Search Results for author:
Found 6 papers, 3 papers with code
GP CC-OPF: Gaussian Process based optimization tool for Chance-Constrained Optimal Power Flow
The developed tool presents a novel data-driven approach based on the GP regression model for solving the CC-OPF problem with a trade-off between complexity and accuracy.
Data-Driven Chance Constrained AC-OPF using Hybrid Sparse Gaussian Processes
The alternating current (AC) chance-constrained optimal power flow (CC-OPF) problem addresses the economic efficiency of electricity generation and delivery under generation uncertainty.
Data-Driven Stochastic AC-OPF using Gaussian Processes
Unfortunately, the most accessible renewable power sources, such as wind and solar, are highly fluctuating and thus bring a lot of uncertainty to power grid operations and challenge existing optimization and control policies.
Identification of Stability Regions in Inverter-Based Microgrids
We also provide a conservative upper threshold of the eigenvalues that are universal for any systems within a reasonable range of R/X ratios.
Network Topology Invariant Stability Certificates for DC Microgrids with Arbitrary Load Dynamics
DC microgrids are prone to small-signal instabilities due to the presence of tightly regulated loads.
A Passivity Interpretation of Energy-Based Forced Oscillation Source Location Methods
The paper goes on to develop a simulation-free algorithm for predicting the performance of the DEF method in a generalized power system, and it analyzes the passivity of three non-classical load and generation components.
Systems and Control Systems and Control
