Modeling the electrical grid impact of wind ramp-up forecasting error offshore in the Mid-Atlantic region

The large wind resource and population centers along the Mid-Atlantic Coast of the United States make it an attractive region to develop offshore wind power. Understanding and accurately predicting the meteorology offshore is fundamental to efficient integration of these future wind farms into an electrical grid. Particular interest is focused on anticipating and reducing errors associated with wind ramps, which are characterized by rapid, sustained changes in wind speed over a period of hours. Using meteorological observations from a coastal buoy, we characterize 428 wind ramp-ups between 2005 and 2012 in terms of frequency, duration and magnitude, time and date of occurrence, and large-scale synoptics. From this group, we select 24 case studies that represent typical and extreme ramp-ups at this location and then model the impact that the forecasting error of these ramp-ups could have on the electrical grid. The case studies are modeled with the Weather Research and Forecasting (WRF) model and compared with nearby buoy observations to assess forecast errors in ramp-up timing, shape, and magnitude. WRF frequently simulated ramp-ups too early, relative to observations, and often predicted the pre-ramp-up wind speed to be too high or the post-ramp-up wind speed to be too low. In the case of August 14, 2007, all three forecast errors occurred. The simulated impact on the grid is calculated by comparing the errors in forecast power with concurrent electrical load data in PJM's Mid-Atlantic Area Council-East (PJM-E) region. The largest impacts on the electrical grid were found to occur in the winter or at night in the summer. This framework allows for the identification of events that would potentially cause problems for the electrical grid in the PJM-E region.