How the machines are taking over the UK energy sector, and why all of us should want them to

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AI is now being adopted across the electricity value chain and this innovation in the sector needs to be seen as a good thing.

For decades, energy consumers in the UK have benefitted from secure, reliable networks, safe in the knowledge that there would always be gas flowing and that electricity power cuts were extremely rare. For the companies that made up the sector, there was little in the way of new competition; customers would stick with their providers almost no matter what and profits kept increasing. Times were good. But times have changed, and will continue, increasingly, to do so.

The number of disruptors, all with the potential to rip up the traditional business model, seems only to ever increase. De-carbonization, storage, electric vehicles, and distributed generation are among the headline-grabbing threats, but there are many others as well.

But companies, both traditional and digital-native new market entrants, are rising to these challenges and increasingly this is through the use of new, innovative technologies.

Artificial intelligence (AI) is a technology that was first discussed in the 1950s, but never really took off until recently with the emergence of big data and advancements in computational power. AI simulates human cognition processes to enhance ability to solve business problems and is now being adopted across the electricity value chain.

 

Value Chain

 

AI use case

 

Generation

One challenge with the increased use of renewable generation methods is their unpredictability and inconsistency. For a number of these techniques, such as wind and solar, weather conditions ( a cloudy afternoon or a still, windless day) severely impact their effectiveness.  But with AI, power generators can predict and manage fluctuations in production by forecasting demand, generation, and weather conditions.  GE Renewable Energy’s Digital Wind Farm uses algorithms to monitor and optimize the turbine as it runs, with the potential to increase energy production by 20%.

 

System Operation

 

Deepmind, Alphabet Inc.’s AI lab, is working with the National Grid to explore how to use their self-developed algorithms to predict surges in demand or instances of oversupply. According to Deepmind’s CEO, this technology could “save 10% of the country’s energy usage without and new infrastructure, just from optimization.”

 

Transmission

 

Advanced machine learning with synchrophasor technology generates swathes of data that can be analyzed in real time to measure the voltage and current on the grid and predict problems about to happen. This ability to process and analyze such volumes of data would simply be beyond human operator capabilities, and therefore helps to build in network resilience.

 

 

Distribution

 

 

The use of drones to help carry out predictive maintenance, replacing time-intensive and risky manual inspections, is a growing trend. The drones are trained using deep-learning algorithms to automatically identify defects and predict failures without interrupting operations.

 

Trading

 

In this era of the prosumer (users generating their own renewable energy and sending the excess back into the grid), blockchain platforms are emerging to allow peer-to-peer trading between producers and consumers. As supply and demand continuously fluctuate, AI can be used to more quickly match producers with consumers. In the UK, start-up Open Utility has spearheaded peer-to-peer activity using its algorithm-based platform, Piclo Flex.

 

Retail

 

Fans of the UK show Dragon’s Den may be aware of a recent pitch by the founders of an energy start up that uses AI to switch consumers to the most cost effective supplier and tariff when their existing deal expires.  The idea was so well received by the Dragons that it received what has been described as the “best deal in the history of the show,” with 3% of equity sold for £120,000.

 

“Just as electricity transformed almost everything 100 years ago, today I actually have a hard time thinking of an industry that I don’t think AI will transform in the next several years.”

Andrew Ng, co-founder of Google Brain and Stanford University Professor.

For all of us as energy consumers, innovation in the sector has to be seen as a good thing. It is helping to drive competition, deliver better customer experiences, and provide increased reliability.  After decades of perceived complacency and low customer satisfaction, the sector is responding. The industry regulator Ofgem has stressed that innovation must become “business as usual,” and the financial incentives to companies set out within the RIIO price control, coupled with the threats outlined in the introduction above, are driving a step change in the use of digital technologies. This is an important point, as incremental change alone, or “continuous improvement,” will not be enough for energy companies to resist these threats, and it’s for this reason that the machines will continue to rise.

 

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