Power transmission lines remain on maximum loading condition in hot summers. Due to this overloading, the connected grid station has severe red hot spots on the junction points in the switchyards. As a result, most of the times pitting happens and sometimes it leads to a breakdown. A grid station no
Temperature profiling of an electric grid using unmanned aerial vehicle
Power transmission lines remain on maximum loading condition in hot summers. Due to this overloading, the connected grid station has severe red hot spots on the junction points in the switchyards. As a result, most of the times pitting happens and sometimes it leads to a breakdown. A grid station normally consists of two or more than two yards, so there are hundreds of critical node points for the red hot spots. The usual practice is that, in hot summers, maintenance workers note down the temperature of each junction point in the daylight using a noncontact thermal gun. During the night, the temperature of each red hot spot is noted by turning off the security lights of the yard so that the glowing point could be visible. It takes a lot of time as there are so many junctions and nodes in the form of a mesh that exist in the grid yard. An unmanned aerial vehicle (UAV) mounted temperature monitoring system is a possible solution for the thermal profiling of electric grid stations. This will not only avoid manual labor, but it will also provide fast and quick results in the digital form which can be processed by a computer.
In this project, the unmanned aerial vehicle-mounted thermal imagery circuit for the temperature profiling of an electric grid station has been proposed. The project consists of two main parts: hardware and software. The hardware part combines unmanned aerial vehicle and thermal camera circuits to capture and transmit the required data. The unmanned aerial vehicle consists of four motors spinning in the opposite direction (2 clockwise and 2 anticlockwise), controlled remotely. The thermal imagery circuit comprises of a microbolometer sensor, thermopile sensor, and a suitable thermal module using a microcontroller. The software component processes the transmitted data required to calculate the temperature of the desired point from the thermal image. The project provides a safe, and cost-effective solution for remotely collecting the thermal profile of an electric grid switchyard in a flexible manner.
The objectives of this project are:
In this project, the AMG8833 thermal sensor is used to measure the temperature of the heated nodes. It is an 8 by 8 array thermal sensor. The temperature range of this sensor is 0 to 80 degrees Celsius or 32 to 176 degrees Fahrenheit with an accuracy of plus-minus 2.5 degrees Celsius. The AMG8833 sensor is a cheap sensor that offers a 60-degree viewing field, with a 10 Hz frame rate. This thermal sensor converts the IR rays into electrical voltage and passes them to the signal conditioning unit, and shows a thermal image of an object on the display screen. In this work, this sensor is interfaced to the Raspberry Pi board. An array of 64 individual pixels temperature is obtained from the sensor. The array is further processed for the determination of temeprature. Figure 01 shows the flow chart for the thermal imaging module.

Figure 01: Thermal imaging module.
Aerial thermal imaging cameras make it easy to quickly survey a large target area and detect problems with power grids. This simplifies the implementation of qualitative analysis by allowing the operator to quickly recognize heat differences in the grid equipment and identify potential deficiencies. Figure 02 shows the drone control flow chart. Figure 03 shows the working flow of the quadcopter.
Figure 02: Drone control and formation planning.

Figure 03: The working flow of the quadcopter.
We have provided schematic drawings of all the hardware. However, a brief description of the connections of the quadcopter is given below.

Figure 04: Quadcopter connections
Figure 05: Quadcopter top view

Figure 06: Quadcopter mounted with thermal setup
Figure 07, Figure 08, and Figure 09 show the wiring schemes of the thermal imaging module.

