Simulating subhourly variability of wind power output

As installed wind power capacity grows, subhourly variability in wind power output becomes increasingly important for determining the system flexibility needs, operating reserve requirements, and cost associated with wind integration. This paper presents a new methodology for simulating subhourly wind power output based on hourly average time series, which are often produced for system planning analyses, for both existing wind plants and expanded, hypothetical portfolios of wind plants. The subhourly model has an AR(p)‐ARCH(q) structure with exogenous input in the heteroskedasticity term. Model coefficients may be fit directly to high‐pass filtered historical data if it exists; for sets of wind plants containing hypothetical plants for which there are no historical data, this paper presents a method to determine model coefficients based on wind plant capacities, capacity factors, and pairwise distances. Unlike predecessors, the model presented in this paper is independent of wind speed data, captures explicitly the high variability associated with intermediate levels of power output, and captures distance‐dependent correlation between the power output of wind plants across subhourly frequencies. The model is parameterized with 1‐minute 2014 plant‐level wind power data from Electric Reliability Council of Texas (ERCOT) and validated out‐of‐sample against analogous 2015 data. The expanded‐capacity model, fit to 2014 data, produces accurate subhourly time series for the 2015 wind fleet (a 49% capacity expansion) based only on the 2015 system's wind plant capacities, capacity factors, and pairwise distances. This supports its use in simulating subhourly fleet aggregate wind power variability for future high‐wind scenarios.