NOTICE This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific

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... ommercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or any agency thereof. Abstract Recent and anticipated trends indicate that renewable resources, particularly wind and solar energy, will provide a growing contribution to the U.S. and global power systems in the coming decades. These resources are variable and uncertain by nature, and their impacts on system expansion and operation need to be properly accounted for in electric system models. To this end, we introduce a new capacity expansion model, the Resource Planning Model (RPM), with high spatial and temporal resolution that can be used for mid-and long-term scenario planning of regional power systems. RPM endogenously and dynamically considers grid integration of renewable resources, including transmission and interconnection availability and costs, renewable resource limits and output characteristics, and dispatch options for conventional generators, in its optimal generator and transmission decision-making. As an hourly chronological model with a highly discretized regional structure, RPM provides a framework where various future scenarios can be explored while ensuring that the scenarios include many aspects of grid reliability. Although the structure of RPM was designed to be adaptable to any geographic region, here we describe an initial version of the model adapted for the power system in Colorado. We present example scenario results from this first version of RPM, including an example of a 30%-by-2020 renewable electricity penetration scenario. Under the assumptions used, the preliminary scenario analysis demonstrates that wind technologies are the dominant contributors to this 30%-by-2020 renewable electricity scenario and that renewable generation largely displaces natural gas. This displacement results in annual carbon dioxide (CO 2 ) emission reductions of approximately 12%. We find that under the least-cost deployment solution from the model, new wind capacity is largely deployed in the north-central and southeastern regions of Colorado and utility-scale solar capacity is largely deployed in the Front Range urban corridor, along with northwestern and south-central Colorado regions. Finally, we observe changes to fossil generation dispatch, particularly with regard to greater power plant ramping and cycling of natural gas combined cycle and coal power plants. In addition to presenting these initial findings, this report provides a detailed documentation of RPM as a new analytic tool for regional power system planning and dispatch.