no code implementations • 12 Nov 2023 • Behrouz Azimian, Shiva Moshtagh, Anamitra Pal, Shanshan Ma
Recently, we demonstrated success of a time-synchronized state estimator using deep neural networks (DNNs) for real-time unobservable distribution systems.
no code implementations • 12 Sep 2022 • Mingyue He, Zahra Soltani, Mohammad Ghaljehei, Masoud Esmaili, Shanshan Ma, Mengxi Chen, Mojdeh Khorsand, Raja Ayyanar, Vijay Vittal
The results illustrate the effective-ness of the proposed ACOPF for unbalanced systems in provid-ing a global optimal solution while capturing the non-linearity and non-convexity of ACOPF.
no code implementations • 1 Jul 2022 • Mengxi Chen, Shanshan Ma, Zahra Soltani, Raja Ayyanar, Vijay Vittal, Mojdeh Khorsand
This paper proposes a two-stage stochastic optimization strategy to optimally place the PV smart inverters with Volt-VAr capability for distribution systems with high photovoltaic (PV) penetration to mitigate voltage violation issues.
no code implementations • 29 May 2021 • Karen Montano-Martinez, Sushrut Thakar, Shanshan Ma, Zahra Soltani, Student Member, Vijay Vittal, Life Fellow, Mojdeh Khorsand, Raja Ayyanar, Senior Member, Cynthia Rojas, Member, IEEE
Reliable and accurate distribution system modeling, including the secondary network, is essential in examining distribution system performance with high penetration of distributed energy resources (DERs).
no code implementations • 24 Dec 2020 • Qianzhi Zhang, Zhaoyu Wang, Shanshan Ma, Anmar Arif
This paper proposes a stochastic optimal preparation and resource allocation method for upcoming extreme weather events in distribution systems, which can assist utilities to achieve faster and more efficient post-event restoration.