PowerSimm RATM

Resource Adequacy Analysis

PowerSimm RATM provides system operators and resource planners with the information they need to determine whether resource portfolios will reliably serve peak load under the full range of possible weather conditions.  Using stochastically simulated weather, PowerSimm RATM captures the nuanced relationship between weather, renewables, generation outages, and load to quickly calculate resource adequacy metrics, including loss of load probability, MW short, expected unserved energy, and renewable capacity credit.

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Get the insight you need to make the right decisions.

PowerSimm RA™ enables planners and grid operators to make the best-informed resource adequacy decisions by accounting for the uncertainty in weather and generation outages.

 

Features of PowerSimm RATM

Determines impact of extreme weather on resource adequacy and renewable capacity credit

Account for joint relationship of weather on load and renewable generation

 

 

Calculates resource adequacy:  loss of load probability (LOLP), MW short, unserved energy, and required reserve margin

 

Detailed simulation of thermal generation outages

 

PowerSimm RATM Modeling Features

As renewables become increasingly integrated into power systems, planners need to understand how weather drives both load and generation and what that mean for resource adequacy.  PowerSimm RA™ realistically simulates weather, renewable generation, load, and the unpredictable nature of generation outages to characterize resource adequacy under real-life conditions.

PowerSimm RA™ is a stand-alone software application that focuses specifically on calculating resource adequacy metrics such as loss-of-load probability (LOLP) and loss-of-load expectation (LOLE) to guide decisions on resource capacity needs. For example, the table on the left is a PowerSimm RA™ output that tells planners how much additional firm capacity is needed to achieve an acceptable LOLH or reserve margin.

 

PowerSimm RA™ can also calculate how much renewables can be relied on to meet peak demand under realistic simulated weather conditions (such as long stretches of low wind or cloudy days) versus simply average weather conditions and output. The graphic below shows an example PowerSimm RA™ chart demonstrating renewable contribution to resource adequacy requirements.

Better models. Better decisions.

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