Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Atena Darvishi"'
Detecting Transformer Fault Types from Dissolved Gas Analysis Data Using Machine Learning Techniques
Autor:
Rohan Raghuraman, Atena Darvishi
Publikováno v:
2022 IEEE 15th Dallas Circuit And System Conference (DCAS).
Publikováno v:
IEEE Transactions on Smart Grid. 12:2389-2401
This article discusses how techniques from reinforcement learning (RL) can be exploited to transition to a model-free and scalable wide-area oscillation damping control of power grids. We present two control architectures with distinct features. Perf
Autor:
Innocent Kamwa, Atena Darvishi, C. M. Rergis, Bruce Fardanesh, Ali Moeini, Jinan Huang, Dmitry Rimorov
Publikováno v:
IEEE Transactions on Power Systems. 35:3825-3834
The article proposes a computationally efficient and robust method for estimating impulse or frequency response in the context of black-box multiple-input-multiple-output linear model identification of large power systems from simulations. The propos
Publikováno v:
Power Electronics and Power Systems ISBN: 9783030674816
This chapter discusses a methodology to monitor voltage stability using synchrophasor technology. Voltage Stability Index (VSI) explained here is computed using the PMU measurements for a transmission corridor to determine if the system has any volta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::276e2fddb492097a9bd2e24a826e75ca
https://doi.org/10.1007/978-3-030-67482-3_20
https://doi.org/10.1007/978-3-030-67482-3_20
Publikováno v:
2020 IEEE/PES Transmission and Distribution Conference and Exposition (T&D).
This paper provides a very detail-oriented study to prepare a full pathway for having an advanced closed-loop control implemented on selected controllable assets of N ew York Power Authority (NYPA), including wind generation to improve dynamic stabil
Publikováno v:
ISGT
Increasing uncertainty raised by the integration of renewable energy resources requires an enormous number of simulations to be carried out for the security assessment of the power grid. However, it is challenging to assess the steady-state and dynam
Publikováno v:
HICSS
Publikováno v:
2019 IEEE Power & Energy Society General Meeting (PESGM).
In this paper we present a prototype study of classifying dynamic events using a deep learning (DL) tool for the New York State (NYS) power grid. We use the utility-level full-scale transmission planning model of Eastern Interconnection (EI) in the P
Autor:
Lin Zhu, Yi Zhao, Yilu Liu, Evangelos Farantatos, Atena Darvishi, Huangqin Xiao, Bruce Fardanesh, Mahendra Patel
Publikováno v:
2019 IEEE Power & Energy Society General Meeting (PESGM).
Conventional oscillation damping controllers are typically designed offline for several selected operating conditions using planning models. This practice cannot guarantee their performance under all possible operating conditions, especially under ce
Autor:
Atena Darvishi, Ian Dobson
Publikováno v:
IEEE Transactions on Power Systems. 31:2116-2124
When power grids are heavily stressed with a bulk power transfer, it is useful to have a fast indication of the increased stress when multiple line outages occur. Reducing the bulk power transfer when the outages are severe could forestall further ca