ECE Dissertation Defense by PhD Candidate, Tan Zhang

Monday, April 23, 2018
10:00 am
Floor/Room #: 
AK 218

Title:

Adaptive Energy Storage System Control for Microgrid Stability Enhancement

 

Abstract:

Microgrids are local power systems of different sizes inside the distribution systems. Each contains a group of interconnected loads and distributed energy resources that acts as a single controllable entity with respect to the grid. Their islanding operation capabilities during emergencies improve the resiliency and reliability of the electric energy supply. Maintaining microgrid stability is challenging due to its low kinetic energy storage capacity, unpredictable system contingencies and power generation from renewable resources.

 

This dissertation highlights the efficacy of flexibly utilizing the battery energy storage systems to enhance the stability of microgrids. It introduces a set of autonomous adaptive control strategies for storage converters to achieve fast microgrid frequency and voltage regulations. The adaptive frequency regulation strategy combines a phase-locked loop frequency measurement based adaptive nonlinear droop control with a simultaneous fast secondary control to help the microgrid frequency quickly return to its nominal value with a zero steady state error after disturbances. The adaptive voltage regulation methodology further enhances microgrid induction motor post-fault speed recovery via adaptively setting the voltage regulator reference point after sensing the low voltage condition. This work also assists in the microgrid design process by determining the normalized minimum storage converter sizing under a wide range of microgrid motor inertia, loading and fault clearing time with both symmetrical and asymmetrical fault types.

 

This study evaluates the expandability of the proposed control methodologies under an unbalanced meshed microgrid with fault-induced feeder switching and multiple contingencies in addition to random power output from renewable generators. The favorable results demonstrate the control robustness under a dynamic changing environment.

 

Research Advisor:

Dr. Alexander E. Emanuel

ECE Department, WPI

 

Committee Members:

Dr. Marija D. Ilić

IDSS, Massachusetts Institute of Technology (MIT)

 

Dr. John Orr

Advisor, ECE Department, WPI

 

Dr. Aleksandar Stanković

ECE Department, Tufts University