How coastal upwelling can affect the offshore component of the sea breeze: WRF simulations for offshore wind energy

Just recently—on July 21, 2014—the Bureau of Ocean Energy Management (BOEM) announced the proposed sale of leases for nearly 344,000 acres offshore New Jersey for commercial wind energy leasing. In their study for BOEM, the National Renewable Energy Laboratory determined maximum potential capacity across the two lease zones of 3,400 megawatts, which is enough to power 1.2 million homes if the New Jersey Wind Energy Area (NJWEA) is fully developed. Yet due to the variable nature of wind, not all of these homes will be powered 100% of the time solely from offshore wind.

Thus, accurate resource assessments and representative forecasts that characterize the spatial and temporal wind variability are critical in reducing the elevated risks and costs associated with offshore wind development and operations. Compared to onshore, the offshore wind resource is much less observed due to costly offshore observational platforms. For example, an offshore met tower can cost upwards of $10 million, and, further, cannot provide any characterization of the horizontal spatial wind variability.

Using realistic real-time and research-mode Weather Research and Forecasting (WRF) microscale (~400 m resolution) simulations of several case studies, we investigate the offshore component of the sea breeze circulation, a prominent source of wind variability in the NJWEA that often occurs during peak energy demand periods (hot summer afternoons). With an innovative coldest-pixel satellite SST composite product, we compare cases with and without coastal upwelling. While studies have shown that coastal upwelling can affect onshore sea breeze frontal speed and structure, few studies, if any, have examined coastal upwelling's effect on sea breeze's offshore component. The offshore vertical structure (including turbulence and shear profiles across wind turbine blade dimensions) of the main sea breeze circulation and potential secondary circulations due to the cold upwelled waters are investigated. The coincidence between the variability in wind power production (supply) and variations in energy prices (demand) is determined for the cases studied herein.

The real-time WRF model used in this study has been validated according to criteria accepted by the wind energy industry. Model results here are further evaluated against surface ocean currents from High Frequency radar, winds from newly-installed coastal SODAR and met tower systems at Tuckerton, NJ, winds from scanning and vertical LIDARs, and observations from other available coastal and offshore meteorological monitoring systems.

Future work will involve coupled ocean-atmosphere-wave modeling with potential data assimilation for improved initialization, which will be important in an operational forecasting environment for offshore wind farm construction and operations & maintenance activities.