# Sensor Technologies for Transmission and Distribution Systems: A Review of the Latest Developments
## 3 Key Transmission and Distribution System Components
### Power Transformers
These forces create axial and radial forces that might lead to the movement of winding, indentation on windings called buckling, or spacing between the discs. Special Hall effect sensors [57] mounted on the transformer windings can sense the change in leakage flux with winding deformations and help in minimizing the amount of repair and the repair time, saving thousands of dollars. Sensors on Power Transmission Transformers vs. Power Distribution Transformers  
Despite having similar components and working principles which results in similar faults as described above for power transmission transformers, power distribution transformers differ in their sizes, ratings, and costs. Power distribution transformers are generally smaller in size, with ratings ranging from 11 KV, 6.6 kV, 3.3 kV, 440 v, and 230 volts, whereas the ratings of power transmission transformers which deal with significantly higher voltages of the transmission lines can range from 400 kV, 200 kV, 66 kV, and 33 kV [58]. Due to lesser sizes and ratings, the price of power distribution transformers can be as little as $700 [17]. Hence, the fault detection and health assessment solutions for distribution transformers must be economical [17], since it won't make sense to have sensors and wireless sensors systems that are more expensive than the transformer itself. Distribution transformers are either pole mounted with oil-based, polymeric, or air-based insulation or substation-based with only oil-type insulation. Apart from the faults discussed above for power transmission transformers, power distribution transformers also undergo insulation failures such as water accumulation, aging or thermal degradation of polymeric paper. Furthermore, distribution transformers are more prone to overloading and unbalanced loading. This is because distribution transformers are generally governed by the end-user or the consumer, making them an uncontrollable load [59]. Uncertainty in load, especially with the recent integration of PV, EV charging stations, etc., further contributes to this cause. Overloading and unbalanced loading can distort the normal circulation of a current, thereby increasing the winding and oil temperatures, resulting in subsequent winding failure and insulation degradation. However, due to the economic aspects, winding temperatures are selected as the primary monitoring parameter [60], and other parameters like changes in current, aging, etc., are detected from the change in winding temperature [61]. For temperature monitoring, distributed temperature sensors are placed on the distribution transformer windings. Recently, fiber optic sensors are being popularly used due to their accuracy in hot spot determination. Furthermore, fiber optic sensors are low in cost and size and can provide measurements during in-service operation with immunity to electromagnetic interference [16; 62]. In addition, various machine learning techniques are being employed to forecast winding temperatures and to build a thermal model to predict anomalies in thermal behavior in the future. Ref. [63] proposes an online transformer health monitoring system using the global mobile service (GSM) with a resolution of 15 s to improve the monitoring process. However, the use of GSM modules and microcontrollers makes the system expensive. Ref. [64] uses a low-cost solution to utilize the data collected from advanced metering infrastructure (AMI) meters for distribution grid asset management. To reduce the amount of data complexity, Ref. [65] uses hourly usage data from AMI and SCADA to determine distribution power transformer failures and overload. The model also uses a geospatial information system (GIS) for geolocation of distribution system instruments and its faults and a customer information system (CIS) for a database of historical information of customer loads and outages. Apart from this, studies are ongoing to introduce low-cost health condition monitoring of power distribution transformers with IoT for smart grids [66; 67; 68].