# Sensor Technologies for Transmission and Distribution Systems: A Review of the Latest Developments
## 4 Outlook

Table 2: _Cont._This made the sensors versatile and enabled them to measure several other fault indicators such as temperature, acoustics, pressure, chemicals, and gas. Phase 3 is referred to as digitalization, which resembles the period where system size, system speed and system integration were given greater importance by the researchers. Since the sensors not only measured the values under observation but were also capable of detecting small changes in them, it was realized that they could be used for fault detection purposes. Hence, it was the need of the hour to have sensors that could function faster and measure multiple components of the grid for fault detection. Developments in the semiconductor industry in the 1960s with the fabrication of system-on-chip devices were a breakthrough that paved way for high performance but low-powered and lightweight sensors that replaced the bulky and lossy measuring instruments on the power grid [63]. These features made it possible for the sensors to be installed remotely and increased the visibility of the grid components, especially those that were installed outside the substations. In the 1970s, the Supervisory Control and Data Acquisition system was invented and deployed in the power grid. This facilitated the deployment of monitoring instruments and sensors that had faster response times and that could initiate local protective actions such as the action of circuit breakers, reclosers, and isolators. However, these sensors had lower sampling rates that were insufficient in the detection of details of transient phenomena that occurred in mere milliseconds. To capture this underlying data for optimum asset utilization, fast acting sensors and switches were deployed in the late 1980s. Phase 4 is the smart systems integration. It represents the current period where researchers are more focused on developing smart sensors that can enable pervasive sensing with system integration and realize system miniaturization. In the early 1990s, MEMS technology was integrated with sensors that improved their accuracy and sensitivity to detect multiple grid parameters. Next, the early 2000s saw the integration of sensors with phase measuring units and measuring units which enabled real-time monitoring with very high sampling rates. Furthermore, the sensor technology matured from the deployment of single sensing devices to its incorporation with SCADAs, PMUs, and MUs, constituting the wide area monitoring systems for complete, synchronized, and digital monitoring of various components of the power grid. Currently, power system operators demand SCADA- and PMU-based real time data to monitor the dynamic power flow of the grid. With the help of these real time grid parameters, responses to emergency, fault and failure events are swift, thereby improving power security. Therefore, SCADAs and PMUs form an integral part of the online dynamic security assessment (DSA) systems [136]. Real time and online system measurements obtained from them are used for system estimation and system modeling to perform power system security analysis. A range of various off-line applications such as validating system models, operations planning, diagnostics, and post-event analyses, etc. are also conducted with these measurements [137]. When this is combined with newer software developments, advanced machine learning based algorithms with improved computational capabilities, and matured fiber optic based wired or wireless communication technologies using Wi-Fi, LoRa, ZigBee, and NB-IOT, [65] advanced applications such as \"faster than real-time\" state estimation [18], predictive controls, and rapid contingency analyses are realized. This creates a pervasive sensing network architecture for the power grid as modeled in Figure 4. Furthermore, the sensor data from equipment monitoring is also integrated into control systems, and new control strategies are devised to deal with the risks of equipment failures, etc.