For the energy utilities companies managing inconsistently/intermittently available renewable energy sources such as solar and wind turbines is a challenge. Due to various weather conditions both solar and wind turbine outputs vary significantly. IBM has developed a forecasting system for energy utility companies to produce accurate weather forecasts within a wind farm as far as one month in advance, or in 15 minute increments.
The solution, named "Hybrid Renewable Energy Forecasting" (HyRef) uses weather modeling capabilities, advanced cloud imaging technology and sky-facing cameras to track cloud movements, while sensors on the turbines monitor wind speed, temperature and direction.
HyRef can predict the performance of individual wind turbine for the days ahead, so that utility companies can plan to increase or decrease generation capacities of conventional sources such as thermal and hydel power plants.
"Utilities around the world are employing a host of strategies to integrate new renewable energy resources into their operating systems in order to reach a baseline goal of a 25 percent renewable energy mix globally by 2025," said Vice Admiral Dennis McGinn, President and CEO of the American Council On Renewable Energy (ACORE). "The weather modeling and forecasting data generated from HyRef will significantly improve this process and in turn, put us one step closer to maximizing the full potential of renewable resources."
"Applying analytics and harnessing big data will allow utilities to tackle the intermittent nature of renewable energy and forecast power production from solar and wind, in a way that has never been done before," said Brad Gammons, General Manager IBM's Global Energy and Utilities Industry. "We have developed an intelligent system that combines weather and power forecasting to increase system availability and optimize power grid performance."