Wind Power Forecasting: Using JMP® Time Series Analysis for Hourly Prediction of Power Generation
Srinivas Reddy Busi Reddy, Srikar Rayabaram, Oklahoma State University
Forecasting wind power generation is crucial for the power system management or energy trading. Wind power forecasts also serve as key inputs for deciding on the use of conventional power plants and for the optimization of scheduling of these plants. Bids for energy to be supplied on a given day are usually required during the morning of the previous day. This poster focuses on the use of JMP Time Series Analysis model to predict hourly power generation, based on past power observations and available meteorological wind forecasts for that period. It first explains the various steps involved in preparing and identifying patterns in time series data, the various models build using JMP time series analysis, evaluating the models and finally discuss the results.
