Cloud Based IoT Solution for Fault Detection and Localization in Power Distribution Systems

Mussawir Ul Mehmood, Abasin Ulasyar, Abraiz Khattak, Kashif Imran, Haris Sheh Zad and Shibli Nisar
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Mussawir Ul Mehmood: Department of Electrical Power Engineering, USPCAS-E, National University of Sciences and Technology, Islamabad 44000, Pakistan
Abasin Ulasyar: Department of Electrical Power Engineering, USPCAS-E, National University of Sciences and Technology, Islamabad 44000, Pakistan
Abraiz Khattak: Department of Electrical Power Engineering, USPCAS-E, National University of Sciences and Technology, Islamabad 44000, Pakistan
Kashif Imran: Department of Electrical Power Engineering, USPCAS-E, National University of Sciences and Technology, Islamabad 44000, Pakistan
Haris Sheh Zad: Department of Electrical Engineering, Riphah International University, Islamabad 44000, Pakistan
Shibli Nisar: Military College of Signals (MCS), National University of Sciences and Technology, Islamabad 44000, Pakistan

Energies, 2020, vol. 13, issue 11, 1-19

Abstract: Power restoring time in power distribution systems (PDS) can be minimized by using efficient fault localization techniques. This paper proposes a novel, robust and scalable cloud based internet of things (IoT) solution for identification and localization of faults in PDS. For this purpose, a new algorithm is developed that can detect single and multiple simultaneous faults in the presence of single and multiple device or sensor failures. The algorithm has utilized a zone based approach that divides a PDS into different zones. A current sensing device (CSD) was deployed at the boundary of a zone. The function of CSD is to provide time synchronized current measurements and communicate with a cloud server through an edge device (ED). Another contribution of this research work is the unique implementation of context aware policy (CAP) in ED. Due to CAP, only those measurements are transmitted to cloud server that differ from the previously transmitted measurements. The cloud server performed calculations at regular intervals to detect faults in PDS. A relational database model was utilized to log various fault events that occur in PDS. An IEEE 37 node test feeder was selected as PDS to observe the performance of our solution. Two test cases were designed to simulate individual and multiple simultaneous faults in PDS. A third test case was implemented to demonstrate the robustness and scalability of proposed solution to detect multiple simultaneous faults in PDS when single and multiple sensor failures were encountered. It was observed that the new algorithm successfully localized the faults for all the three cases. Consequently, significant reductions were noticed in the amount of data that was sent to the cloud server. In the end, a comparison study of a proposed solution was performed with existing methods to further highlight the benefits of our technique.

Keywords: IoT; cloud computing; fault localization; power distribution systems; MQTT; fault identification; edge intelligence (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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