TY - DATA T1 - Code underlying: Balancing Operator’s Risk Averseness in Model Predictive Control for Real-time Reservoir Flood Control. PY - 2025/02/05 AU - Dimitri Solomatine AU - Edo Abraham AU - Ja-Ho Koo AU - Andreja Jonoski UR - DO - 10.4121/9a6a0464-2981-470a-8d7a-48c7e7fff27d.v1 KW - MPC KW - Model Predictive Control KW - Dynamic Weight KW - Flood control KW - Reservoirs N2 -
Python codes for the parameterized dynamic MPC implementation.
Inflow data is collected from the Data portal managed by Korean government.
PDMPC main is the python file to run the PDMPC, and other files are for the function or class using in main.py.
Formulation.py contains only linear MPC formulation by Pyomo. Evaluator.py includes python functions to evaluate the linear MPC results.
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