Demonstration of demand driven deployment capabilities in cyclus

Gwendolyn J. Chee, Jin Whan Bae, Robert R. Flanagan, Roberto E. Fairhurst Agosta, Kathryn D. Huff

Research output: Contribution to conferencePaperpeer-review

Abstract

In this work, we developed demand-driven deployment capabilities in Cyclus, d3ploy. User-controlled capabilities such as supply/capacity buffers, constraint deployment, prediction algorithms, and installed capacity deployment were introduced to give a user tools to minimize commodity undersupply in the simulation. We demonstrate d3ploy's capability to automatically deploy fuel cycle facilities to meet various types of user-defined power demands: constant, linearly increasing, and sinusoidal.

Original languageEnglish
Pages394-401
Number of pages8
StatePublished - 2020
Event14th International Nuclear Fuel Cycle Conference, GLOBAL 2019 and Light Water Reactor Fuel Performance Conference, TOP FUEL 2019 - Seattle, United States
Duration: Sep 22 2019Sep 27 2019

Conference

Conference14th International Nuclear Fuel Cycle Conference, GLOBAL 2019 and Light Water Reactor Fuel Performance Conference, TOP FUEL 2019
Country/TerritoryUnited States
CitySeattle
Period09/22/1909/27/19

Funding

This research is funded by the Department of Energy (DOE) Office of Nuclear Energy’s Nuclear Energy University Program (Project 16-10512, DE-NE0008567) "Demand-Driven Cycamore Archetypes". The authors want to thank members of the Advanced Reactors and Fuel Cycles (ARFC) group at the University of Illinois at Urbana-Champaign. We also thank our colleagues from the Cyclus community, particularly those in the University of Wisconsin Computational Nuclear Engineering Research Group (CNERG) and the University of South Carolina Energy Research Group (ERGS) for collaborative Cyclus development. This research is funded by the Department of Energy (DOE) Office of Nuclear Energy's Nuclear Energy University Program (Project 16-10512, DE-NE0008567) "Demand-Driven Cycamore Archetypes". The authors want to thank members of the Advanced Reactors and Fuel Cycles (ARFC) group at the University of Illinois at Urbana-Champaign. We also thank our colleagues from the Cyclus community, particularly those in the University of Wisconsin Computational Nuclear Engineering Research Group (CNERG) and the University of South Carolina Energy Research Group (ERGS) for collaborative Cyclus development.

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