Project Details
 |
North Carolina Renewable Ocean Energy Program: Comprehensive Gulf Stream Ocean Energy Resource Assessment Using an Integrated Observing and Modeling Approach |
Sponsor: University of North Carolina Coastal Studies Institute
Collaborators:
University of North Carolina, Chapel Hill: John Bane, Sara Haines
University of North Carolina Coastal Studies Institute: Mike Muglia
Funding period: July 2015 - June 2016
Description
Building on previous years' research into developing a combined modeling -observational prediction system to guide the optimal development of ocean energy extraction
from the Gulf Stream off the coast of North Carolina (NC), this project will further develop the Integrated Observing- Modeling Prediction and Assessment System to support ocean hydrokinetic energy assessment. We will produce the best available quantitative descriptions of numerous aspects of the ocean environment that relate to power generation in the Gulf Stream along the
NC continental slope and outer continental shelf. In addition to calculating the power levels in
the Stream, we will continue gathering information that will be helpful in engineering design,
environmental assessment, and developing an improved understanding of the character and
causes of the current variability in this region. This last topic will be especially valuable in
model predictions that are necessary for emplacement and operations of submarine power
generating machinery. As in the past, we will continue to interface with the other groups in the
Program, who are considering the environmental, geological, economic and other aspects of the
Ocean Energy program.
The modeling system that we have used for ocean current and power estimation will be further
improved upon, and we will continue making important and useful current measurements from
mooring, ship transect surveys and HF Radar surface current measurements for model validation
and for power generation estimations. The radar in particular will provide an essential tool to
observe Gulf Stream high frequency variability, and infer spatial and temporal changes in Gulf
Stream transport (Figure 4).
Results
Work is in progress.