Title

Digital control algorithms : low power wind turbine energy maximizer for charging lead acid batteries

Abstract

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.

Notes

This item is only available in print in the UCF Libraries. If this is your thesis or dissertation, you can help us make it available online for use by researchers around the world by downloading and filling out the Internet Distribution Consent Agreement. You may also contact the project coordinator Kerri Bottorff for more information.

Thesis Completion

2009

Semester

Summer

Advisor

Batarseh, Issa

Degree

Bachelor of Science (B.S.)

College

College of Engineering and Computer Science

Degree Program

Electrical Engineering and Computer Science

Subjects

Dissertations, Academic -- Engineering and Computer Science;Engineering and Computer Science -- Dissertations, Academic

Format

Print

Identifier

DP0022304

Language

English

Access Status

Open Access

Length of Campus-only Access

None

Document Type

Honors in the Major Thesis

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