A Reinforcement Learning Embedded Surrogate Lagrangian Relaxation Method for Fast Solving Unit Commitment Problems
Unit commitment problems are operation optimization problems solved by independent
system operators (ISOs). These problems generally need to be solved within a limited time …
system operators (ISOs). These problems generally need to be solved within a limited time …
Multi-scale spatio-temporal transformer: A novel model reduction approach for day-ahead security-constrained unit commitment
M Liu, X Kong, K **ong, J Wang, Q Lin - Applied Energy, 2025 - Elsevier
Security-constrained unit commitment (SCUC) in large-scale power systems faces
significant computational challenges, particularly with increasing renewable energy …
significant computational challenges, particularly with increasing renewable energy …
Data-augmentation acceleration framework by graph neural network for near-optimal unit commitment
The acceleration of large-scale unit commitment (UC) problems has been a long-standing
challenge in the power industry. Independent system operators are required to find a near …
challenge in the power industry. Independent system operators are required to find a near …
[HTML][HTML] Feasible-enabled integer variable warm start strategy for security-constrained unit commitment
Security-constrained unit commitment (SCUC) is a crucial procedure in power system
planning and operation. As renewable resources are integrated, it is suggested to perform …
planning and operation. As renewable resources are integrated, it is suggested to perform …
Selectively Linearized Neural Network Based RoCoF-Constrained Unit Commitment in Low-Inertia Power Systems
M Tuo, X Li - 2023 North American Power Symposium (NAPS), 2023 - ieeexplore.ieee.org
Conventional synchronous generators are gradually being replaced by inverter-based
resources. Such transition introduces more complicated operation conditions and the …
resources. Such transition introduces more complicated operation conditions and the …
A synthetic texas backbone power system with climate-dependent spatio-temporal correlated profiles
Most power system test cases only have electrical parameters and can be used only for
studies based on a snapshot of system profiles. To facilitate more comprehensive and …
studies based on a snapshot of system profiles. To facilitate more comprehensive and …
Graph neural networks for power grid operational risk assessment under evolving unit commitment
This article investigates the ability of graph neural networks (GNNs) to identify risky
conditions in a power grid over the subsequent few hours, without explicit, high-resolution …
conditions in a power grid over the subsequent few hours, without explicit, high-resolution …
An objective feasibility pump method for optimal power flow with unit commitment variables
P Li, J Su, X Bai - Electric Power Systems Research, 2024 - Elsevier
Unexpected and significant power fluctuations caused by severe faults or rapid changes in
renewable energy generation could lead to the divergence of the security constraint …
renewable energy generation could lead to the divergence of the security constraint …
Transmission Expansion Planning for Renewable-Energy-Dominated Power Grids Considering Climate Impact
As renewable energy is becoming the major resource in future power grids, the weather and
climate can have a higher impact on grid reliability. Transmission expansion planning (TEP) …
climate can have a higher impact on grid reliability. Transmission expansion planning (TEP) …
[HTML][HTML] Feasibility-guaranteed machine learning unit commitment: Fuzzy Optimization approaches
The unit commitment (UC) problem is solved several times daily in a limited amount of time
and is commonly formulated using mixed-integer linear programs (MILP). However, solution …
and is commonly formulated using mixed-integer linear programs (MILP). However, solution …