network analysis result generates shorter distance routes for meter reading. The results of the analysis can be validated with the analysis graph, where the patterns of the distance are compared in a graph which shows the distance generated from the new suggested cluster of new MRU boundary decrease incrementally compared with the distance of existing MRU routes.