In the world of clean technology, we often see new renewable energy ideas that could provide large amounts of power, but we also see lots of ideas for generating smaller amounts of energy for say charging devices or powering lighting. This latest idea from a Wake Forest University sophomore, is one of the latter. Yinger ‘Eagle’ Jin has been testing a wave energy harnessing technology he built in the school’s pool to see how much energy swimmers could generate during the day.
The university says, “Jin constructed an oscillating water column, one of the most productive wave energy converters available, to test the amount of electricity that could feasibly be produced by the pool’s waves. It uses a large volume of moving water (in the case of Wake Forest’s Reynolds Gym pool, the waves generated by daily swimmers) as a piston in a cylinder. Air is forced out of the column as a wave rises and fresh air is drawn in as the wave falls. This movement of air turns a turbine at the top of the column, which ultimately converts the wave energy to electricity.”
“We are talking a very small scale, but recreational swimmers produce a decent amount of waves,” Jin said. “The concept is similar to the idea that at a regular gym you have exercise bikes that are powered by someone spinning the pedals.”
Jin found that an average of 10 people swim per hour for the 10 hours a day that the pool is open. He calculated that if each person swims butterfly stroke, the swimmers would generate enough waves to produce 10 kilowatt-hours of electricity a day, or enough to power 10 100-watt bulbs for a day.
Jin’s project has a greater purpose beyond just generating electricity from swimmers’ waves. The mathematical model Jin and his mathematics professor Sarah Mason developed to measure the energy output from the waves can also be applied in bigger water sources than the pool.
“There is certainly room for continuation in Eagle’s project; in particular one publishable goal is to calculate how much energy could be produced through wave energy off the coast of North Carolina,” Mason said. “We have computed rough estimates but would need to factor in more details and be more precise if we wanted to get an accurate prediction.”
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