145. 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. 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 histo