activity
20202023
most citedDiesel Generator Model Parameterization for Microgrid Simulation Using Hybrid Box-Constrained Levenberg-Marquardt Algorithm

29 citations · 29 across the 4 of their papers we have counts for

collaborators

6 papers

eess.SY2023

Multi-Feeder Restoration using Multi-Microgrid Formation and Management

Valliappan Muthukaruppan, Rongxing Hu, Ashwin Shirsat +4

This papers highlights the benefit of coordinating resources on mulitple active distribution feeders during severe long duration outages through multi-microgrid formation. A graph-…

eess.SY2022

Optimal Control Design for Operating a Hybrid PV Plant with Robust Power Reserves for Fast Frequency Regulation Services

Victor Paduani, Qi Xiao, Bei Xu +2

This paper presents an optimal control strategy for operating a solar hybrid system consisting of solar photovoltaic (PV) and a high-power, low-storage battery energy storage syste…

eess.SY2022

SA-HMTS: A Secure and Adaptive Hierarchical Multi-timescale Framework for Resilient Load Restoration Using A Community Microgrid

Ashwin Shirsat, Valliappan Muthukaruppan, Rongxing Hu +8

Distribution system integrated community microgrids (CMGs) can partake in restoring loads during extended duration outages. At such times, the CMG is challenged with limited resour…

eess.SY2020

A Regression-based Voltage Estimation Method for Distribution Volt-Var Control with Limited Data

Catie McEntee, Ning Lu, David Lubkeman

This paper presents a regression-based method for estimating voltages and voltage sensitivities for volt-var control on distribution circuits with limited data. The estimator uses…

eess.SY202029 cited

Diesel Generator Model Parameterization for Microgrid Simulation Using Hybrid Box-Constrained Levenberg-Marquardt Algorithm

Qian Long, Hui Yu, Fuhong Xie +2

Existing generator parameterization methods, typically developed for large turbine generator units, are difficult to apply to small kW-level diesel generators in microgrid applicat…

eess.SY2020

FeederGAN: Synthetic Feeder Generation via Deep Graph Adversarial Nets

Ming Liang, Yao Meng, Jiyu Wang +2

This paper presents a novel, automated, generative adversarial networks (GAN) based synthetic feeder generation mechanism, abbreviated as FeederGAN. FeederGAN digests real feeder m…