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System Architecture for Distributed Control Systems and Electricity Market Infrastructures.
|Title:||System Architecture for Distributed Control Systems and Electricity Market Infrastructures.|
|Contributors:||Mechanical Engineering (department)|
|Date Issued:||Aug 2018|
|Publisher:||University of Hawaiʻi at Mānoa|
|Abstract:||Societal interests and environmental considerations continue to fuel the evolution of the|
modern energy grid. As we move towards a system with increased and decentralized integration
of renewable energies, the dynamic and volatile nature of these renewables need to
be considered. This calls for a paradigm shift not only in the planning and operation of
our energy grid, but also in the way energy is consumed, marketed, and distributed. That
is, mechanisms are needed to control grid demand when needed to ensure the important
balance of demand and supply on the grid. Much theoretical work exists to address these
challenges, including new control strategies focused on optimization of networked resources,
strategies that focus on optimizing behaviors, and dierent game-theoretic market infrastructures
that economically incentivize the use of novel demand response strategies. An
agent-based testbed system has thus been architected to allow rapid development of smart
agents that implement these control strategies and market infrastructures to test their interactions
when deployed in a modern information and communication technology system.
The behavior of various roles (e.g. system operator, demand response aggregators, and residential
homes) can be programmed in the form of Python applications that communicate
over the MQTT protocol. The use of a graph databases for cyber-physical energy system
modeling is demonstrated as a conguration and management tool for running distributed
co-simulations. A web application for monitoring and control for each role is backed by relational
and graph databases. All system components can be adapted for dierent purposes
and then deployed using Docker containers. Two use case scenarios were implemented and
demonstrated the information system's ability to simulate dynamic pricing DR programs
and emergency DR programs utilizing the multi-agent system. Testing distributed agents
in the presented virtual Smart Grid testbed is shown to help develop these smart agents
and validate their feasibility and ecacy at scale without having to physically implement
the supporting sensor and control infrastructures; thus, the testbed system can bridge the
implementation gap between theoretical models and actual systems.
|Description:||M.S. Thesis. University of Hawaiʻi at Mānoa 2018.|
|Rights:||All UHM dissertations and theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission from the copyright owner.|
|Appears in Collections:||
M.S. - Mechanical Engineering|
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