New Jersey is targeted to become a leader in offshore wind energy in the country with the recent contract of 1.2 GW in phase 1 and an ambitious plan to increase the offshore wind energy capacity to 3500 MW by 2030 (Board of Public Utilities, 2018). The booming wind energy sector needs expertise and knowledge to support the design of wind farms, the assessment of project safety and environmental impacts, and the development of efficient system control for the local atmospheric and ocean conditions. This project is designed to integrate the oceanographic modeling and wind energy simulation to develop a comprehensive modeling platform to connect the physics of wind turbines and the local coastal process modeling tools.
Atmospheric processes off the coast of New Jersey and throughout the Mid Atlantic are highly dynamic and tightly coupled to the evolution of the coastal ocean. Large horizontal temperature gradients and rapidly evolving coastal ocean upwelling centers can alter seabreezes, low-level jets, tropical cyclone intensity, and other wind features. In order to fully understand the regions wind resource and predict future wind power production on time-scales of hours to days coupled air-sea and wind turbine modeling systems need to be developed. Additionally, the influence of wind farms on the region ocean circulation, mixing, and ecosystems are not currently well understood. Critical stakeholder issues persist including alteration of sediment transport balances and shoreline erosion, impacts on the recreational and commercial fishing communities including ocean accessibility and safety in their fishing activities with the presence of new wind farms. These issues should be adequately examined to address the concerns of the stakeholders and decision makers. This presentation will show our progress in building a synergic wind energy-coastal process platform, which couples OpenFAST and a newly coupled oceanic and atmospheric numerical modeling system WRF-ROMS. We will present the preliminary results in calibration and validation of the simulation.