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Development and deployment of multi-scale production cost models
Development and deployment of multi-scale production cost models
<p>The complexity and resolution required to model the modern power system is increasing. Stochastic resources such as wind and solar motivate a need to study numerous weather conditions and deployment scenarios. Distributed energy resources, new bulk power generation, inter-sectoral dependencies, and evolving consumer preferences also contribute to the growing complexity of the system. Improved tools are necessary to study the impact of these changes to the power system. In this project we propose to work with industry to increase the fidelity and accuracy of production cost models (PCM) while simultaneously decrease computation time. Industry partners will participate in NREL led workshops for the Grid Modernization Laboratory Consortium (GMLC) that assist participants in running detailed models of their systems on DOE computing facilities with laboratory methods. The software vendor Energy Exemplar will contribute to the project and assist in the commercialization of improved PCM methods. Because of this project, members of the Technical Review Committee (TRC) will be able to run 60,000 node models of the Eastern Interconnection at a 5-minute resolution using mixed integer optimizations. This greatly exceeds existing industry capabilities, and will allow for more rigorous analysis of the impacts of wind, solar, and distributed energy resources. Power system planners, reliability organizations, regulators and policy makers have indicated that in order to plan for the rapidly changing electricity system they must be able to simulate a broad range of highly detailed power system scenarios. PCMs are one of many tools used by these groups for planning and operating the power system. Traditionally, system planners have been forced to choose between two conflicting parameters in PCMs: model resolution and solve time. Reducing model resolution reduces the relevancy of the simulated system in representing the actual system, but decreases solve time. Long solve times limit the number of scenarios that planners and reliability coordinators can analyze. This project aims to address three industry challenges: 1) reduce the time necessary to solve PCM simulations; 2) improve the accuracy of PCM through geographic decomposition of the SCUC and SCED; and 3) apply stochastic methods to address the inherent stochasticity in power system planning and operations. NREL's Peregrine computing facility will be leveraged for both development of new methods for PCM and deployment of existing methods on industry defined use cases. One of the primary focus regions for the project will be the Eastern Interconnection. This project will build on the success of Eastern Renewable Generation Integration Study (ERGIS) to allow industry partners to simulate their own scenarios on the ERGIS model, and others.</p>
