Power's Future: Streamlining Transmission Planning

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Guidehouse

Fortnightly Magazine - June 2 2025

Given the all-of-the-above generation buildout strategy that many utilities are embracing, how should they streamline their transmission planning and interconnection approaches?

Santos Garza Romero: Before FERC Order 2023, utilities and balancing authorities reviewed interconnection applications in series, looking at generation and load projects individually in their respective interconnection queues.

As the number, size, and type of projects began growing and changing, this approach became unsustainable. According to the Lawerence Berkeley National Laboratory, new generating capacity entering the queues grew from one hundred twenty-seven gigawatts in 2010 to nine hundred eight gigawatts in 2023.

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Looking for a new approach, utilities must first limit the size of each queue. At the same time, they must train and develop a workforce and implement software tools to analyze and manage the queue process, and capable hardware to handle the increased computational demands – as MISO has done by adopting Pearl Street’s SUGAR tool.

At least in the early phases of a study, utilities must develop automated tools for qualifying and quantifying the upgrade requirements for interconnecting the cluster, though generation projects increasingly require specialized studies, such as electromagnetic transients. All of these tests should occur before they are mandated by requirements such as the high penetration of inverters.

Depending on the number of clusters analyzed each year, a utility could transfer the results into its annual transmission planning process, combining to capture benefits from new load, generation, and transmission all in one model. The transmission plan will capture necessary grid upgrades along with the CAPEX needed to implement them.

Producing a transmission plan is an arduous process that can vary annually because of changes in regulatory frameworks, load growth, or power consumption profiles, so utilities must design and implement tools and processes that constantly revise key assumptions and automate their modeling.