Equation-Free System-Level Modeling and Analytics in Energy Processing Systems
Wang, Gang.
2019
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Energy processing
systems have a distinct multi-scale nature, which emerges as a critical challenge in
analyzing their dynamical behavior. Meanwhile, the development of smart grids leads to
the integration of complex power electronic infrastructures, of distributed renewable
generation, and of evolving control and communication strategies. Therefore, it is
challenging to establish a detailed ... read moremodel and simulate the multi-scale and large-size
energy system. In our research, equation-free modeling method is utilized, which enables
models at the microscopic (component) level of description to perform the modeling task
at the macroscopic (system) level. The modeling of the microscopic system requires
formulating the exact models and solving explicit equations. However, the equation-free
approach utilizes the characteristics of the component model and numerical algorithms to
analyze the energy system at the macroscopic level, which typically requires much
coarser information of the system. A computational framework is built to model the
energy processing system with the equation-free method. This framework can be used in
the modeling of power electronic circuits and power systems. The macroscopic behavior of
the model can answer system-level questions without prior knowledge of the system-level
model. For instance, the steady-state of a series resonant circuit (SRC) is derived with
short burst simulation of the component-level model. Meanwhile, the macro-level model
can perform the stability analysis and bifurcation detection of the circuit. In the
application to power systems, our equation-free approach realizes the reduced-order
modeling and stability evaluation for the demonstrated system. Therefore, this
computer-aided modeling framework can analyze the well-encapsulated and complex energy
systems by systematically deriving macro-level
information.
Thesis (Ph.D.)--Tufts University, 2019.
Submitted to the Dept. of Electrical Engineering.
Advisor: Aleksandar Stanković.
Committee: Jason Rife, Usman Khan, and Andrija Sarić.
Keyword: Electrical engineering.read less - ID:
- sq87c702x
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