Doctoral Dissertations

Keywords and Phrases

Dual Active Bridge; Generalized Average Modeling; Microgrids; Nonintrusive Load Monitoring; Stochastic Hybrid System

Abstract

"A modeling framework for dc microgrids and distribution systems based on the dual active bridge (DAB) topology is presented. The purpose of this framework is to accurately characterize dynamic behavior of multi-converter systems as a function of exogenous load and source inputs. The base model is derived for deterministic inputs and then extended for the case of stochastic load behavior. At the core of the modeling framework is a large-signal DAB model that accurately describes the dynamics of both ac and dc state variables. This model addresses limitations of existing DAB converter models, which are not suitable for system-level analysis due to inaccuracy and poor upward scalability. The converter model acts as a fundamental building block in a general procedure for constructing models of multi-converter systems. System-level model construction is only possible due to structural properties of the converter model that mitigate prohibitive increases in size and complexity.

To characterize the impact of randomness in practical loads, stochastic load descriptions are included in the deterministic dynamic model. The combined behavior of distributed loads is represented by a continuous-time stochastic process. Models that govern this load process are generated using a new modeling procedure, which builds incrementally from individual device-level representations. To merge the stochastic load process and deterministic dynamic models, the microgrid is modeled as a stochastic hybrid system. The stochastic hybrid model predicts the evolution of moments of dynamic state variables as a function of load model parameters. Moments of dynamic states provide useful approximations of typical system operating conditions over time. Applications of the deterministic models include system stability analysis and computationally efficient time-domain simulation. The stochastic hybrid models provide a framework for performance assessment and optimization"--Abstract, page iv.

Advisor(s)

Kimball, Jonathan W.

Committee Member(s)

Crow, Mariesa
Ferdowsi, Mehdi
McMillin, Bruce M.
Shamsi, Pourya

Department(s)

Electrical and Computer Engineering

Degree Name

Ph. D. in Electrical Engineering

Sponsor(s)

National Science Foundation (U.S.)
Missouri Space Grant Consortium

Comments

This work was funded by the National Science Foundation, award 1406156, and by a fellowship from the NASA-Missouri Space Grant Consortium.

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2018

Journal article titles appearing in thesis/dissertation

  • An improved generalized average model of dc-dc dual active bridge converters
  • Modeling dual active bridge converters in dc distribution systems
  • Accurate energy use estimation for nonintrusive load monitoring in systems of known devices
  • Modeling and analysis of dc microgrids as stochastic hybrid systems

Pagination

xiv, 164 pages

Note about bibliography

Includes bibliographic references.

Rights

© 2018 Jacob Andreas Mueller, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 11302

Electronic OCLC #

1041858516

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