An efficient modeling and simulation platform to assess autonomous power systems
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Autonomous power system (APS) that exploits local renewable energy sources has potential to provide useful energy at lower costs when compared with conventional energy. Modern APS involves the control of renewable energy systems with intermittent power production; interaction with conventional energy generation; and management of energy storage and consumption. The system configuration of an APS is often complex due to the mix of energy generations and desire to optimize the utilization of the renewable energy. The fact that a large amount of data must be processed within a very short period of time makes the APS very challenging. In this work, we introduce a modeling and simulation methodology to analyze autonomous power systems. We develop a simulation platform using VisualSim software package to create simulation programs. We model an APS for hybrid electrical vehicle (HEV) with solar energy, thermoelectricity, fuel energy, and various buses. Simulation results suggest that controller area network (CAN) bus outperforms FlexRay and Bluetooth; this is because CAN bus optimizes the communication required by the vehicular system to use the renewable energy sources. The proposed modeling and simulation platform is easy, fast, and reliable to assess the components required in any autonomous power systems.
Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science