Better wind turbine forecasting; wind speed and wind turbine power output at single turbine spatial scale

Wind turbine generator power output and consumer electricity demand vary independently from one another. This presents a difficult situation for electricity grid managers as they attempt to exactly match demand using wind turbines and conventional generators (e.g. hydro, fossil fuels). Accurate forecasting of wind turbine generator power enhances management of the electricity grid, allowing for more wind turbine generating capacity while maintaining grid stability. This research will perform a sensitivity analysis on, calibrate and validate the newest high resolution wind power forecasting model for Atlantic Canada. Resolution of space and time have increased from 12 km and 60 minutes, representing an entire wind farm with one forecast point, to 0.1 km and 5 minutes, representing a single wind turbine in a specific topographic and surface roughness environment. Sensitivity analysis will compare the incremental gains in forecast accuracy due to increasing resolution. Calibration will be completed by forecasting a variety of wind turbine types and farms and comparing with actual performance data. Validation will insure accurate forecasting for a variety of conditions, topographies, and wind farm layout.

Faculty Supervisor:

Lukas Swan

Student:

Partner:

Scotia Weather Services Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Dalhousie University

Program: