2. Edge Computing Will Help with Consumers and Assets
Energy and utilities firms have been investing in edge computing technology for years to process and act upon data faster by putting computing power and networking closer to where assets are in the field. This trend will grow in several ways in 2023 and beyond, Villali says.
Customer engagement is one. As more utility customers adopt smart energy meters, solar panels, electric vehicles and other distributed energy technologies, he says, edge computing will help companies determine how customers are consuming energy and when they might be able to sell energy back to the utility.
Whigham says that edge computing can help enable a “two-way grid,” which is becoming necessary as new technologies and solutions around distributed generation and storage become more prevalent.
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On the operational side, edge computing will aid firms as they deploy more grid-scale renewable energy resources and assets, including wind farms and arrays of solar panels, many of which are in very remote locations. Edge computing will likely help energy and utilities companies monitor, manage and optimize these assets by collecting and analyzing data from the edge, Villali says.
That could include both making sure those assets are operating as efficiently as possible and getting analytics from the grid and distribution systems, Villali notes. For example, a wind farm needs to be monitored for how it is sending and storing energy, since the wind is not always blowing, but edge computing can also help companies determine the timing on sending energy to the grid.
“We are seeing a lot of use of edge computing around predictive maintenance and remote monitoring, to avoid disruptions in supply and reduce outages and customer cost,” Whigham says. “We see this continuing in the future and expanding into areas that further connect stakeholders in the energy ecosystem, in particular better connecting the customers with the assets that they are served by and the field crews that serve them.”
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3. Energy & Utility Firms Will Continue to Study AI
AI represents a growth area in 2023 for energy and utilities firms, Villali says, but there is still a learning curve around the use cases. In IDC’s recent Future of Operations Worldwide Survey, more than half of utilities surveyed said they are still learning about how to best deploy AI.
There are clear use cases for AI in the E&U market. One is on the operational side, including the deployment of AI-based tools for predictive and preventative maintenance for assets. “Basically, tracking history and work orders to understand the historical issues that assets have had” to get ahead of problems before they occur, Villali says.
Another AI use case is in analyzing market data around energy supply and demand fundamentals. Neural networks have been used for a long time on demand management or demand forecasting, which will continue to improve.
AI can also be used for both short-term operational decision-making, such as responding to real-time supply and demand fundamentals, and long-term forecasting about future energy demand patterns as well as consumers’ interests in green energy programs, helping providers prepare.
“To date, it seems that AI is a great complement to existing, human-initiated ways to perform the analysis, largely leveraging existing data sets with traditional analytical ability,” he says. “Over time, it is very possible that AI becomes the ‘first chair’ in these areas, with human interaction being the review point, analysis and final decision-making in the process. It may take some time for this to occur, but over time, this seems inevitable.”