User-Centred Scalable Big Data Visualizer for Power Consumption Data in the Electrical Secondary Distribution Network

Authors

DOI:

https://doi.org/10.52339/tjet.v39i2.704

Keywords:

Smart Grid, Big Data Visualization, Visualization Models, Tanzania

Abstract

Establishment of Smart Grids for electrical power has been practised worldwide for the purpose of bringing reliability, security, and efficient management of electrical power networks for enhancing quality service to the society. Apart from the potential aim, smart grid has been a challenge to developing countries, including Tanzania from cost and technology point of view. Due to the use of many smart equipment involved in smart grids like Advanced Metering Infrastructure (AMI) equipped with smart meters and sensors, handling and managing big data has been a challenge. Among the challenges is the issue of visualizing the Big Data due to big volume generated with high velocity. This paper is developing a user-centered scalable big data visualizer for the electrical secondary distribution network by making use of design process model by Akanmu et al. (2017) and design activity framework by McKenna et al. (2014). The approach involves three phases: pre- development, development and post-development phase. The paper reviews several approaches in visualization and demonstrates effective big data visualization. The paper managed to visualize households’ units purchased against power consumed as well as balancing visualization of transformer phases.

Downloads

Download data is not yet available.

Author Biographies

Lucina Lawi, University of Dar es Salaam

University of Dar es Salaam Computing Centre

Ellen A. Kalinga, University of Dar es Salaam

Department of Computer Science and Engineering

Downloads

Published

2020-12-31

How to Cite

Lawi, L., & Kalinga, E. (2020). User-Centred Scalable Big Data Visualizer for Power Consumption Data in the Electrical Secondary Distribution Network. Tanzania Journal of Engineering and Technology, 39(2), 177-197. https://doi.org/10.52339/tjet.v39i2.704
Abstract viewed = 113 times