The key to driving the green energy transition is through using smart data to map electrical flows on the grid.
That’s according to scientists from the Centre for Solar Energy and Hydrogen Research (ZSW) in Germany, who are looking to use ‘intelligent algorithms’ to more accurately forecast supply from renewables and demand from consumers.
Renewables feature prominently in Germany’s power grid, so a comprehensive view of energy flows is needed to ensure the grid remains balanced.
This is more easily done with traditional central feeds from power plants, where power supply can be simply adjusted to match consumption.
However, striking the right balance is far more difficult with increasingly decentralised feeds from intermittent solar and wind sources.
C/sells, a new four-year project from ZSW, aims to optimise the flexibility of power grids with very high solar penetration in 46 sample regions and neighborhoods.
The project’s overall budget runs to around €100 million (£87.3m) and involves 42 partners, including the Federal Ministry for Economic Affairs and Energy.
Dr. Jann Binder, Head of the Photovoltaics Department at ZSW, said: “These new methods analyse vast amounts of complex information.
“They sift through this mountain of data to independently filter out crucial properties for forecasting. These are key factors that influence green power plants’ expected electricity yields and consumers’ demand for electricity.”
The European Commission has approved plans to put in place a reserve for four years to ensure sufficient electricity capacity in Southern Germany.