Equation-Free System-Level Modeling and Analytics in Energy Processing Systems - Wang, Gang. (Tufts University. Tisch Library., 2019)
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 model 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.