Cloud based power failure sensing and management model for the electricity grid in developing countries – a case of Zambia
Sinkala, Janet Nanyangwe
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In Zambia part of the electric grid is not monitored, this means that there are no sensors in the electric grid to enable grid status information to be sent to the power utility. Without these sensors the power utility finds it difficult to determine when there is a power failure in the distribution electric grid, especially if the power failure occurs in the Low Voltage level. Usually power failure management relies on humans. The customer with a telephone is the one whose call initiates the dispatch of a field crew to attend to power failures. However, this system of addressing power outages is not very effective and usually results in long durations of system interruptions which have a negative impact on the social economic activities of the country. This study proposes a cloud based power failure sensing system to enable automatic power failure sensing and reporting as well as monitoring of the low voltage power network. A baseline study was conducted to determine the challenges faced by both ZESCO (Service provider) and the electricity clients in the current power failure reporting management model. The results from the baseline study indicate that challenges are being faced by electricity clients when it comes to reporting power failures. These include failure to get through to the customer call centre due to busy lines, unanswered calls, failed calls and network failure. Challenges faced by the electricity service provider are the inability to attend to all the customers through the call centre as customer calls are rejected due to limited Call Centre system resources, difficulties in determining the power failure location and poor response to power failures reported. To address these challenges the proposed cloud based power failure sensor prototype made use of a Voltage sensor circuit, Arduino Microcontroller board, SIM7600E 4G/GPRS/GSM/GPS module, cloud architecture, Web Application and Google Map API. This research proves that automating the distribution network is necessary as the results from the proposed model show reduction in dependency on customer trouble calls, improved power failure reporting time, automatic update of power failure location information, power utility visibility of the grid and quick response to power failures resulting in reduced outage durations. The results of this research were successfully published in the International Journal of Advanced Computer Science and Applications (IJACSA) Journal Volume 11 Issue 2 February 2020. Key words – Cloud Technology, power failure sensing, low voltage network, electric grid, cloud architecture.
The University of Zambia
- Engineering