Figure 07: Schematic connection 01

Figure 08: Schematic connection 02

Figure 09: Schematic connection 03
The electric grid is an important connecting link between the distribution system and the transmission lines. In an electric grid, the switchgear directs the flow of energy and ensures the safety of the system by directly controlling the input and output power flow. Transformers are used to change the supply voltage from one level to another according to the situation. A grid station consists of multiple incoming and outgoing circuits connected to a common bus bar system, auto-transformer, current transformer (CT), and potential transformer for protection and measurement purposes.
The power transmission line is a conductor which is used to carry electricity from generating stations to the distribution substation to deliver electric energy to consumers. To transfer the electrical energy from generating stations, the generated voltages are stepped up through a transformer and carried out through the transmission line. When the electrical energy reached the substation, it steps down to a lower voltage level, which is then delivered to the distribution lines. The distribution lines, distribute the electrical energy to consumers (industries, houses, farms, etc). The structure type of the transmission system is determined by the route, existing infrastructure, and the voltage level of the electrical power.
Substations and transmission line localities remain on maximum loading condition in hot summers. Overloading in harsh conditions results in the red-hot spots of the critical nodes in the substations and transmission lines which then results in the pitting of conductors and most of the times breakdowns so timely monitoring or inspection of these nodes or critical points is required. There are hundreds of nodes present even in a substation so it takes too much time. Natural conditions and patrolling in this condition need manpower in harsh conditions, which is difficult. Thus, temperature profiling based on quadcopters is a possible option to automate the process. This will reduce manual labour and the time required for the thermal profiling of the grid. In addition, the temperature nodes are collected in digital form. The data can be processed for further analysis.
Videos links of the project:
Flying drone thermo profiling: https://drive.google.com/file/d/1WdAbUIWNY8GvsmIcrEHxmQBX6kBY8-ch/view?usp=sharing
Electric grid transformer ground thermo profiling 02: https://drive.google.com/file/d/1qYknCEZIcMtrUxAcIz05EUzrEJ43Yh0c/view?usp=sharing
Virtual network computing is exploited in this project for communication between UAV-mounted thermal modules and ground control. The server is installed on the UAV-mounted computer, the client installed it on the ground control computer. The connection of the two devices using the VNC is shown in Figure 10.

Figure 10: Ground control of the UAV using VNC
Results and Findings
Emissivity is a measure of the efficiency at which a surface emits thermal energy. Emissivity is essential for both calculations of heat transfer and accurate measurement of non-contact temperature. An object having low emissivity appears dull to a thermal camera.
In the ideal case, the emissivity range is from 0 to 1, whereas in reality, the range of emissivity is from 0.01 to 0.99. It depends on the material, temperature, wavelength as well as nature of the surfaces. For example, polished metal surfaces have lower emissions but coarse metal surfaces have higher emissions. Table 01 shows the range of emissivity of different electrical materials.
Table 01: Emissivity of Electrical Equipment
| Equipment | Emissivity (30 to 200oC) |
| PG clamp two-bolt connector | 0.70 to 0.80 |
| PG clamp three-bolt connector | 0.61 to 0.75 |
| New parts of the fuse cut-out | 0.43 to 0.64 |
| Old parts of the fuse cut-out | 0.51 to 0.85 |
| New insulators connector | 0.48 to 0.58 |
| Old insulators connector | 0.43 to 0.69 |
| Disconnecting switch | 0.66 to 0.85 |
| Aluminum conductor | 0.71 to 0.79 |
Experimental Results
After getting the knowledge of the emissivity. The thermal setup is tested on many objects like the human body, running stove, plastic chair, and floor of the house. Some results are attached to this proposal.
Figure 11, shows the thermal image of a human body. The image is captured at a distance of less than 1 foot from the human body. The output temperature is 27 degrees Celsius.

Figure 11: Human Body Thermal Image 01
Figure 12, shows the thermal image of a human body. The image is captured at a distance of up to 4 feet from the human body. The output temperature is 26 degrees Celsius.

Figure 12: Human Body Thermal Image 02
Figure13 shows the thermal image of a human body. The image is captured at a distance of up to 7 feet from the human body. The output temperature is 25 degrees Celsius.

Figure 13: Human Body Thermal Image 03
From Figures 11, 12, and 13 it is clear that as the distance from the human body increases the ability to measure the correct temperature of the human body by AMG 8833 is reduced. For precise and accurate results, the distance of the object from AMG 8833 must be within 4 feet.

Figure 14: Running Stove Thermal Image 01 from 4 feet

Figure 15: Transformer Thermal Image 01 from 5 feet

Figure 16: Transformer Thermal Image 02 from 8 feet





Table 02 shows the output temperatures in celsius from the thermal setup.
&
| Hottest point temperature | Mean temperature | Room temperature | Standard deviation | Variance |
| 26.25 | 24.26 | 23.1 | 1.2 |
Equipment
PG clamp two-bolt connector
PG clamp three-bolt connector
New parts of the fuse cut-out
Old parts of the fuse cut-out
New insulators connector
Old insulators connector
Disconnecting switch
Aluminum conductor
| Hottest point temperature | Mean temperature | Room temperature | Standard deviation | Variance |
| 26.25 | 24.26 | 23.1 | 1.2 |
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