Return to search

Control Strategies for the Next Generation Microgrids

In the context of the envisioned electric power delivery system of the future, the smart grid, this dissertation focuses on control and management strategies for integration of distributed energy resources in the power system. This work conceptualizes a hierarchical framework for the control of microgrids---the building blocks of the smart grid---and develops the notion of potential functions for the secondary control for devising intermediate set points to ensure feasibility of operation of the system. A scalar potential function is defined for each controllable unit of the microgrid such that its minimization corresponds to achieving the control goal. The set points are dynamically updated using communication within the microgrid. This strategy is generalized to (i) include both local and system-wide constraints and (ii) allow a distributed implementation.

This dissertation also proposes and evaluates a simple yet elaborate distributed strategy to mitigate the transients of controllable devices of the microgrid using local measurements. This strategy is based on response monitoring and is augmented to the existing controller of a power system device. This strategy can be implemented based on either set point automatic adjustment (SPAA) or set point automatic adjustment with correction enabled (SPAACE) methods. SPAA takes advantage of an approximate model of the system to calculate intermediate set points such that the response to each one is acceptable. SPAACE treats the device as a generic system and monitors its response and modulates its set point to achieve the desired trajectory. SPAACE bases its decisions on the trend of variations of the response and accounts for inaccuracies and unmodeled dynamics.

Case studies using the PSCAD/EMTDC software environment and MATLAB programming environment are presented to demonstrate the application and effectiveness of the proposed strategies in different scenarios.

Identiferoai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/33889
Date06 December 2012
CreatorsAli, Mehrizi-Sani
ContributorsReza, Iravani
Source SetsUniversity of Toronto
Languageen_ca
Detected LanguageEnglish
TypeThesis

Page generated in 0.0019 seconds