Enhancing Service Restoration in Tanzanian Power Grid using Internet of Things Sensors and Renewable Energy Sources

The increased dependence on the electric power grid, coupled with the increasing number of new customers, motivates the need to improve the reliability and resilience of the electric distribution systems. Modern distribution systems are becoming more resilient against power outages due to the increasing integration of Distributed Energy Resources (DERs) and the availability of efficient mechanisms for load shedding. Several studies considered fault detection and Service Restoration (SR) as separate problems without considering the implementation feasibility of integrating both solutions. To ensure the resiliency in the power system, it is important to have proper mechanisms which integrate sensing, detection, and SR as one problem while considering the load shedding and DER for improved capacity. Hence, this study proposed an IoT-based-sensor network framework with an enhanced algorithm coupled with a Binary Bat metaheuristic algorithm for SR integrating sensing, detection, and restoration. The proposed algorithms have been tested in Tanzania's electrical distribution network, considering the inclusion of DERs and load shedding. The results showed that DERs' size and locations significantly impact restoration schemes' performance with a power loss reduction of 74%. Therefore, efficient SR schemes should consider optimal DERs placement and a combination of load shedding and DERs integration for improved performance.