Search Results for author:
Found 7 papers, 2 papers with code
Impact of Internal Algebraic Variable Treatment on Transient Stability Simulation Performance
It is a general notion that, in transient stability simulations, reducing the number of algebraic variables for the differential-algebraic equations (DAE) can improve the simulation performance.
Fusion of Model-free Reinforcement Learning with Microgrid Control: Review and Insight
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 regulation.
Andes_gym: A Versatile Environment for Deep Reinforcement Learning in Power Systems
The environment leverages the modeling and simulation capability of ANDES and the reinforcement learning (RL) environment OpenAI Gym to enable the prototyping and demonstration of RL algorithms for power systems.
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.
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.
