Why AI Is Our Best Bet To Save Green Energy In The US

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KEY POINTS

  • Global energy investment topped $2 trillion last year and the International Energy Agency estimates that China needs to add the equivalent of today’s U.S. power system to its electricity infrastructure by 2040, while India needs the equivalent of the European Union’s.
  • Average American household power interruptions totaled six hours in 2018, according to the latest U.S. Energy Information Administration statistics, up threefold from 2013 when reliability data was first collected.
  • Policymakers and business leaders will need to ensure their responses to the dawning AI revolution are smart, practical and, most importantly, ethical. 

The devastation wrought by wildfires along the U.S. west coast in recent days has exposed a fundamental flaw in the adoption of green energy: without digital innovation to create smart grids, clean energy is a green illusion.

Across the globe, hundreds of billions of dollars are being spent each year on wind and solar power projects to reduce carbon emissions and combat global warming, widely blamed for the increasing intensity and frequency of the heatwaves and wildfires seen so far this year, not only in the U.S., but also in Argentina, Australia, parts of the Arctic, the Amazon and central Asia.

The unprecedented carnage is heartbreaking. It serves as yet another warning of the need to address global warming, an existential threat that will be with us long after the current pandemic. Sadly, however, few living outside of California will have noticed the rolling electricity blackouts of recent weeks that have left millions of residents sweltering in the dark for hours at a time, compounding the misery of the wildfires.

In its haste to lead the global fight against climate change, the Golden State sprinted to replace dependable natural gas power generation plants with large-scale wind and solar farms, without the digital innovation necessary to ensure the aging grid could handle new two-way flows of energy. The results have been disastrous.

In fact, the rapid rise of alternative energy worldwide is placing enormous pressure on existing electric grids, which in most countries like the U.S. still rely heavily on human decision-making to run smoothly.

Global energy investment topped $2 trillion last year and the International Energy Agency estimates that China needs to add the equivalent of today’s U.S. power system to its electricity infrastructure by 2040, while India needs the equivalent of the European Union’s.

So, the stakes are high, and yet utilities across the world are already struggling with reliability issues as operators simultaneously integrate renewables and unplug coal- and gas-fired generation, which, unlike renewables, are capable of producing steady streams of power or firing up quickly when needed at peak times of demand.

The U.S. is a cautionary tale. Sudden power fluctuations on the grid today are undermining economic growth with blackouts alone costing upwards of $150 billion annually in lost productivity and damage to infrastructure and equipment.

Average American household power interruptions totaled six hours in 2018, according to the latest U.S. Energy Information Administration statistics, up threefold from 2013 when reliability data was first collected.

U.S. data centers, manufacturers and retailers report experiencing power outages at least once a month, making the issue the latest boardroom headache.

It does not have to be like this. Better weather forecasting and energy grid management is possible, thanks to advances in digital technology, particularly artificial intelligence (AI).

Combined with new capabilities that capture more data from the grid, AI, predictive analytics, machine learning and autonomous control — when paired with renewable infrastructure — allows for better decision making in real-time on the grid.

The result is a smart grid that can create adaptive emergency control AI algorithms to support grid operators when power suddenly surges or falls, generating countermeasures to prevent blackouts in milliseconds, not precious minutes or hours.

If, as some industry analysts say, data is the new oil, then AI is the new refinery, transforming crude data from the grid into highly efficient and effective fuel that keeps everyone’s lights on with less effort and lower utility bills.

AI is also a critical component to protecting the grid against future cyberattacks. By turning the grid into a routable energy network, AI can steer electric power around compromised parts of the grid, avoiding events like the unprecedented and debilitating “Crash Override” cyberattack that brought darkness to large parts of Ukraine in 2016.

AI is a relatively new and much-misunderstood technology. Many fear threats to future jobs and individual liberty. To be clear, these are legitimate concerns.

Policymakers and business leaders will need to ensure their responses to the dawning AI revolution are smart, practical and, most importantly, ethical. And to build trust, technology companies will need to share much-needed clarity on the performance, accuracy and potential hidden bias of AI models.

But the myriad challenges confronting our grid underscore the need for continuous innovation that accelerates the pace of change.

For utilities, the time to join the AI revolution is now.

Chad Steelberg is Chairman and CEO of Veritone (NASDAQ: VERI), a California-based AI technology company.

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