Artificial intelligence will substantially contribute to the accelerating energy transition and complete decarbonisation
With concerns around global warming and climate change now gaining considerable traction from governments around the world – especially post estimates from the World Economic Forum (WEF) revealing 18% of global GDP could be affected by the year 2100 due to climate inaction – the global mobilisation towards using technology for direct coordinated and concerted action against climate change is today higher than ever.
There are now incentives too. Allied Market Research opines that the renewable energy market is set to grow from $880 billion to nearly $2 trillion by 2030. Additionally, given burgeoning awareness around the importance of environmental and social governance issues, there are set to be political incentives as well, opines technologist Bernard Marr. He adds:
“2022 is set to be a record year in terms of the scale at which the switchover from fossil fuels to renewable sources will take place. It’s also a year in which we will see new and exotic sources of energy emerge from laboratory and pilot projects and start to become a part of everyday life.”
As with most others, AI is set to have transformative effects across the energy sector as well – in forecasting demand, managing resource distribution, ensuring power availability, and waste minimisation. This becomes particularly relevant for the renewable energy industry where, often, energy cannot be stored for long periods of time and has to be used close to the time and location of energy generation. The WEF writes:
“The economic value of AI for the energy transition is difficult to estimate, given that it has the potential to be widely adopted across the energy value chain to enable entirely new revenue streams through new business models, and given that some of its benefits will come in the form of avoided costs (e.g. lowering equipment replacement costs through the predictive maintenance of existing assets).
Considering the levels of investment required to deliver the energy transition, even if AI were to reduce the required investment or shave peak energy demand by a small percentage, this would drive billions of dollars in savings for the industry and consumers alike.”
AI – a critical tool
AI is also set to be a critical tool in achieving results based on commitments made under the 2015 Paris Agreement – in limiting global temperature rises to well under 2°C. To this end, the WEF reports: “In recent years, the energy sector has become increasingly digital, and it is clear that further digitalisation will be a key feature of the energy transition and an essential driver of the sector’s progress towards ambitious climate goals.”
- Digitalisation needed as an enabler to a swift and controlled energy transition: In order to achieve a deeply decarbonised global energy system, there must be a major increase in the interaction between the power, industry, transport, and building sectors – built on the pillars of independent telecommunication and energy networks. Each aspect of the system needs to be optimised to make it reliable, affordable, and clean – and this is where AI waltzes in.
“Optimising each sector separately would exclude flexibility-generating options and reduce the scope for system-wide transformation processes that would maximise the benefits of digital technology for the full energy system, as well as more broadly for the economy, the environment and society”, writes the WEF.
- Decarbonising the power sector is the first step: The transformation of the global energy system will require not only a rapid expansion of the renewable power supply system but also ‘a vast clean electrification of heat, industry, and transport.’ According to long-term scenario analysis of the global energy system by BloombergNEF, 56% of power generation is set to be provided by solar and wind in 2050, requiring about $15.1 trillion investment in wind, solar, and batteries and $14 trillion in power grid investments by 2050.