Renewable Energy Forecast Error Correction (No. 0072)

Summary

Algorithm to predict error in renewable energy forecasts.

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. Here we present a promising algorithm developed by a group of researchers led by Prof. Mahesh Bandi. The algorithm enables operators to manage varying levels of power generation and operate equipment efficiently and traders to make marketing decisions.

Applications

• Wind Power
• Solar Power
• Ocean Power

Advantages

• Minimal data is required to perform forecast error analysis; time series for actual power generated and forecast power
• Applicable to any data sampling rate