Data-driven control and optimal management of electric distribution grid with high penetration of distributed energy resources (DERs) based on spectral clustering

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Patel, S. (2022). Data-driven control and optimal management of electric distribution grid with high penetration of distributed energy resources (DERs) based on spectral clustering. Unc Charlotte Electronic Theses And Dissertations.
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Abstract

Motivated by the government's clean energy targets, the penetration of Distributed Energy Resources (DER) is increasing. These DERs interconnections bring the added generation and storage capacity at the distribution level. Also, with the increasing implementation of smart inverters and Advanced Distribution Management Systems (ADMS), the flexibility of the DERs can be leveraged to solve the distribution grid issues like abnormal voltages, intermittencies, and thermal overloads. The proposed work focuses on the development of a robust distributed control architecture to control and optimally manage the load and PV variations using energy storage by creating the virtual clusters of the distribution grid. The approach is based on a spectral clustering distributed control methdology that partition the grid into manageable clusters. The cluster of the distribution grid represents a good balance of local load and DER generation. An approach for reactive power to voltage sensitivity is also proposed for voltage regulation purposes at the cluster level based on the grid measurements. The cluster configurations adapt to accommodate the varying grid topology or changing load and DER generation. For the distribution grids receiving the set-points at the substation level for management of transmission power flow, an Alternating Direction Methods of Multipliers (ADMM) based optimization is proposed to share the area set-points among the clusters based on the state of charge of each cluster. The controllable assets of each cluster (BESS) are managed through model predictive control. The improvement in the grid resiliency is demonstrated through the implementation of the complete framework to support the loads on the healthy part of the grid without interruptions during the contingency/outage scenarios on the distribution grid.

Details
Author

Patel, Shyamal

Title

Data-driven control and optimal management of electric distribution grid with high penetration of distributed energy resources (DERs) based on spectral clustering

Physical Description

1 online resource (176 pages) : PDF

Date

2022

Degree Granting Institution

University of North Carolina at Charlotte

Abstract

Motivated by the government's clean energy targets, the penetration of Distributed Energy Resources (DER) is increasing. These DERs interconnections bring the added generation and storage capacity at the distribution level. Also, with the increasing implementation of smart inverters and Advanced Distribution Management Systems (ADMS), the flexibility of the DERs can be leveraged to solve the distribution grid issues like abnormal voltages, intermittencies, and thermal overloads. The proposed work focuses on the development of a robust distributed control architecture to control and optimally manage the load and PV variations using energy storage by creating the virtual clusters of the distribution grid. The approach is based on a spectral clustering distributed control methdology that partition the grid into manageable clusters. The cluster of the distribution grid represents a good balance of local load and DER generation. An approach for reactive power to voltage sensitivity is also proposed for voltage regulation purposes at the cluster level based on the grid measurements. The cluster configurations adapt to accommodate the varying grid topology or changing load and DER generation. For the distribution grids receiving the set-points at the substation level for management of transmission power flow, an Alternating Direction Methods of Multipliers (ADMM) based optimization is proposed to share the area set-points among the clusters based on the state of charge of each cluster. The controllable assets of each cluster (BESS) are managed through model predictive control. The improvement in the grid resiliency is demonstrated through the implementation of the complete framework to support the loads on the healthy part of the grid without interruptions during the contingency/outage scenarios on the distribution grid.

Genre

doctoral dissertations

Subjects--Topics

Electrical engineering

Degree

Ph.D.

Keywords

Admm
Cluster Control
Critical Loads
Distributed Energy Resources
Distribution Grid Management
Resilience

Subject Area

Electrical Engineering

Advisor(s)

Kamalasadan, Sukumar

Committee Members

Cecchi, Valentina
Ebong, Abasifreke
Ogunro, Vincent

Degree Note

Thesis (Ph.D.)--University of North Carolina at Charlotte, 2022.

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Rights Holder Information

Copyright is held by the author unless otherwise indicated.

Identifier

Patel_uncc_0694D_13094

Permalink

http://hdl.handle.net/20.500.13093/etd:2824