# Sensor Technologies for Transmission and Distribution Systems: A Review of the Latest Developments
## 4 Outlook
For example, currently, advanced automation schemes such as fault location, isolation, and service restoration systems (FLISR) [138] are being deployed in distribution systems that are controlled in real time by SCADA. They provide support for the enabling of DERs and improve distribution automation with efficient fault localization. The current trend in the modern-day sensor technology is the integration of multiple sensors and other connected devices to form wireless sensing networks (WSN). The deployment of WSNs in the transmission and distribution systems is unique since it is an advanced technology facilitating not only efficient data acquisition but also data transmission and data processing to provide complete real-time monitoring of the grid. WSNs enable pervasive sensing among the transmission and distribution system components for fault measurements as well as the continuous monitoring of power system components for state estimations and forecasting [3]. This pervasive sensing network framework in power systems is depicted in Figure 4. The figure clearly demarcates the three major layers that constitute WSNs [2] that are deployed in transmission and distribution systems. The first layer is the perception layer or the input layer. It consists of the deployment of multiple sensors on various components of the transmission and distribution system. These sensors are often referred to as input sensors or source sensor nodes. The sensor nodes can also contain a sensor module along with a processor module for data processing, a wireless communication module for data transmission, and an energy management module to supply power to the other modules [139]. These sensor nodes can be deployed remotely to acquire raw grid parameter values essential for monitoring individual grid components. These sensor nodes can form part of a bigger assembly of sensors constituting SCADAs, PMUs, and MUs, for time synchronized data acquisition. The raw grid parameter values acquired can be interfaced with hardware for processing or control purposes through remote terminal units and programmable logic controller devices. The second layer facilitates the transmission of the raw grid parameter data into the application layer for further processing. The network layer broadly consists of two networks for data transmission called the core networks and the access networks [140]. The core networks are responsible for the wired transmission of data, especially with the help of optical fiber as a network channel. Access networks enable data transmission through wireless communication systems. Various modern wireless communication technologies [141] such as Wi-Fi, LoRa, NB-IoT, ZigBee, and satellites can be employed here. The third layer is called the application layer. This layer constitutes several application infrastructures, middleware, and application systems like SCADA servers and SCADA dashboards, where the transmitted data is analyzed, generally by operator personnel. The grid parameter data can also be processed in the application layer for the detection of developing fault features for online transmission system monitoring  
Figure 3: Timeline for development of modern sensor technology. and online distribution system monitoring or online individual equipment monitoring. Intelligent computing with machine learning techniques can be used to process the raw grid parameter data for fault classification and fault forecasting, leading to the predictive maintenance of the system. This in turn forms an outage management system [142] for the transmission and distribution system components. Hence, through this process, pervasive sensing with WSN is realized in transmission and distribution systems. The future development of sensors must consider certain unique features of the future power grids and the upcoming smart grids.