no code implementations • 26 May 2022 • Armin Aligholian, Hamed Mohsenian-Rad
To tackle these challenges, we propose an unsupervised graph-representation learning method, called GraphPMU, to significantly improve the performance in event clustering under locationally-scarce data availability by proposing the following two new directions: 1) using the topological information about the relative location of the few available phasor measurement units on the graph of the power distribution network; 2) utilizing not only the commonly used fundamental phasor measurements, bus also the less explored harmonic phasor measurements in the process of analyzing the signatures of various events.
no code implementations • 17 Jan 2022 • Ali Nejat, Laura Solitare, Edward Pettitt, Hamed Mohsenian-Rad
Community resilience in the face of natural hazards relies on a community's potential to bounce back.
no code implementations • 19 Sep 2021 • Ehsan Samani, Mahdi Kohansal, Hamed Mohsenian-Rad
Our analysis includes developing a new strategy for convergence bidding.
no code implementations • 30 Nov 2020 • Ehsan Samani, Hamed Mohsenian-Rad
To address this open problem, in this paper, we study three years of real-world market data from the California ISO energy market.
no code implementations • 30 Jul 2020 • Armin Aligholian, Alireza Shahsavari, Emma Stewart, Ed Cortez, Hamed Mohsenian-Rad
The proposed unsupervised event detection and clustering methods are applied to real-world micro-PMU data.
no code implementations • 11 Dec 2019 • Armin Aligholian, Alireza Shahsavari, Ed Cortez, Emma Stewart, Hamed Mohsenian-Rad
It uses the same features that are often used in the literature to detect events in micro-PMU data.
no code implementations • 19 Mar 2018 • Wayes Tushar, Chau Yuen, Hamed Mohsenian-Rad, Tapan Saha, H. Vincent Poor, Kristin L Wood
Peer-to-peer (P2P) energy trading has emerged as a next-generation energy management mechanism for the smart grid that enables each prosumer of the network to participate in energy trading with one another and the grid.