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The Resource Planning Model (RPM)

An image of a overlapping circles labelled Resource, Technical, Economic, and Market Potential that include the key assumptions for each segment on a bullet list inside it.

Figure 1. Combined nodal and zonal structure of the Colorado-centric RPM

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The Resource Planning Model (RPM) is a capacity expansion model designed for a regional power system, such as a utility service territory, state, or balancing authority. RPM applies National Renewable Energy Laboratory's (NREL's) extensive experience with national-level capacity expansion modeling, particularly the NREL Regional Energy Deployment System (ReEDS) model and production cost simulations to regional electric system planning—to capture how increased renewable deployment might impact regional planning decisions for clean energy or carbon mitigation analysis. Model versions for regions within the Western Interconnection are currently available for research applications and an Eastern Interconnection version is under development.

RPM includes an optimization model that finds the least-cost investment and dispatch solution over a 20-year planning horizon. The model investment decisions are made for multiple conventional and renewable generation technologies, storage technologies, and transmission. The model has high spatial resolution to represent the grid network (down to the individual unit and line for a "focus region" of interest) and multiple solar and wind spatial resource regions. Dispatch modeling within RPM is conducted using hourly time-steps sampled throughout a year, and the model considers energy balance, reserves, and many generator constraints (Figure 2). Transmission constraints are represented with a transport (pipe-flow) model or a linearized DC power flow algorithm. The model accounts for boundary interactions (e.g., changing power and energy transfers between balancing areas) using a zonal representation of the entire interconnection while retaining the nodal resolution for the focus region (Figure 1). RPM, which is developed at the National Renewable Energy Laboratory, was designed specifically to consider the characteristics of wind and solar technology resources—that is, location-dependence, variability, and uncertainty—in its investment decisions; it accounts for distance-based interconnections, endogenous capacity credits, increased operating reserve requirements, curtailment, transmission congestion, and cycling costs to better assess the economic costs and value of competing electricity technologies.


An image of a overlapping circles labelled Resource, Technical, Economic, and Market Potential that include the key assumptions for each segment on a bullet list inside it.

Figure 2. RPM hourly dispatch for the Western Interconnection

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Hurlbut, David, Scott Haase, Clayton Barrows, Lori Bird, Greg Brinkman, Jeff Cook, Megan Day, Victor Diakov, Elaine Hale, David Keyser, Anthony Lopez, Trieu Mai, Joyce McLaren, Emerson Reiter, Brady Stoll, Tian Tian, Harvey Cutler, Dominique Bain, and Tom Acker. 2016. Navajo Generating Station & Federal Resource Planning. Volume 1: Sectoral, Technical, and Economic Trends. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-66506.

Barrows, Clayton, Jennifer Melius, and Trieu Mai. 2016. Renewable Energy Deployment in Colorado and the West: A Modeling Sensitivity and GIS Analysis. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-65350

Hale, Elaine, Brady Stoll, and Trieu Mai. 2016. Capturing the Impact of Storage and Other Flexible Technologies on Electric System Planning. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-65726.

Barrows, Clayton, Trieu Mai, Elaine Hale, Anthony Lopez, and Kelly Eurek. "Considering Renewables in Capacity Expansion Models: Capturing Flexibility with Hourly Dispatch." Paper prepared for IEEE Power and Energy Society General Meeting, Denver, CO, July 2015.

Getman, Dan, Anthony Lopez, Trieu Mai, and Mark Dyson. 2015. Methodology for Clustering High-Resolution Spatiotemporal Solar Resource Data. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-63148.

Mai, Trieu, Clayton Barrows, Anthony Lopez, Elaine Hale, Mark Dyson, and Kelly Eurek. 2015. Implications of Model Structure and Detail for Utility Planning: Scenario Case Studies Using the Resource Planning Model. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-63972.

Mai, Trieu, Easan Drury, Kelly Eurek, Natalie Bodington, Anthony Lopez, and Andrew Perry. 2013. Resource Planning Model: An Integrated Resource Planning and Dispatch Tool for Regional Electric Systems. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-56723.