Integrated Active and Reactive Power Management of Power Distribution System Considering Distributed Energy Storage and PV Farms

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Ahmed, M. (2018). Integrated Active and Reactive Power Management of Power Distribution System Considering Distributed Energy Storage and PV Farms. Unc Charlotte Electronic Theses And Dissertations.
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Abstract

Modern electric distribution system with distributed Photo-Voltaic (PV) farms and energy storage units have been facing technical challenges due to the difficulty in managing them collectively. This dissertation presents new solutions for energy management of PV farms integrated power distribution systems using energy storage. First, a new local net active power management methodology for PV point of common coupling (PCC) is discussed. Further, this approach is extended as an integrated net active power management architecture based on an optimal ramp rate algorithm. The approach considers the ramp rate and state-of-charge of the energy storage device that can be used for resource allocation. Second, an integrated feeder level peak load management methodology with a load prediction approach is illustrated with the methodology applied to separated and decomposed load types. Third, a coordinated volt-var control approach considering a fast and slow change in the active power is illustrated. Fourth, a dynamic volt-var control approach with sensitivity based algorithm is illustrated. The novelty in the volt-var control approach is that the methodology coordinate with legacy devices and voltage source converters. Also, a dynamically changing framework is designed based on active and reactive power sensitivity. Finally, an integrated volt-var-watt control approach is illustrated. This approach coordinates with active and reactive power in the feeder considering the reactive and active power capability of the device.

Details
Author

Ahmed, Muhammad

Title

Integrated Active and Reactive Power Management of Power Distribution System Considering Distributed Energy Storage and PV Farms

Physical Description

1 online resource (187 pages) : PDF

Date

2018

Degree Granting Institution

University of North Carolina at Charlotte

Abstract

Modern electric distribution system with distributed Photo-Voltaic (PV) farms and energy storage units have been facing technical challenges due to the difficulty in managing them collectively. This dissertation presents new solutions for energy management of PV farms integrated power distribution systems using energy storage. First, a new local net active power management methodology for PV point of common coupling (PCC) is discussed. Further, this approach is extended as an integrated net active power management architecture based on an optimal ramp rate algorithm. The approach considers the ramp rate and state-of-charge of the energy storage device that can be used for resource allocation. Second, an integrated feeder level peak load management methodology with a load prediction approach is illustrated with the methodology applied to separated and decomposed load types. Third, a coordinated volt-var control approach considering a fast and slow change in the active power is illustrated. Fourth, a dynamic volt-var control approach with sensitivity based algorithm is illustrated. The novelty in the volt-var control approach is that the methodology coordinate with legacy devices and voltage source converters. Also, a dynamically changing framework is designed based on active and reactive power sensitivity. Finally, an integrated volt-var-watt control approach is illustrated. This approach coordinates with active and reactive power in the feeder considering the reactive and active power capability of the device.

Genre

doctoral dissertations

Subjects--Topics

Electrical engineering

Degree

Ph.D.

Keywords

Energy Storage System
Load Prediction
Net-Load
Sensitivity Analysis
Volt-Var-Watt Control

Subject Area

Electrical Engineering

Advisor(s)

Kamalasadan, Sukumar

Committee Members

Cecchi, Valentina
Kakad, Yogendra
Ali-Hasan, Mohamed
Noras, Maciej

Degree Note

Thesis (Ph.D.)--University of North Carolina at Charlotte, 2018.

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Rights Holder Information

Copyright is held by the author unless otherwise indicated.

Identifier

Ahmed_uncc_0694D_11928

Permalink

http://hdl.handle.net/20.500.13093/etd:1606