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Found 13 papers, 2 papers with code
Coordination of Damping Controllers: A Data-Informed Approach for Adaptability
This is a performance measure based on the physics of the power system, which encapsulates the oscillation energy related to synchronous generators.
Modeling the impact of extreme summer drought on conventional and renewable generation capacity: methods and a case study on the Eastern U.S. power system
This paper proposes a systematic, analytical approach for assessing the impacts of extreme summer drought events on the available capacity of hydro, thermal, and renewable energy generators.
DiME and AGVis: A Distributed Messaging Environment and Geographical Visualizer for Large-scale Power System Simulation
This paper introduces the messaging environment and the geographical visualization tool of the CURENT Large-scale Testbed (LTB) that can be used for large-scale power system closed-loop simulation.
Virtual Inertia Scheduling for Power Systems with High Penetration of Inverter-based Resources
Then, VIS-based real-time economic dispatch (VIS-RTED) is formulated to minimize generation and reserve costs, with a full consideration of dynamic frequency constraints and derived inertia support reserve constraints.
Fusion of Model-free Reinforcement Learning with Microgrid Control: Review and Vision
Challenges and opportunities coexist in microgrids as a result of emerging large-scale distributed energy resources (DERs) and advanced control techniques.
Decentralized and Coordinated Vf Control for Islanded Microgrids Considering DER Inadequacy and Demand Control
Then, a decentralized and coordinated control framework is proposed to regulate the output of inverter based generations and reallocate limited DER capacity for Vf control.
DLMP of Competitive Markets in Active Distribution Networks: Models, Solutions, Applications, and Visions
The DLMP provides a solution that can be essential for competitive market operation in future distribution systems.
Deep Reinforcement Learning based Model-free On-line Dynamic Multi-Microgrid Formation to Enhance Resilience
The proposed deep RL method provides real-time computing to support on-line dynamic MMGF scheme, and the scheme handles a long-term resilience enhancement problem using adaptive on-line MMGF to defend changeable conditions.
Deep Learning based Model-free Robust Load Restoration to Enhance Bulk System Resilience with Wind Power Penetration
This paper proposes a new deep learning (DL) based model-free robust method for bulk system on-line load restoration with high penetration of wind power.
Encoding Frequency Constraints in Preventive Unit Commitment Using Deep Learning with Region-of-Interest Active Sampling
Frequency-constrained unit commitment (FCUC) is proposed to address this challenge.
Hybrid Imitation Learning for Real-Time Service Restoration in Resilient Distribution Systems
Self-healing capability is one of the most critical factors for a resilient distribution system, which requires intelligent agents to automatically perform restorative actions online, including network reconfiguration and reactive power dispatch.
Effective Parallelism for Equation and Jacobian Evaluation in Power Flow Calculation
This letter investigates parallelism approaches for equation and Jacobian evaluations in large-scale power flow calculation.
Hybrid Symbolic-Numeric Library for Power System Modeling and Analysis
This paper proposes a two-layer hybrid library consisted of a symbolic layer for descriptive modeling and a numeric layer for vector-based numerical computation.
