Application of Industry 4.0 Technology and Internet of Things in Power Transmission Protection, Monitoring and Asset Management

Industry 4.0 is used interchangeably with the fourth industrial revolution and the Internet of Things (IoT) is the key driver in this entire value chain. IoT is a cyber-physical system which essentially includes smart sensors, actuators, and gateways that are networked to communicate a stream of data to the data analytic platform. The advances in communication technology, computational technologies and data analytics allow effective monitoring and predictive control of the physical system. IoT is being applied in various domains ranging from factories, transportation, power grids and buildings with a common aim to make them smart and enhance value to their stakeholders. Supervisory Control and Data Acquisition (SCADA) was the most preferred domain in an electric grid substation where we could see the IoT concepts being implemented some four to five decades back. With the advent of newer Information and Communication Technologies (ICT), there is an urge for more effective monitoring and predictive controls of the assets in a transmission system which in turn will enhance the reliability, availability and overall efficiency of the system. IoT technology can be applied in transmission and distribution sectors to improve reliability and availability at a reduced cost which might be beneficial to the utilities as well as end customers. This paper reviews the IoT readiness of EHV substations in transmission systems and also the gaps which need to be filled whilst its implementation. Major components considered in a typical transmission system are High Voltage Primary Equipment, Station Auxiliaries, Transmission Lines and Control Buildings wherein the smart sensors are embedded in form of meters, transducers, potential free dry contacts, communication ports on legacy protocols and other communicable IoT devices. These transmission assets can be protected and monitored concerning their operating parameters and their health to decide upon the asset management strategy.