Date of Award

2020

Document Type

Dissertation

Degree Name

Ph.D.

Organizational Unit

Daniel Felix Ritchie School of Engineering and Computer Science, Electrical and Computer Engineering

First Advisor

Amin Khodaei

Second Advisor

Yun-Bo Yi

Third Advisor

Mohammad Abdul Matin

Keywords

Power systems

Abstract

Evolution of modern power systems are more distinct in distribution grids, where the growing integration of microgrids as well as distributed energy resources (DERs), including renewable energy resources, electric vehicles (EVs), and energy storage, poses new challenges and opportunities to grid management and operation. Rapid growth of distribution automation as well as equipment monitoring technologies in the distribution grids further offer new opportunities for distribution asset management. The idea of aggregated DERs is proposed as a remedy to streamline management and operation of advanced distribution grids, as discussed under three subjects in this dissertation. The first subject matter focuses on DER aggregation in microgrid for distribution transformer asset management, while the second one stresses on aggregated DER for developing a spinning reserve-based optimal scheduling model of integrated microgrids. The aggregation of EV batteries in a battery swapping stations (BSS) for enhancing grid operation is investigated in the third subject.

Distribution transformer, as the most critical component in the distribution grids, is selected as the component of the choice for asset management practices, where three asset management studies are proposed. First, an approach in estimating transformer lifetime is presented based on the IEEE Std. C57.91-2011 and using sensory data. Second, a methodology to obtain a low-error estimate of transformer loss-of-life is investigated, leveraging an integrated machine learning and data fusion technique. Finally, a microgrid-based distribution transformer asset management model is developed to prolong the transformer lifetime. The resulting model aims at reshaping the distribution transformer loading via aggregating microgrid DERs in an efficient and asset management-aware manner.

The increasing penetration of microgrids in distribution grids sets the stage for the formation of multiple microgrids in an integrated fashion. Accordingly, a spinning reserved based optimal scheduling model for integrated microgrids is proposed to minimize not only the operation cost associated with all microgrids in the grid-connected operation, but also the costs of power deficiency and spinning reserve in the islanded operation mode. The resulting model aims at determining an optimal configuration of the system in the islanded operation, i.e., optimal super-holons combination, which plays a key role in minimizing the system-aggregated operation cost and improving the overall system reliability.

The evolving distribution grids introduce the concept of the BSS, which is emerging as a viable means for fast energy refill of EVs, to offer energy and ancillary services to the distribution grids through DER aggregation. Using a mixed-integer linear programming method, an uncertainty-constrained BSS optimal operation model is presented that not only covers the random customer demands of fully charged batteries, but also focuses on aggregating the available distributed batteries in the BSS to reduce its operation cost. Furthermore, the BSS is introduced as an energy storage for mitigating solar photovoltaic (PV) output fluctuations, where the distributed batteries in the BSS are modeled as an aggregated energy storage to capture solar generation variability.

Numerical simulations demonstrate the effectiveness of the proposed models as well as their respective viability in achieving the predefined operational objectives.

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Mohsen Mahoor

Provenance

Received from ProQuest

File Format

application/pdf

Language

en

File Size

148 p.

Discipline

Engineering, Electrical engineering, Energy

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