Digital control algorithms : low power wind turbine energy maximizer for charging lead acid batteries
Fossil fuel consumption throughout the world is drawing attention to the need for alternative energy sources to provide for the large demand for energy. It is becoming more apparent everyday that fossil fuels are unreliable sources of energy due to the volatile pricing of such commodities as well as the toll that these energy sources take on the environment.
Fossil fuels are non-renewable sources of energy that when burned to create energy produce bi-products that are extremely harmful to the global environment. Today, renewable energy sources such as wind and solar energy are playing larger roles as sources of electricity and are providing new jobs as well as research opportunities both in academia and in industry. It is for this reason that wind turbine energy harvesting is the topic of this thesis and how the efficiency of wind turbine power conversion systems can be improved to become a more viable source of energy.
Large wind turbines, along with their power conversion electronics, exist today for the sole purpose of serving a large population of consumers with "green" electricity. Unfortunately, systems designed for low power wind turbines do not utilize advanced methods of maximizing energy draw from wind turbines both from hardware and software point of views. This theses is presents a method of efficient energy extraction and conversion from low power wind turbines to charge lead ac id batteries.
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Bachelor of Science (B.S.)
College of Engineering and Computer Science
Electrical Engineering and Computer Science
Dissertations, Academic -- Engineering and Computer Science;Engineering and Computer Science -- Dissertations, Academic
Length of Campus-only Access
Honors in the Major Thesis
Hamilton, Christopher, "Digital control algorithms : low power wind turbine energy maximizer for charging lead acid batteries" (2009). HIM 1990-2015. 877.