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SAS UK & Ireland

Get used to AI supporting our daily lives

In an increasingly digital world, it is inevitable that artificial intelligence (AI) will support the energy transition. Companies and end-users need to become comfortable with it as soon as possible, says Dave Ferguson from SAS UK & Ireland



The views expressed are those of the author and do not necessarily reflect the position of FORESIGHT Climate & Energy


Digital tools can facilitate better and faster decision making
With Antonio Guterres, secretary-general of the United Nations, describing a major new report on climate change as a "survival guide for humanity", the need for action has never been greater. The report, which focuses on the key role of clean energy and technology, outlines several mitigation options from increased use of solar and wind farms, to the electrification of urban transport systems. In many developed countries, we are already seeing the adoption of low-emission technologies, with Iceland and Norway leading the way. Renewable energy has provided almost 100% of electricity production in Iceland since 2015, with approximately 73% coming from hydropower and 27% from geothermal power. In Norway, 98% of the electricity production comes from renewable energy—with hydropower being the primary source. As these levels of renewable energy shares are seen in more and more markets, so too there needs to be a growing level of artificial intelligence (AI) to help integrate this clean power.

BEHAVIOUR CHANGE
Last year, it was reported that smart metres had been installed in over half of UK homes and small businesses, enabling individuals to view their actual energy consumption in kWh, as well as showing the cost of this energy. With the price of energy continuing to rise, many households now rely on this insight to ensure that their usage remains affordable. However, the rollout has not been without controversy. Plans to use these devices as a way of charging households more to use power at peak times, with cheaper rates available when demand is lower, attracted criticism. The next step in this process is the roll-out of consumer access devices. These devices enable the transfer of energy data from the metre into the cloud. Their ability to link with smartphones, tablets and other devices, will enable intelligent choices to be made with limited human intervention. Should usage exceed a certain level, the network will automatically take action to bring this down, turning off non-essential devices operating within the home.

MONITORING AND ANALYSIS
It is not just in the home that we are seeing innovative uses of AI-powered technology to help better manage the network. Recently, we have seen drone piloting software used to maintain high-voltage pylons, enabling quicker and more efficient maintenance to be carried out. Designed to inspect each pylon from a few metres away, the drones are controlled by a computer in a control station. Should a drone find an issue, it automatically takes photos to document the condition of the pylon’s steel arms, fittings and conductors. Within minutes, the drones will capture the images and send them to an AI-powered solution that analyses corrosion levels. Previously, information about the condition of electricity pylons was captured manually, with people having to physically visit and assess each pylon. This process would take hours, with pylons potentially out of action for days. With this sort of technology at their disposal, energy providers can more effectively manage the network, ensuring it is operating as efficiently as possible.

UNDERSTANDING THE DATA
While these are two very different examples of how AI is being used to provide more insight into consumption and prompt action to be taken quicker, they both highlight how access to real-time data can enable smarter decision-making. By applying AI and machine learning algorithms to existing data sets, more accurate forecasting can be undertaken, giving energy providers a clear understanding of exactly what is going on across the network. The fact that renewable energy cannot be produced on demand, adds to the complexity of this challenge. By linking existing datasets with weather apps and other data sources, providers can develop a rich and more granular picture of the situation. Should the AI detect a surge in solar energy on a certain day, energy providers can take the necessary steps to avoid problems. Similarly, they might want to consider buying and storing the energy generated from the solar panels fitted on homes, an option that is far cheaper than buying from a wholesaler. As we have seen over the past 12 months, there have been calls for greater regulation around the open market and overall price of energy—this is a global issue and something that will no doubt continue throughout 2023. With energy transition a key focus for humanity, nations across the world need to start using the tools at their disposal to improve understanding around usage and to enable smarter and more sustainable decision-making. •


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