How AI will be the energy industry’s unexpected repairman
What is Beyond Limits’ strategy and vision?
Our mission is to create automated solutions with human-like powers of reasoning that amplify the talents and capabilities of people. We specialize in complex challenges in extreme environments. Human beings haven’t done many things more difficult than landing spacecraft on a planet 150 million miles away. It takes extreme trust in the AI to drive autonomous decision-making beyond the reach of human experts. We recognize that many companies on earth have similar needs for mission-critical systems with acute situational awareness in real-time, predictive analytics, domain expertise at the edge, and instantaneous human-like reasoning to make informed decisions and take meaningful action. This is why Beyond Limits was created.
What are some real-life examples where AI made a difference in the US or elsewhere?
AI is ubiquitous, spanning everything from customer-centric applications and devices to industrial settings. Using the Transmission and Distribution industry as an example, AI is currently being used to examine and classify drone aerial photos of equipment, such as transmission towers and lines to find anomalies and to detect impending failures. In this case, AI can scale to support large numbers of photos in an automated fashion and reliably detect signs of impending failures so that additional steps can be taken to verify and mitigate issues.
What specifically can energy companies and grid operators do to prepare for future climate change outages?
First, the energy industry must consider some of the root causes of climate change-related power outages. Some examples include high voltage power lines touching surrounding trees, unusually strong and unpredictable storms, excessively high temperatures, and extended heat waves. AI can be applied to improve weather forecasting capabilities with increased accuracy and speed, which allows energy companies to better predict when and where disruptions may occur and consequently prepare for it. Similarly, improved forecasts using AI for power consumption can greatly improve the ability of grid operators and generation companies to plan ahead and attempt to mitigate issues.
When demand exceeds grid capacity, it can cause uncontrolled shutdown of power generation equipment, which can trigger a domino effect and cause grid disruption. The ability for power generators and grid operators to accurately predict and manage power flow over the physical grid infrastructure to match available generation with demand are the key steps to mitigate future climate change outages.
Are you optimistic that AI and other new technologies can enable the industry to reach net zero targets?
AI can significantly contribute to efforts to reach net zero targets. For the power industry, the goal is always to accurately match demand with generation. As such, we need AI in place to predict and forecast demand accurately and in a timely manner so that we can match generation with its inherent latency when changing set points and variability due to cloud and wind influence on renewables. The biggest benefit AI can bring to net-zero goals is allowing facility managers to use as much renewable energy as possible while taking all these parameters and variabilities into account.
What should be the priorities for governments and private companies to fast-track AI investment/system roll outs
There are several areas that should be high priority, including:
- Start small to solve specific problems, scale up with experience
- Take advantage of and mine the large data sets from increased number of installed sensors and measurement
- Identify specific use cases with defined returns on investment
- Digitize domain expertise and enrich it with AI/ML
- Align stakeholders and their priorities with AI investments
- Fund promising companies and technologies
Do AI costs need to come down to ensure mass market penetration, or are there products and services for all budgets?
From a business perspective, it’s all about return on investment. The focus should not be the cost of the AI/ML tech, but rather the end result. Businesses must remember that cost will continue to decrease due to technology evolution, both in hardware and software, but it is important to continue investing in promising technologies. As a result, there will always be products and services for all levels and budgets. The question is whether you want to be a leader or a laggard.