Examples of AI utilization in the energy industry

About the energy industry

Since many things have been connected to the Internet by IoT technology, more and more things are controlled by electricity, and the need for them is increasing. Therefore, the existence of electric power and energy as a social infrastructure is increasing, and a more stable supply is required. In the energy industry, we have prepared various menus such as equipment inspection, repair, replacement, and improvement so that electricity can be supplied stably for a long period of time. In the energy industry, AI-based models are being created based on past accumulated data and incorporated into systems. This makes it possible to analyze the knowledge and experience of veterans using AI, aiming to optimize operations.

Energy industry challenges

One of the challenges facing the energy industry today is that it relies too much on traditional nuclear and thermal power generation. In the future, vehicles such as electric vehicles will become commonplace, and the use of computers and various communication devices will increase in our daily lives, and the servers that support them will also require enormous power. In addition, we must increase the usage rate of renewable energy in order to deal with the environmental problem, which can be said to be the biggest problem. The energy industry, such as electricity and gas, is the infrastructure that supports such a society, so it is necessary to provide more stable and efficient power supply in the future.

Examples of AI utilization in the energy industry

“A fictitious power transmission line diagnostic system that utilizes artificial intelligence (AI) using the cloud as a platform)”

Traditionally, when checking the safety of overhead power lines, maintenance workers usually use scopes to inspect from the ground or actually climb towers and hang them on power lines with special equipment.
In addition, for fictitious power transmission lines that are difficult for maintenance workers to check, such as in mountainous areas, it takes time because the helicopter VTR is inspected by slow motion playback.
For this reason, the “Overhead Transmission Line Diagnostic System” conducts efficient safety confirmation with the aim of improving inspection quality and further reducing costs.
For this energy industry, AI can maintain overhead power lines, reducing manpower and costs.


The solution here is to have AI analyze the VTR shooting data of the fictitious transmission line, aiming to reduce the number of personnel and obtain high-quality information. When processing a huge amount of data, the quality of the results varies from person to person, so we will let AI analyze it to output a certain level quality of information.

・ Let AI learn the VTR shooting data and inspection technology of fictitious power transmission lines that have been accumulated so far, and let them learn deeply.
・Allow automatic determination of abnormalities from VTR data of fictitious power transmission lines taken with a drone.
・ AI will perform inspection work using VTR, which has been confirmed by workers so far, aiming to improve abnormality detection and shorten inspection work time.


The effect here is that by leaving the analysis of overhead transmission lines to AI, we were able to reduce the number of personnel and obtain highly accurate output. As a result, personnel can work on more necessary tasks, leading to cost reductions and system efficiency. In addition, it is possible to reduce personnel fatigue, which leads to increased employee motivation.

・ Costs can be reduced by facilitating maintenance of electric power equipment, leading to a stable supply of electric power.
・Abnormalities can be automatically determined from VTR data  fictitious power transmission lines taken with a drone, eliminating the need for personnel and allowing people to work more efficiently.
・By having AI perform inspection work using VTR, highly accurate output can be obtained, leading to more sophisticated abnormality detection and shorter inspection work time


This time, we focused on the maintenance of transmission lines, but in the power infrastructure, similar AI-based failure monitoring systems have been incorporated into generators and other devices. This makes it possible to reduce the number of personnel and costs compared to the past, leading to a stable supply of electric power.

There are two points that AI is useful for industry, “quantitative perspective” and “qualitative perspective”. From a quantitative perspective, in the past, people checked all the data, and although it was an intellectual work, it was a labor-intensive work, so there was a problem in securing personnel and time. From a qualitative perspective, when a person processes the huge amount of data, there is a problem that the quality of information differs depending on individual experience and knowledge.

However, by doing labor-intensive work with AI, people are now able to work on their original, more creative work. In addition, information can be guaranteed to a certain level of quality.

Through such efforts, more efficient and stable power supply is possible. In addition, by reducing the burden on people, employees’ aspirations and learning aspirations will improve. In this way, the coexistence of AI and people will lead to the development of companies and people, and it is expected that further usage will increase in the future.