How Power Companies Benefit from Accurate Weather Forecasts

It’s pretty easy to understand how the weather affects certain forms of power generation and infrastructure. Sunlight is obviously needed to generate solar power, wind is required to produce wind energy, and extreme storms of all kinds can wreak havoc on transmission and distribution lines, and other energy-related assets. Therefore, having accurate and constantly updated weather information is vital to power companies.

“First and foremost, utilities need to understand as best as possible the forecast of the environmental resources that are supplying these generation sources. It’s ultra-critical, because even small, slight changes in wind speed or solar radiation can have pretty substantial impacts as far as the capacity factor that a renewable generator is operating at,” Nic Wilson, director of product management for weather and climate risk with DTN, said as a guest on The POWER Podcast. DTN is a global data, analytics, and technology company with a staff of expert meteorologists, climatologists, and data analysts that leverage information and data from around the globe combined with the most accurate weather information available.

Wilson highlighted some of the weather-related applications that utilities are integrating into their operations. “One of the focal points for DTN is working with utility emergency preparedness teams in order to help them better understand and forecast at-risk weather environmental hazards that are going to impact their overhead distribution operations, and understanding and communicating appropriately the outage impact risks,” he said.

“Another application is asset inspection,” said Wilson. “After a storm goes through, how does the utility prioritize where it’s going to do inspection along its lines for potential damage?” One way could be using DTN’s tools. Wilson suggested, for example, a company responsible for the operations and maintenance of wind farms could use DTN data to identify turbines that may have experienced blade damage during a weather event. With that insight, the company could proactively inspect for compromises to the fiberglass blades before the damage turned catastrophic.

Load forecasting is another important use case for DTN’s data. Many things must be considered to develop load forecasts including historical trends and current events. Wilson suggested temperature, precipitation, cloud cover, time of day, time of year, and more will affect not only the renewable energy production, but also demand for electricity. With accurate forecasts, power companies can plan appropriately to take advantage of any given situation. If they anticipate a surplus, units could be taken offline for scheduled maintenance, but if the supply is expected to be tight, they can issue orders to increase plant readiness.

“Then, there’s some emerging applications, such as capital planning, where utilities are trying to climate-adjust the age, and understand the performance and condition monitoring of their assets in order to prioritize resiliency investments,” Wilson said.

Rain can play a big role in vegetation management and soil conditions. If dealing with drought conditions, vegetation may stagnate and wildfire risk could increase. Alternatively, when rain is abundant, vegetation can grow quickly and interfere with lines, which also increases risks. Soggy or washed out soil can also cause problems such as reducing pole stability and/or weakening root systems, which can result in infrastructure damage. There’s obviously a lot that can go wrong as a result of the weather. “I never get tired of the problems that our utility customers bring forward for DTN to try to solve,” said Wilson.

DTN’s products are constantly being refined too. Wilson said artificial intelligence and machine learning are behind many of the improvements. “We are consistently doing what we call retraining. So, as new data becomes available from the utility, whether that’s outage management system data, or condition monitoring information, or satellite- or LIDAR [light detection and ranging]-derived vegetation datasets, we’re incorporating that into our models and updating them as frequently as possible in order to ensure that our predictions are as representative of the current environment as possible,” he said.

Wilson said DTN is making some forays into climate modeling and trying to understand how different environmental factors of interest to utilities are going to evolve in not only the next three to six months on a seasonal basis, but also out to 30 years in the future. This is important information for power companies because they are often making investments with a 50-year time horizon in mind. “The more intelligence that we can provide as far as how they need to design and build resiliency into their power network for the long run is going to ultimately help drive decisions that are going to get the most return on investments and bring the best outcomes to their customers,” he said.

To hear the full interview with Wilson, which includes additional insight on weather forecasting techniques, dynamic line rating technology, and how DTN’s predictions can help utilities estimate post-storm needs, listen to The POWER Podcast. Click on the SoundCloud player below to listen in your browser now or use the following links to reach the show page on your favorite podcast platform:

For more power podcasts, visit The POWER Podcast archives.

Aaron Larson is POWER’s executive editor (@AaronL_Power, @POWERmagazine).

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