The adoption of artificial intelligence in the energy industry has been somewhat slow and it is currently being used mainly in limited roles. However, there is an increasing understanding of the advantages that AI, robotics, machine learning, and related technologies can contribute to this sector.
The Internet of Things (IoT)
The Internet of Things (IoT) has enabled the collection and transmission of complex data in huge amounts. This data, gathered via connected devices, such as sensors, can be analyzed and interpreted to gain useful insights.
AI-enabled robots are mostly in the stage of research and testing. The Offshore Robotics for Certification of Assets (Orca) program is developing robots that can inspect, repair, maintain and certify offshore energy installations.
They have sensors to allow them to understand the environment and algorithms for planning, acting, and interacting with humans and the environment. These sophisticated robots are currently being tested by Total in the North Sea.
Application of AI, Smart Software and Cloud Computing
Cloud computing, AI, and smart software offer the ability to process, stream, analyze, and interpret data at unprecedented speed.
Oil companies need cheap and fast ways to find out if there is any oil in a well. Some data, such as rock density, can be analyzed by AI far faster than by humans.
ARC Systems Inc, an electric motor manufacturer, uses state-of-the-art computer-aided design systems and proprietary magnetic design programs to produce products such as AC induction motors and AC/DC motors with gearheads and brakes.
Some of its brushless DC motors and alternators are used by fuel companies for oil drilling. Its technological capability has made it a market leader in electromechanical motion control evolution.
Power grid operators are finding new ways to constantly monitor, analyze, and interpret data to make sure that the supply of electricity meets the demand. They also need the ability to ensure smooth management of the combination of fossil fuels, nuclear power, and renewable sources.
Wind farm operators are now collecting wind speed data and can determine real-time weather conditions. They can identify the output of the turbines and the power exported to the grid.
More Widespread Adoption Is Coming
Declines in costs of data processing and processing power are having an impact on adoption. Some companies have been reluctant to become early adopters because of the risks. Time is necessary to develop the algorithms needed to construct and program robots to do special tasks.
The size of the power and renewable energy sector and the oil and gas industry is a huge market for software creators, engineers, and AI developers. Technological advancements are likely to snowball in the coming decade.
Wide adoption of machine learning and AI-enabled robots are likely to completely change the cost structures and operations of energy companies. Risks will be reduced, health and safety improved, and the skill sets required will change.
Redesigning the World of Work
The adoption of AI and automation will lead to the reduction of on-site staff as operations are supervised from remote centers.
On the plus side, it will free employees to focus on the more human aspects of tasks, requiring more emotional intelligence, leadership skills, and verification of the solutions and insights generated by the sensors and automated equipment. New tech jobs will be created and roles will require a more modern skillset.
The energy industry may have been slow adopters of AI but the realization of its benefits is creating acceleration in implementation and the next decade could see significant changes taking place.