The growing integration of distributed energy resources (DERs) in distribution grids raises various reliability issues due to DER's uncertain and complex behaviors. With large-scale DER penetration in distribution grids, traditional outage detection methods, which rely on customers report and smart meters' “last gasp” signals, will have poor performance, because renewable generators and storage and the mesh structure in urban distribution grids can continue supplying power after line outages. To address these challenges, we propose a data-driven outage monitoring approach based on the stochastic time series analysis with a theoretical guarantee. Specifically, we prove via power flow analysis that dependency of time-series voltage measurements exhibits significant statistical changes after line outages. This makes the theory on optimal change-point detection suitable to identify line outages. However, existing change point detection methods require post-outage voltage distribution, which are unknown in distribution systems. Therefore, we design a maximum likelihood estimator to directly learn distribution pa-rameters from voltage data. We prove the estimated parameters-based detection also achieves optimal performance, making it extremely useful for fast distribution grid outage identifications. Furthermore, since smart meters have been widely installed in distribution grids and advanced infrastructure (e.g., PMU) has not widely been available, our approach only requires voltage magnitude for quick outage identification. Simulation results show highly accurate outage identification in eight distribution grids with 17 configurations with and without DERs using smart meter data.
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Review of Control Techniques for Wind Energy Systems
In recent years, penetration of renewable energy resources into the power grid has increased significantly. Wind, as a renewable, clean, and abundantly available source of energy, has an important share in the energy mix. However, increasing the penetration of wind power in the power grid can adversely affect the power quality and introduce new operational challenges. This paper discusses issues related to the integration of wind farms in the power system, such as maximum power point tracking, fault ride-through capabilities, interarea and subsynchronous oscillations, and voltage flicker, and provides a review of the existing control strategies to address these issues in Types I, II, III, and IV wind turbines. This paper also identifies challenges and opportunities ahead.
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- NSF-PAR ID:
- 10282658
- Date Published:
- Journal Name:
- Energies
- Volume:
- 13
- Issue:
- 24
- ISSN:
- 1996-1073
- Page Range / eLocation ID:
- 6666
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/en13246666
