The Renewables.ninja software tool aims to ease predicting renewable energy output for academics and industry. The creators, from Imperial College London and ETH Zürich, have already used it to estimate Europe-wide solar and wind output, and companies such as German electrical supplier RWE are using it to test their own output models.
To test the model, Dr. Iain Staffell, from the Centre for Environmental Policy at Imperial, and Dr. Stefan Pfenninger, who is now at ETH Zürich, have used Renewables.ninja to estimate productivity of all wind farms planned or under construction in Europe throughout the next 20 years.
They found that wind farms in Europe currently have an average capacity factor of around 24%, which means they produce around a quarter of the energy that they could if the wind blew continuously – all day, every day. This number is a factor of how much wind is available to each turbine. Because new farms are being built using taller turbines placed further out to sea, where wind speeds are higher, the average capacity factor for Europe should rise to around 31%. This would allow 3x as much energy to be produced by wind power in Europe compared to today, not only because there are more farms, but because those farms can take advantage of better wind conditions.
In another research paper, they modelled hourly output of solar panels across Europe. Even though Britain is not the sunniest country, researchers found that on the best summer days, solar power produces more energy than nuclear power. However, the pattern of this solar output through the year substantially changes how the rest of the power system will have to operate. Wind and solar energies have a strong dependence on weather conditions, and these can be difficult to integrate into national power systems that require consistency. If excess power is generated by all energy sources, then some supplies have to be turned off.
Currently, wind and solar are the easiest to switch on and off, so they are often the first to go. Making use of larger capacity for solar energy generation relies on changes to the national energy system, such as adding new types of electricity storage or small, flexible generators to balance the variable output from solar panels.
Renewables.ninja uses 30 years of observed and modelled weather data from organizations such as NASA to predict wind speeds likely to influence turbines and sunlight levels likely to strike solar panels at any point on the Earth during the year. These figures combined with manufacturer’s specifications for wind turbines and solar panels generate a power-output estimate for a farm placed at any location.
“Modelling wind and solar power is difficult because they depend on complex weather systems,” Staffel says. “If every researcher has to create their own model when they start to investigate a question about renewable energy, a lot of time is wasted. So we built our models so they can be easily used by other researchers online, allowing them to answer their questions faster.”
He and Pfenninger have been beta testing Renewables.ninja for six months and now have users from 54 institutions throughout 22 countries, including the European Commission and the International Energy Agency.
Pfenninger says, “Renewables.ninja has already allowed us to answer important questions about the current and future renewable energy infrastructure across Europe and in the U.K., and we hope others will use it to further examine the opportunities and challenges for renewables in the future.” www.imperial.ac.uk