New Resource Adequacy Modeling Tools Needed For The Evolving Grid, NRRI Says
June 14, 2022
by Peter Maloney
June 14, 2022
Traditional resource adequacy tools are not sufficient to ensure reliability in a rapidly changing electric power system, according to a new report from the National Regulatory Research Institute (NRRI), the research arm of the National Association of Regulatory Utility Commissioners (NARUC).
Power grids are evolving rapidly from a system served by dispatchable resources to a system that relies on variable energy resources (VERs) and duration-limited storage, the report noted. Those changes are making many of the tools power system planners relied on “obsolete,” according to the report, Resource Adequacy Modeling for a High Renewable Future.
In the past, electric system planners only needed to worry about unusually high loads or high forced outages, the report said. “Now, they must worry about unusually high loads during periods of unusually low renewable output and limited storage duration” that, coupled with more extreme weather, can compound risks and require “a fundamental rethinking of planning for low probability, high impact events,” the report said.
The NRRI report, like other recent reports, highlighted that weather is emerging as a fundamental driver of power system conditions and will require changes in resource adequacy planning to account for increasing uncertainty on both the supply and demand side of the equation.
The North American Electric Reliability Corp.’s 2022 Summer Reliability Assessment identified an “elevated or high risk” of energy shortfalls this summer because of predicted above-normal temperatures and drought conditions.
And earlier this year a paper by NARUC, the National Association of State Energy Officials and Converge Strategies recommended new approaches to estimating the value of resiliency in the face of changing grid conditions and weather patterns.
Updating reliability planning for a “new energy paradigm” will require taking into account meteorology, variable renewable energy generation, forced outages, and energy limited storage, the report said.
The report’s authors argue in favor of using a Monte Carlo simulation that is capable of factoring in multiple inputs and uncertainties while maintaining historical correlations. For example, “traditional models used average or typical time profiles of load and renewables while focusing on generator outages as the primary source of uncertainty, greatly underestimating the risk of load shedding,” they said.
The report also noted that traditional models for resource planning often fail to include weather data, climate impacts, behind-the-meter resources, transmission, or sophisticated data on energy storage availability.
The authors included another example of the failure of traditional resource adequacy modelling. They ask, “At the high end of renewable penetration, how much storage would be required to cover Dunkelflaute, the ‘dark doldrums,’ that occur in the winter when wind ceases to blow for several days?”
To ensure that resource adequacy models can provide valid risk assessments, the report recommended they should simulate random variables as weather dependent; benchmark simulations against historic data; model generator outages as weather driven; scale simulations to match future expectations, and include climate effects in simulations.