In renewable energy, utility operators use forecast models to predict energy fluctuations over a future time horizon to account for operating reserves, and protect grid infrastructure from instabilities. These models are of limited accuracy and as a result operating reserves may be inadequate or over-provided, and grid instabilities may be caused by under or over production of power. Forecasting enables operators to manage varying levels of power generation and operate equipment efficiently and traders to make marketing decisions. However, it has been reported by an operator that over the 5 year period 2008-2013 wind power failed to meet forecast 58% of the time.
This technology makes it possible to quantify two errors, used to qualify and improve forecast models, protecting against losses in revenue and grid instabilities caused by energy fluctuations.
Minimal data is required to perform forecast error analysis; time series for actual power generated and forecast power.
Applicable to any data sampling rate.
This technology validates forecast models and does not generate forecast models