# A Review of Health Assessment Techniques for Distribution Transformers in Smart Distribution Grids
## 4 Advanced Technologies for Real-Time Monitoring Transformer Condition in a Smart Distribution Grid  
Due to some economic aspects, the online condition monitoring system has not been directly implemented in distribution transformers in past times [75; 76]. However, with the new generation of the smart distribution grid, the internet of things (IoT), cloud computing, and advanced metering infrastructure are often combined in the electric power systems. This complex system can gather huge data and information, assisted by an array of new approaches, technologies and applications. The real-time data collection, transmission, data access, and rapid analysis of huge amounts of multivariate data are becoming the basis for sustaining the reliable operation of power systems. The development of these advanced technologies aims to optimize the operation of the distribution network, simplify the distribution transformer monitoring process but still ensure high accuracy. While the Internet of Things can help to track, monitor and manage electric equipment through connecting with the internet for information exchange, improve the communication platform of the smart grid. Cloud computing provides a solution to store huge amounts of data and process heavy computational work for transformer monitoring activities of the distribution grid. Many research studies have been implemented to take advantage of this smart management system. Because distribution transformers are critical assets and the load of a distribution transformer is governed by the end-user, which therefore makes it an uncontrollable load [58; 65], further uncertainty comes from PV integration at the distribution level as well as EV recharging facilities. Thus extensive and continuous monitoring is required. Most conventional diagnosis methods for distribution transformers were traditionally carried out off-line when the transformer was taken out of service. With the development of the information technology and smart sensors devices, the reliability of the transformer status assessment system can be carried out on line. The monitoring process is carried out online, in real-time, and thus the accuracy of the condition analysis for the transformer can be greatly improved. Real-time monitoring of transformers can help to find out the potential risks of failure for distribution transformers. For this reason, further analysis can be implemented to identify the development trend of the risks easily and help giving necessary decisions in time in order to avoid unexpected and catastrophic equipment shut-downs. Monitoring data is also stored on the cloud system and analyzed to assist in making decisions on the replacement and maintenance of distribution transformers in the future. In [77], an online transformer health monitoring system is proposed by using the global mobile service (GSM). A mobile-embedded system including a single-chip microcontroller and sensors is designed to monitor load currents, over-voltage, transformer oil level and oil temperature. If there is any abnormality in the system, the GSM module will send short message service (SMS) messages to designated mobile telephones containing information about the abnormality. After the fault clearing, the total system again starts to monitor the condition of the transformer. As it is a wireless communicating system, there is no need for high-cost large cables. In paper [78], GSM is also used to monitor distribution transformers' parameters such as current, temperature, oil level, vibration and humidity in every fifteen seconds. The monitoring process is implemented pretty the same with the described system in [79]. The microcontroller is the core of RTU that collects data from sensors nearby the transformer and sends data to monitoring nodes via GSM/GPRS module. GPRS has high efficiency, convenience and low cost and provides a good solution to meet the need of distribution transformer monitoring systems. Figure 6 presents the general flowchart of the monitoring systems.