PNNL Awarded $6.8 Million for Marine, River Power Studies
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- Created on September 02, 2009
“Understanding how harnessing marine and hydrokinetic energy can affect the environment is key,” said Charlie Brandt, director of PNNL’s Marine Sciences Laboratory in Sequim, Wash. “This work will help remove the roadblocks that currently prevent developers from putting tidal-, wave- and current-powered machines in the water.”
Some of the issues researchers will examine include how fish and marine mammals are directly affected by water power devices – including induced electromagnetic fields, noise and blade strike – and whether producing these kinds of power could create “dead zones” by interfering with the ocean’s circulation and nutrient patterns.
Staff from PNNL’s offices in Seattle, Richland and Sequim, Wash., and Portland, Ore., will work together on the project. The study will also be done in collaboration with Oak Ridge National Laboratory, Sandia National Laboratories, the Northwest National Marine Renewable Energy Center (to which the University of Oregon and the University of Washington belong), the University of Massachusetts-Dartmouth and Pacific Energy Ventures, an Oregon renewable energy consulting firm.
DOE’s Office of Energy Efficiency & Renewable Energy also announced that PNNL would support four other advanced water power technology projects being led by other national laboratories. For two of the projects, PNNL will partner with the National Renewable Energy Laboratory and Sandia National Laboratories to use computational fluid dynamic models to develop and evaluate marine and hydrokinetic power devices. PNNL will also work with Argonne National Laboratory on advanced water flow forecasting to optimize the efficiency and environmental performance of hydroelectric power plants. And, finally, PNNL will team with Oak Ridge National Laboratory to increase fish passage safety and power production at existing dams, study how fish and wildlife are affected by the variable stream flows from dams, and measure and predict greenhouse gas emissions from dam reservoirs.
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