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 language | English |
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Pages | 394-401 |
Number of pages | 8 |
State | Published - 2020 |
Event | 14th International Nuclear Fuel Cycle Conference, GLOBAL 2019 and Light Water Reactor Fuel Performance Conference, TOP FUEL 2019 - Seattle, United States Duration: Sep 22 2019 → Sep 27 2019 |
Conference
Conference | 14th International Nuclear Fuel Cycle Conference, GLOBAL 2019 and Light Water Reactor Fuel Performance Conference, TOP FUEL 2019 |
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Country/Territory | United States |
City | Seattle |
Period | 09/22/19 → 09/27/19 |
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.