Abstract
The modern power grids are developing towards smartness with innovative electric power systems management by embracing Information and Communication Technology (ICT) systems in addition to other technologies for real-time control and monitoring. These systems rely on the use of sensors, which generate a lot data, for situation awareness and visibility. Approaches and techniques based on ICT-solutions for faults handling have advanced up to electrical transmission networks and not well addressed in electrical secondary (low voltage (LV)) distribution networks which are prone to various types of faults affecting a significant number of customers. Data-driven approaches with cloud-fog based system architecture have emerged as potential solution to address fault detection in these LV distribution networks. In this paper, an overview of cloud-fog based architectural design is presented for applications to enhance fault detection in electrical secondary distribution network. The proposed platform make use of microservice architecture to assist the distributed applications to effectively utilize the virtualized systems. Workflow and use case are also presented as well as techniques on addressing the required technological platforms for implementation to facilitate fault detection in the distribution networks.
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References
Green, R.C., Wang, L., Alam, M.: Applications and trends of high performance computing for electric power systems: focusing on smart grid. IEEE Trans. Smart Grid 4, 922–931 (2013)
Pant, V., Jain, S., Chauhan, R.: Integration of fog and IoT model for the future smart grid. In: 2017 International Conference on Emerging Trends in Computing and Communication Technologies, ICETCCT 2017, pp. 1–6 (2018)
Strachan, A., Elders, I., Galloway, S.: Improving network visibility for better integration of low carbon technologies into LV networks. In: Proceedings - 2018 53rd International Universities Power Engineering Conference, UPEC 2018, pp. 1–6 (2018)
Mnyanghwalo, D., Kawambwa, S., Mwifunyi, R., Gilbert, G.M., Makota, D., Mvungi, N.: Fault detection and monitoring in secondary electric distribution network based on distributed processing. In: 2018 20th International Middle East Power Systems Conference, MEPCON 2018 - Proceedings (2019)
Andegelile, Y., Chugulu, G., Bitebo, A., Mbembati, H., Kundaeli, H.: Enhancing faults monitoring in secondary electrical distribution network. Presented at the 1 May 2019
Forsyth, P., Nzimako, O., Peters, C., Moustafa, M.: Challenges of modeling electrical distribution networks in real-time. In: 2015 International Symposium on Smart Electric Distribution Systems and Technologies, pp. 556–559 (2015)
Barbato, A., Dedè, A., Della Giustina, D., Massa, G., Angioni, A., Lipari, G., Ponci, F., Repo, S.: Lessons learnt from real-time monitoring of the low voltage distribution network. Sustain. Energy Grids Netw. 15, 76–85 (2018)
Chen, Q., Kaleshi, D., Armour, S., Fan, Z.: Reconsidering the smart metering data collection frequency for distribution state estimation. In: 2014 IEEE International Conference on Smart Grid Communications (SmartGridComm), pp. 517–522. IEEE (2014)
Bonomi, F., Milito, R., Natarajan, P., Zhu, J.: Fog computing: a platform for internet of things and analytics. In: Studies in Computational Intelligence, pp. 169–186. Springer (2014)
Da Silva, W.M., Tomas, G.H.R.P., Dias, K.L., Alvaro, A., Afonso, R.A., Garcia, V.C.: Smart cities software architectures: a survey. In: Proceedings of the ACM Symposium on Applied Computing, pp. 1722–1727 (2013)
Kumar, T.S.: Efficient resource allocation and QoS enhancements of IoT with fog network. J. ISMAC 01, 21–30 (2019)
Vulcan, A.M., Nicolae, M.: High performance computing based on a smart grid approach. In: 2017 21st International Conference on Control Systems and Computer Science, pp. 651–655 (2017)
Production-Grade Container Orchestration – Kubernetes. https://kubernetes.io/
Enterprise Container Platform—Docker. https://www.docker.com/
What are microservices? https://microservices.io/
Yangui, S., Ravindran, P., Bibani, O., Glitho, R.H., Hadj-Alouane, N.B., Morrow, M.J., Polakos, P.A.: A platform as-a-service for hybrid cloud/fog environments. Presented at the June 2016
Mouradian, C., Naboulsi, D., Yangui, S., Glitho, R.H., Morrow, M.J., Polakos, P.A.: A comprehensive survey on fog computing: state-of-the-art and research challenges. IEEE Commun. Surv. Tutorials 20, 416–464 (2018)
Barik, R.K., Gudey, S.K., Reddy, G.G., Pant, M., Dubey, H., Mankodiya, K., Kumar, V.: FogGrid: leveraging fog computing for enhanced smart grid network. In: INDICON-2017 14th IEEE India Council International Conference, pp. 1–6 (2017)
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This work is supported by Swedish International Development Agency (SIDA) under IGRID project under University of Dar es Salaam.
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Gilbert, G.M., Naiman, S., Kimaro, H., Mvungi, N. (2020). A Cloud-Fog Based System Architecture for Enhancing Fault Detection in Electrical Secondary Distribution Network. In: Pandian, A., Palanisamy, R., Ntalianis, K. (eds) Proceeding of the International Conference on Computer Networks, Big Data and IoT (ICCBI - 2019). ICCBI 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 49. Springer, Cham. https://doi.org/10.1007/978-3-030-43192-1_92
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