There are few industries more critical to global prosperity than the energy sector. Though companies like BP and Shell often catch flack — at times, deservedly so — there's no denying that they play a critical role in bringing humans' light, heat, and fuel to power their vehicles. So how is AI (and other technologies) helping these companies? Is it improving accountability, or leading to lower costs for consumers?
These industry insiders shared their insights on the state of AI in the energy sector. Here's what they said:
1. Greg Slater, General Manager at Flutura Decision Sciences and Analytics
“I believe there are two primary considerations when evaluating the state of AI for applications in the energy industry. The first is that companies are becoming more AI savvy and realize that a one-size-fits-all approach does not produce the best outcomes. Companies are now looking at multiple AI vendors or platforms, based on the use cases they identify, or that need improvement in their organizations, in order to enhance their operations. Companies are moving away from the concept of using one AI platform that encompasses everything because that AI platform is doing something well and likely doing something less than optimally. In these instances, enterprises are now using multiple vendors that are pioneers and extremely good in specific areas. For instance, Flutura’s customers engage with us to address and tackle specific use cases.
In addition, the second consideration is a compelling one – companies are looking for tangible results. The energy sector is looking for AI companies that deliver good ROI, have a track record of delivering on specific use cases and can support tangible results, ultimately showing customers (and potential customers) where they can make valuable changes that increase revenue and reduce costs.”
2. Muffi Ghadiali, founder and CEO of Electriphi
“We're on the cusp of the biggest energy transition in history – from oil to electrons. The entire value chain is being re-imagined from production, delivery, infrastructure to the consumption of energy. This shift means a new set of challenges: people now need to consider energy and infrastructure based on time of use, demand capacity, environmental impact. The common thread that ties everything together is data, analytics, and insights.”
3. Larsh Johnson, CTO of Stem
“The energy industry does not use AI in the conventional sense of recreating human decisions. Rather it uses algorithms to make super-intelligent decisions that are just too complex for humans to make. For example,
batteries can be used to dispatch energy with dispatch timing and magnitude depending on a variety of value streams. Such decisions have to be made by AI every few minutes adjusting each time to a wide variety inputs like customer load, solar generation, weather, and prices, etc. The number of incentives and constraints make it too complex for a human to take an optimal decision. AI is being used to address such problems.”
4. Edwin Chen, AI Solution Consultant at Dynam
“The global energy industry is undergoing a tremendous shift with the emergence and renewable energy deployment, decentralization by independent power producers and adoption of new technologies. Energy suppliers are exploring creative ways to employ and deploy AI technologies to improve the accessibility and efficiency use of renewable energy technologies. AI possesses the potential to transform the energy sector.”
5. Shuli Goodman, Executive Director of LF Energy
“AI is early in power systems – particularly when you look where we will be 10-15-20 years out and to the role of automation in orchestrating variable energy and 100% decarbonization.”
6. Jeff McGehee, Director of Engineering at Very
“AI is largely in the same place across almost every industry – it’s struggling to make the leap from academia to real-world implementation. The largest and most advanced software companies have gotten a grasp of what it takes to bring AI systems into the world, but everyone else is lagging. There are not enough AI practitioners who possess knowledge of both the deep complexity of the academic theory at the core of AI, and the necessary software engineering fundamentals required to build large scale software projects. This is because AI is a new field, and the most knowledgeable individuals are coming straight out of technical MS/Ph.D. programs. While their knowledge regarding AI fundamentals is valuable, they still have a lot to learn regarding building real software systems that leverage AI.”
7. Mark Chung, co-founder and CEO of Verdigris
“AI in energy is still in its infancy. It's a powerful new technology but it requires big data and big data sets. The challenge within energy industry today is that almost all of it is built with antiquated systems. So the infrastructure for AI is still immature. AI is probably strongest today in utilities where there's some interesting legacy data already ported to cloud.
In energy management within buildings, it's still virtually nonexistent. That's where a large opportunity exists especially around IoT.”
8. Jason Kram, Executive Vice President at Adapt2 Solutions
“AI is quickly growing momentum in the energy industry, particularly for forecasting activities which is at the core for trading strategies and operations. Today, nearly all forecasting has some element of AI (whether predictive analytics or paired with machine learning technology) that provides access to more data to better predict extreme events or weather patterns. Although AI is in its early stages of implementation, its effect is already modernizing the energy grid, creating stronger trading strategies and risk management policies – ultimately revolutionizing the way we produce, transmit and consume energy.”
9. Morgen Henderson, Journalist at Solar Power Authority
“AI is becoming an integral part of the energy industry and will continue to do so in the future. Because artificial intelligence can analyze large sets of data, it has found ways to more efficiently store energy, simplify energy grid operations, and monitor energy consumption.”
10. Binu Parthan, Principal Consultant at Sustainable Energy Associates
“I believe the current state mainly involves predictive analysis using AI. Utilities are using predictive analysis to forecast demand, dispatch energy resources and predict faults and schedule maintenance. At the energy user-level, predictive analysis using AI is being used to optimize energy usage, improve energy efficiency resulting in energy savings and reduce energy expenditure.”
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