With data, a better way to manage solar and wind energy

The sun doesn't always shine and winds don't always blow. With analytics and big data, we can mitigate the risk of using them as energy sources.
Written by IBM Experts, Contributor on

Brad Gammons is general manager of IBM's Global Energy and Utilities Industry. Rolf Gibbels is an executive member of IBM’s global Energy & Utilities group.

One of the major challenges of relying on solar and wind as energy sources is their intermittency –- the sun doesn’t always shine and winds don’t always blow.

Since we can’t control the weather, we are coming up with innovative ways to work with it.

Our latest breakthrough is a cutting-edge power and weather modeling system called the Hybrid Renewable Energy Forecasting solution, or HyRef. This new technology is just another example of how big data can help transform industries, which in this case, enabling energy providers to forecast renewable power production in a new way.

The system works by using weather prediction and analytics to forecast the availability of wind and solar energy, so utility companies such as China’s State Grid Jibei Electricity Power Company Limited, can weave more renewable energy into the power grid. The roll-out is part of a SG-JBEPC-led, 670 megawatt demonstration project in the Zhangbei province in China, the largest renewable energy initiative to include solar and wind power, energy storage, and transmission.

Increasing the dependability of these renewable energy sources within the electrical grid is crucial to helping ramp up new solar and wind installations as well as combating climate change.

“Wind power is the largest and most readily-deployable form of new clean energy available, and utilities play a critical role in delivering this energy to retail electricity customers,” according to the American Wind Energy Association.

This new forecasting system gets the job done. SG-JBEPC estimates that it will increase the dispatch of renewable energy generation by 10 percent, or enough energy to power more than 14,000 homes, capturing energy that would otherwise have been lost. This will lower the need for conventional coal and natural gas plants, hence reducing emissions.

For China, this achievement is significant when you factor in the country’s commitment to transform its energy infrastructure: to build a nationwide smart grid. With this initiative in mind, the Chinese government issued a policy, stating that wind power forecasting becomes an essential part for all wind power dispatched into the electrical grid.

HyRef uses sensors placed on the wind turbines, which track wind speed, temperature, and direction. While advanced cloud imaging technology and cameras, coupled with weather modeling technologies, monitor cloud movements in near real time to improve power forecasts. This continuously changing data is fed to analytics systems to produce accurate local weather and power forecasts for each wind farm as far as a month in advance or short-term forecasts of zero to four hours per in 15-minute increments.

By using these local weather forecast, HyRef can estimate how much energy each of the wind turbines and solar arrays will generate , helping utilities such as SG-JBEPC accurately and dependably anticipate the amount of renewable energy power it can redirect into the power grid or store for when the sun hides behind clouds and the wind remains dormant.

Global climate change, skyrocketing population growth, and the continued march of economic develop demand that the industry become smarter. Energy and utility organizations around the world are making the necessary investments to transform energy infrastructures and integrate cleaner energy sources into the grid. With advanced analytics, wind power and other renewable sources are becoming dependable energy alternatives and with wind power estimated to generate 4.9 percent of the world’s electricity in 2017, the prospects seem bright.

Photo: George M. Groutas/Flickr

This post was originally published on Smartplanet.com

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