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What’s The Future Of AI In Energy? 11 Experts Share Their Insights

  • 30 September 2019
  • Sam Mire

Let's hope that with AI's help, the future of energy isn't as bleak as many project it to be.  Let's believe that the indomitable human spirit, alongside the latest in technology and innovation, will create a sustainable means of powering humanity well into the future. Will this be the case, or are we being overly optimistic?

These energy industry professionals shared their visions of energy's future with us for comparison. Here's what they said:

1. Larsh Johnson, CTO of Stem 

“Today, AI is primarily being used to drive operations. Going forward, AI will become a key driver behind all facets of energy businesses like system sizing, predictive maintenance, supply chain optimization, automated contracting etc. And most importantly, customers will be offered AI-enabled choices that they can direct as AI has simplified the process of setting their energy strategy.”

2. Edwin Chen, AI Solution Consultant at Dynam

“There is an immensely bright future for AI in the energy sector.  Increasing demand for energy necessitates and accelerates the adoption of AI decision-making capabilities with scale and complexity that exceeds human capabilities.  The ubiquity of adopting AI solutions will help and encourage us to efficiently manage and optimize energy supply and demand as we transition away from fossil and oil-based energy generation.”

3. Greg Slater, General Manager at Flutura Decision Sciences and Analytics

“The industry is moving fast and what once was thought of as impossible, is now possible. AI is providing stability and enabling a new constant way of performing operations that eventually become invisible to daily operations and workloads.  Companies will soon take AI for granted as in becomes fully integrated into energy company operations.”

4. Mark Chung, co-founder and CEO of Verdigris

Mark Chung“The future of AI in energy is tough to translate to words. It will be an integral part of the rapidly decentralizing model for electricity in the next decade. It will be an integral part of how we manage the energy supply chain and utilities. It will be an integral part of how we consume it in our transportation, in our cities, ports, buildings, factories, homes and individual appliances. It's basically all of the things that power civilization interconnected through a handful of really powerful AIs… that will either greatly benefit or ultimately destroy humanity.”

5. Binu Parthan, Principal Consultant at Sustainable Energy Associates

“I believe there are significant opportunities from Artificial Neural Networks (ANNs) which could increase the share of renewable energy in energy systems through optimal sizing, performance forecasting, diagnostics and through the balancing of power systems.”

6. Andrew Tang, Vice President, Energy Storage, Solar and Integration at Wärtsilä

AI will become a greater player in our energy future as utilities focus on decreasing emissions and continue to tap into the potential of renewable energy resources. More than 90 cities and states across the country have made 100% renewable energy commitments to date, and in order to make progress towards these targets, utilities are starting to shift away from manual control systems. A whole new energy management approach is needed because renewable sources are less predictable than traditional thermal assets. Without machine learning capabilities, the amount of renewable energy that can be added into the grid will be capped at very low percentages.”

 7. Shuli Goodman, Executive Director of LF Energy

“The implications are that substations MUST be redesigned as edge gateway routers that can facilitate “networking” electrons. Not that an edge energy ‘router' will defy physics, but that the data about energy – or the meta data of the electron and the meta data about the supply and demand – will need to be able to flow through pipes that are big enough and into systems that have the capacity to learn from and make sense of the data in terms of patterns and responses to patterns. That's the future of the grid – and that is why the first steps at digitalization are laying down the foundations that will enable AI and ML at scale – but we are probably 5-10 years off for that degree of automation. We have a few problems we have to solve first. But, we can see the beginning…it's on the horizon.”

8. Jason Kram, Executive Vice President at Adapt2 Solutions

“Energy efficiency and demand response are constantly gaining importance from all over the world. AI enables energy businesses to streamline workflows to make more informed decisions about their increasingly smart energy grid. Just recently, the UK shared forecasts for solar power generation which have become far more accurate through the use of artificial intelligence. This has the potential to lower energy bills and carbon emissions – a win all around.”

9. Morgen Henderson, Journalist at Solar Power Authority

“In the future, AI could very well be the number one contributor to energy conservation. Outside of helping control power grids, artificial intelligence can be used in individual homes to conserve energy. Smart homes, which are powered by artificial intelligence, are making it easier for everyday people to use less energy by recognizing patterns in the home.

For example, smart homes can use AI sensors to turn off lights, air conditioners, heaters, devices plugged into the wall, etc., when it senses they aren't being used or someone isn't home. These all seem like small things that don't use much power and wouldn't matter over the long run, but it adds up to a significant amount of energy over time.”

10. Jeff McGehee, Director of Engineering at Very

“Hyper-efficiency is the future of AI in energy. AI will control power generation schedules based on load forecasts, eliminating the need to dump unused energy from the grid*. It will predict failures of all sorts of equipment in every stage of the energy life cycle. It has the capability to help geologists and geotechnical engineers identify and tap into the remaining fossil fuel reserves, help engineers design machines and buildings that will be more energy efficient by helping them sort through the millions of possible design options available, control HVAC systems in a way that minimizes wasted energy, as well as will improve the speed at which chemists derive new types of fuel by running and/or simulating many experiments simultaneously.  These efficiency increases will decrease waste, and increase the speed of innovation in the energy industry, which is the industry’s greatest hope for meeting the energy demands of the future.”

11. Alexandra Zelenko, Technical Writer at DDI Development

Energy companies are turning greater control over the data into actionable insight to drive faster and sharper decision-making. AI-assisted analytics allows energy companies to move from a product-based to a process-based approach. They can quickly see where failures in the process are likely to occur and take corrective actions before problems arise. The more sophisticated analytic engines become, the more user-friendly business intelligence capabilities become. Simple interfaces, visualizations, dashboards simplify the analysis process for users from top to bottom. Moreover, deploying the correct AI-powered solutions will be vital to delivering flexibility and agility to meet business and customer demands in the energy sector.”


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About Sam Mire

Sam is a Market Research Analyst at Disruptor Daily. He's a trained journalist with experience in the field of disruptive technology. He’s versed in the impact that blockchain technology is having on industries of today, from healthcare to cannabis. He’s written extensively on the individuals and companies shaping the future of tech, working directly with many of them to advance their vision. Sam is known for writing work that brings value to industry professionals and the generally curious – as well as an occasional smile to the face.