Weekly Newsletter

11 September 2023

Weekly Newsletter

11 September 2023

Predictive AI offers energy security amid changing industry

The technology can be used to help protect assets and prevent disruption as renewable sources increasingly take centre stage.

Eve Thomas September 08 2023

Artificial intelligence (AI) will revolutionise the potential of predictive maintenance, improving system efficiency and international energy security by identifying and resolving problems before they create disruption, according to a new report from GlobalData, Energy Monitor's parent company.

The Thematic Intelligence: Artificial Intelligence in Energy report explores the way in which AI is changing the energy sector. It suggests that AI will increasingly be used to analyse real-time data to detect and repair faults, using monitoring, thermographic and analytical technology.

The report explains: “Implementing AI in the energy sector will benefit resource management, failure prevention and predictive analytics for renewables,” adding that predictive AI will offer energy security by allowing a better understanding of the fluctuations within the sector while reducing the risk of unforeseen equipment failures.

Among the use cases provided for predictive technology is the assessment of likely impacts of external factors, such as poor weather in the case of renewable energy sources. This is particularly important as the supply from non-dispatchable resources fluctuates, impacting wholesale price predictions and requiring predictive analytics tools to estimate output. The technology will help to enable secure electricity transmission.

In addition, it is suggested that AI will further enable energy security by reducing the risk of asset failures. Algorithms can identify and flag likely issues with assets, analysing real-time sensor data to detect faults, before repairing them ahead of breakdowns.

The Artificial Intelligence in Energy report also considers the potential for hazard detection, citing the example of E.ON, which used drones to photograph power poles and lines, before using Grid Vision (an AI-supported inspection tool) to evaluate the images for maintenance purposes. In this way, it argues that AI will keep human lives out of the most dangerous situations. 

“AI-powered systems can anticipate potential threats to energy supplies and proactively strategize solutions,” it says. “Moreover, AI-driven energy management platforms can dynamically adjust energy production and distribution, balancing the intermittency of renewables with the availability of traditional energy sources, thus ensuring a reliable and stable energy supply.”

Elsewhere, the report notes some of the challenges faced by the energy industry and the mitigating impact AI might have. These include the issue of an ageing workforce as a retiring population sees experts leave the profession. It posits that AI might bridge the skill gap between retiring experts and new employees, by organising, storing and retrieving insights and experiences. 

Thematic Intelligence: Artificial Intelligence in Energy provides insights into AI and its potential impact on the energy sector.

Quantum computers could transform oil and gas research

Although quantum computing is still in the R&D stage, its potential use cases in the oil and gas industry are numerous and are likely to expand. Oil majors, such as BP and ExxonMobil have joined IBM’s Q Network to develop quantum computers that will increase the understanding of subsurface geology. Companies are also looking at these computers to study molecular modeling and emission mitigation. Besides, the long-standing problems of matching demand with production and optimizing supply chains could be solved using quantum computing.

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