A hierarchy of microgrid models with some applications

This dissertation proposes a hierarchy of microgrid models that can be utilized for power system analysis and control design purposes. The microgrid models are classified according to time resolution and, consequently, according to complexity and computational cost as well. Our approach involves three key stages: (1) the formulation of high-order models, using existing circuit and control laws in the literature, followed by (2) a systematic reduction of the high-order models to reduced-order models using singular perturbation analysis and, finally (3) a hierarchical classification of the high-order and reduced-order models according to the time-scales we propose they should be utilized for. The resulting hierarchy of microgrid models is comprised of a microgrid high-order model (µHOm), the microgrid reduced-order model 1 (µROm1), the microgrid reduced-order model 2 (µROm2), and the microgrid reduced-order model 3 (µROm3), the last three of which are developed in this work. Each microgrid model we develop is composed of models for three-phase inverters, microturbines, type-C wind turbine generators, distribution line networks, and generic elements (e.g. loads) connected to the network. We identify the time resolution of the models and analyze the performance of these models using various power system test cases. We also showcase two applications of our reduced-order models: first in the design of a robust synchronization method for electric power generators, and secondly in the development of a hardware-in-the-loop laboratory for analysis and testing of microgrid controls.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2019

Author dc:creator

• Ajala, Olaolu

Contributors dc:contributor

• Domínguez-García, Alejandro D.
• Sauer, Peter W.
• Liberzon, Daniel M.
• Bose, Subhonmesh

• Microgrids, Distributed Energy Resources, High-Order Modeling, Reduced-Order Modeling, Singular Perturbation Analysis

Statement dc:rights

• Copyright 2018 Olaoluwapo Ajala

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/102828

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/102828