An Advanced Atmospheric Ocean Assessment Program Designed to Reduce the “Risks” Associated with Offshore Wind Energy Applications

The Rutgers University Center for Ocean Observing Leadership (RU-COOL) is one of the world’s leaders in the study of physical and biological environmental conditions for the coastal ocean and it is the foremost expert in the study of the offshore waters along coastal NJ and the New York Bight (Schofield et al., 2008).RU-COOL has over a decade of experience applying advanced ocean observing technology (e.g. Schofield et al, 2007) along with atmospheric and ocean models to support a network of State, Local, and Federal government agencies (Glenn and Schofield, 2003).  Additionally, the Rutgers Department of Marine and Coastal Sciences (DMCS) has established several academic-government-industry partnerships to accomplish a wide array of innovative research and applied goals for public, scientific, and military applications (Glenn and Schofield, 2009).

RU-COOL is a member of the Rutgers Energy Institute (REI) which integrates Rutgers’ expertise in science, engineering, economics, and policy, putting it at the forefront of alternative energy research. (http://rei.rutgers.edu).  The technologies developed and employed by RU-COOL have been tried, tested, and accepted by the world’s foremost experts in the scientific community. Additionally, we have extensive experience running the state-of-the-art Weather Research and Forecasting (WRF) model, which has been optimized for research quality simulations (NSF Ocean Observing Initiative) and operational applications (NOAA Integrated Ocean Observing System) for the coastal ocean from Cape Cod to Cape Hatteras. This model has been well tested through a cooperative education operational forecasting project with PSEG that provided highly accurate and reliable information for severe storm management and power restoration activities.  The innovative Rutgers WRF (RU-WRF) model is also configured for offshore wind resource evaluations

The variability in the wind resource at atmospheric heights representative of offshore wind turbine dimensions in conjunction with varying energy demand must be taken into account to ensure economical and reliable electrical grid management.  Therefore, the “risks” and associated costs resulting from the variability of wind power production and uncertain demand requirements can be significantly reduced with a representative analytical/predictive program designed specifically for each offshore wind energy site, transmission/distribution hubs, and affected adjacent coastal/inland areas.

RU-COOL has developed an innovative monitoring/modeling program that is designed for realistic coastal/offshore wind resource assessments that are relevant to the offshore area that is adjacent to NJ’s coast.  The advanced and adaptive monitoring/modeling programs developed by RU-COOL have been extensively applied to determine the climatology and associated variability of both the mesoscale and microscale wind resource encompassed by NJ’s offshore area that is designated for wind energy development (Glenn and Dunk, 2013).  The final reports for Phase I II and III of the associated project, “An Advanced Atmospheric/Ocean Assessment Program Designed to Reduce the Risks Associated with Offshore Wind Energy Development Defined by the NJ Energy Master Plan and the NJ Offshore Wind Energy Economic Development Act”, can be reviewed using the links provided below.

The technologies developed by RU-COOL include high-resolution sea surface current monitoring along with representative surface wind field estimations determined by coastal radar (CODAR), which is used to detect sea breeze development and spatially evaluate model performance.

Also, RU-COOL has developed a unique product for determining realistic sea surface temperatures (SSTs) detected by infrared (IR) satellite remote sensing.  This product enables high-resolution SST detection during both clear and cloudy atmospheric conditions.  The spatial and temporal resolution of SSTs derived enables identification of coastal upwelling centers that affect the extent of sea breeze propagation and vertical development.

Furthermore, it has been demonstrated that SST is one of the most significant model inputs for determining the dynamics of the offshore wind resource.  Therefore, advanced and adaptive monitoring/modeling programs developed by RU-COOL should prove to be the most accurate and representative techniques for analyzing and predicting the wind characteristics along with other atmospheric/oceanic parameters that are specific for NJ’s coastal and adjacent offshore areas.

altsst

alt

cycle

alt

Virtual Met Station Data Directory


Resources:

Final Report Phase One (For Ideal Viewing of PDFs right click and select “save as”)

Final Report Phase Two (For Ideal Viewing of PDFs right click and select “save as”)

Final Report Phase Three

HF Radar Diagnostics

HF Radar Totals


80 m 90 m 100 m 110 m 120 m
ANNUAL annual-80 annual-90 annual-100 annual-110 annual-120
ANNUAL
DETAILED
annual-d-80 annual-d-90 annual-d-100 annual-d-110 annual-d-120
SPRING spring-80 spring-90 spring-100 spring-110 spring-120
SPRING
DETAILED
spring-d-80 spring-d-90 spring-d-100 spring-d-110 spring-d-120
SUMMER summer-80 summer-90 summer-100 summer-110 summer-120
SUMMER
DETAILED
summer-d-80 summer-d-90 summer-d-100 summer-d-110 summer-d-120
FALL fall-80 fall-90 fall-100 fall-110 fall-120
FALL
DETAILED
fall-d-80 fall-d-90 fall-d-100 fall-d-110 fall-d-120
WINTER winter-80 winter-90 winter-100 winter-110 winter-120
WINTER
DETAILED
winter-d-80 winter-d-90 winter-d-100 winter-d-110 winter-d-120

Next Page > > Monthly Wind Resource Maps

Last Page > > Wind Resource Maps Extended Field


Related Publications


Related Presentations:


Funding provided by BPU. This study benefits from and contributes to the IOOS through MARACOOS.