Cloud computing in the smart grid context: an application to aid fault location in distribution systems concerning the multiple estimation problem

Abstract

Cloud computing has been envisioned as the main technology capable of integrating and managing many systems in a smart grid (SG). Thus, this research aims to develop a cloud computing infrastructure to store and manipulate smart distribution system data. To do this, extensible architecture with essential services was proposed to be integrated into an advanced metering infrastructure to host new applications in smart distribution systems. Based on this proposition, a cloud computing platform was developed using open source tools. A new application to reduce multiple estimation for fault location in radial distribution systems using data mining techniques over smart meter data was implemented. An optimised version of the data mining tool known as DAMICORE (DAta MIning of COde REpositories) was implemented as an extension to the proposed architecture basic services. The new cloud application was tested using hundreds of fault simulations on a test feeder and was able to reduce multiple estimation by more than 90% in the simulated fault cases. The results show that the proposed cloud computing architecture and infrastructure enable new smart distribution system applications, contributing to the development of SGs and diffusion of cloud computing in this context.