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Reliability Analysis of Power Grids Considering Component Failures of Variable Energy Resources

delete2025-11-01
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PRE
AI
D
Dilip Pandit *
R
R. K. Saket
A
Atri Bera
N
Niannian Cai
N
Nga Nguyen
DOI:10.1109/TIA.2025.3577149delete
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Abstract

Abstract

En 中文
This paper proposes an improved model for the reliability assessment of power systems considering component failures of variable energy resources (VER). The inherent intermittency of VER such as solar photovoltaic (PV) and wind farms, along with their susceptibility to component failures, present significant challenges to reliable system operation. These issues, combined with power grid operation and network constraints, complicate the reliable operation of VER-integrated power systems. To address these concerns, this paper introduces a reliability assessment framework that considers VER input variability, its impact on component availability, and their resulting impact on overall system reliability. Stochastic models based on discrete Markov processes are developed to incorporate variable irradiance, wind speeds, and their effects on PV and wind component failure rates. A next-event and state transition-based approach is then developed to integrate the stochastic models into a mixed-timing sequential Monte Carlo simulation framework for composite reliability assessment. Case studies on the RTS-GMLC system demonstrate the effectiveness of the proposed model in evaluating the reliability of VER-integrated systems.
Keywords:
Reliability
Wind speed
Wind farms
Wind turbines
Stochastic processes
Power system reliability
Maintenance engineering
Computational modeling
Monte Carlo methods
Vectors
Composite reliability assessment
failure rates
Monte Carlo simulation
variable energy resources (VER)

Journal

IEEE Transactions on Industry Applications cover
IEEE Transactions on Industry Applications
IF:
4.5
Papers:
1.1W
Citations:
3.5W

Organization

I
indian institute of technology system (iit system)
Scholars:
9.3W
Papers: 9.9W
Citations: 93
U
united states department of energy (doe)
Scholars:
11.2W
Papers: 9.6W
Citations: 246
S
Sandia National Laboratories
Scholars:
5.3K
Papers: 3.7K
Citations: 6.4K
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