Design, construction, and testing of a research quality electric machine testbed

With energy demands and costs growing every day, the need for improving energy efficiency in electrical devices has become very important. Research into various methods of improving efficiency for all electrical components will be a key to meet future energy needs. This report documents the design, construction, and testing of a research quality electric machine dynamometer and test bed. This test cell system can be used for research in several areas including: electric drives systems, electric vehicle propulsion systems, power electronic converters, load/source element in an AC Microgrid, as well as many others. The test cell design criteria, and decisions, will be discussed in reference to user functionality and flexibility. The individual power components will be discussed in detail to how they relate to the project, highlighting any feature used in operation of the test cell. A project timeline will be discussed, clearly stating the work done by the different individuals involved in the project. In addition, the system will be parameterized and benchmark data will be used to provide the functional operation of the system. With energy demands and costs growing every day, the need for improving energy efficiency in electrical devices has become very important. Research into various methods of improving efficiency for all electrical components will be a key to meet future energy needs. This report documents the design, construction, and testing of a research quality electric machine dynamometer and test bed. This test cell system can be used for research in several areas including: electric drives systems, electric vehicle propulsion systems, power electronic converters, load/source element in an AC Microgrid, as well as many others. The test cell design criteria, and decisions, will be discussed in reference to user functionality and flexibility. The individual power components will be discussed in detail to how they relate to the project, highlighting any feature used in operation of the test cell. A project timeline will be discussed, clearly stating the work done by the different individuals involved in the project. In addition, the system will be parameterized and benchmark data will be used to provide the functional operation of the system.

Minimizing residential distribution system operating costs through intelligently scheduled plug-in hybrid electric vehicle charging

Rising fuel prices and environmental concerns are threatening the stability of current electrical grid systems. These factors are pushing the automobile industry towards more effcient, hybrid vehicles. Current trends show petroleum is being edged out in favor of electricity as the main vehicular motive force. The proposed methods create an optimized charging control schedule for all participating Plug-in Hybrid Electric Vehicles in a distribution grid. The optimization will minimize daily operating costs, reduce system losses, and improve power quality. This requires participation from Vehicle-to-Grid capable vehicles, load forecasting, and Locational Marginal Pricing market predictions. Vehicles equipped with bidirectional chargers further improve the optimization results by lowering peak demand and improving power quality.

AGENT BASED, DISTRIBUTED CONTROL STRATEGIES AND OPTIMIZATION OF PLUG-IN ELECTRIC VEHICLES ON SMART/MICROGRID ARCHITECTURES

This thesis will present strategies for the use of plug-in electric vehicles on smart and microgrids. MATLAB is used as the design tool for all models and simulations. First, a scenario will be explored using the dispatchable loads of electric vehicles to stabilize a microgrid with a high penetration of renewable power generation. Grid components for a microgrid with 50% photovoltaic solar production will be sized through an optimization routine to maintain storage system, load, and vehicle states over a 24-hour period. The findings of this portion are that the dispatchable loads can be used to guard against unpredictable losses in renewable generation output. Second, the use of distributed control strategies for the charging of electric vehicles utilizing an agent-based approach on a smart grid will be studied. The vehicles are regarded as additional loads to a primary forecasted load and use information transfer with the grid to make their charging decisions. Three lightweight control strategies and their effects on the power grid will be presented. The findings are that the charging behavior and peak loads on the grid can be reduced through the use of distributed control strategies.