Author :
Bahramirad, Shay ; Svachula, Joseph ; Juna, John
Abstract :
The convergence of information technology (IT) with the 20th-century power grid has resulted in the development of smart electricity grids in the 21st century. The ultimate goal in the introduction of IT is to achieve an adaptable, secure, reliable, resilient, and flexible power grid that is able to address current and future reliability, economic, and environmental challenges. The application of IT has also resulted in myriad sensors and measurement and monitoring devices, among others, for enabling real-time, more intelligent control of the electricity infrastructure. Communication sensors often gather much more data than required for their intended applications in power grids. The storage and utilization of such data allows further applications in power grids, ranging from real-time alarm processing of potential grid violations and directing maintenance crews to trouble spots during major storm events to finding seasonal trends in deteriorating power quality levels. The collected data (labeled “big data” in the literature) require efficient storage, processing, and analytics, which is a major challenge for large utilities worldwide. In addition, if the collected data are not accurately analyzed for management decision making in utility companies, the envisioned benefits of the smart grid will not be fully captured and investments will be wasted. The ultimate goal for utilizing a smart grid is to efficiently integrate big data with diverse sets of applications and enhance the operations and control of electricity grids for addressing the energy needs and challenges in an evolving environment.
Keywords :
Big Data; decision making; power engineering computing; smart power grids; storage management; Big Data; IT; communication sensors; data storage; data utilization; electricity infrastructure; flexible power grid; information technology; intelligent control; management decision making; monitoring devices; myriad sensors; power quality levels; real-time alarm processing; smart electricity grids; utility companies; Data handling; Data storage systems; Distributed databases; Information analysis; Information management; Smart grids; Trust management;