In October 2019, National Grid Partners invested $102 million of its $250 million venture fund in emerging technology companies in the energy industry. VentureBeat also highlights companies which could be of interest:
According to BIS Research, North America is believed to persist as the leading market for AI in energy up until 2024, nevertheless, Asia-Pacific is anticipated to observe a strong growth over the same period due to the growing need of more decentralised power generation.
Some of the key companies in this sector that are exploring the opportunities presented by AI in the Energy industry, includes:
There are many investment options when it comes to AI in the energy industry, owing to AI having a variety of applications. These can be in:
5 countries that are considering AI includes:
At the forefront of The United States’ broad AI strategy are corporations who are focusing on self-regulation and rapid technological development. In February 2019, the American AI initiative was launched, which has a focus on driving technological breakthroughs.
The U.K. has established an ethical approach. The development of the Centre for Data Ethics and Innovation as well as the Office for AI, were the first in the world of advisory-type organisations in government. Companies such as the National Grid System Operator are also investing in and developing AI and machine learning for applications such as wind power forecasting.
China have been aggressively pushing for national AI development. In 2017, China launched the New Generation AI Development Plan, announcing their aim to be the world’s leading AI innovation centre by 2030.
Singapore proposed an AI governance framework in January 2019, taking a “human-centric” approach. Its plan emphasises transparency and fairness as guiding their principles. Singapore has set up a US$109m programme, AI SG, to promote further research and innovation.
India’s policymakers aim for AI to help in solving the country’s important social challenges. A national strategy for artificial intelligence was outlined in 2018.
Currently, the critical success factors seem to be related to how much investment is being given to these technologies as well as the policies, regulations and incentives of the future which will be different from country to country.
The implications that the use of AI could have on production capabilities are mostly positive, both in terms of the traditional hydrocarbons industry as increased operations efficiency and optimisation would result in more efficient production, as well as the renewables industry where AI used for the forecasting of wind and solar production capabilities would also result in an increase of efficiency.
To generate public awareness about both new/existing products and technologies, as well as to compete with the products offered by other companies, main players within this industry are focusing on product launches and developments to introduce new technologies or developing further on the existing product portfolio. An example from January 2019 can be seen with Kellton Tech Solutions, who launched a cloud-based AI platform with real-time analytics for the oil and gas industry
Many governments around the world are increasingly pushing for decarbonization, however, up until May 2019, when 42 countries came together to support a global governance framework for artificial intelligence (FT), AI was largely unregulated throughout the world, with the Energy and Utilities sector being quite heavily regulated in comparison.
As the rapid development of AI in recent years has outran regulation, there are major challenges that need to be addressed: including biased AI decisions, outright fakery and misinformation, and the dangers of automated military weapons (FT). On the other hand, the lack of a governance and legal framework may be a reason as to why this industry has grown rapidly of these technologies. Either way, the regulations, policies and laws will need to evolve in such a way to keep a reasonable balance of the ethical and practical consequences of applying AI to the Energy industry. According to CMS, the challenge will be to grow AI past its infancy and unlock wide scale consumer engagement.
Because of the rapid growth making the market more competitive, companies are implementing collaborative strategies that include partnerships and joint ventures. An example of this can be taken from August 2019, when AutoGrid Systems entered a collaboration with Amazon Web Services for the digitalisation of power grid using the AutoGrid Flex AI platform.
More prominent examples of how companies are currently investing in AI in energy/utilities can be seen in the oil and gas industry.
In January 2019, BP invested in Belmont Technology to bolster their AI capabilities through the advancement of a cloud-based geoscience platform. This investment will be used to boost their ongoing work in discovering various applications of cognitive computing and machine learning (BIS Research). With these AI tools, the efficiency and optimisation of their upstream processes can be increased through, for example, automating the analysis of the geological data and digitising records.
Smart Energy International also mention other examples, including Belectric, a start-up in grid-scale solar and storage technology, was acquired by Innogy. As well as Enel and its launch of an innovation hub and lab to hosts start-ups researching and developing technologies including the internet of things (IoT), big data, automation, AI and augmented reality.
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