Today’s energy supply is not up to the challenges of renewable, decentralized electricity production and the electrification of mobility and heat. In a renewable energy supply, there is too much electricity when the sun is shining and too little when it is not. In addition, more and more electric cars and heat pumps will increase the demand for electricity and lead to more extreme load peaks. The electricity grid must become more flexible to react quickly to these fluctuations. Electric cars are an essential flexibility to achieve this goal. Today, many utilities have limited knowledge about the amount and timing of charging in their grid. Within this challenge, we would like to address this issue using data analytics. We will develop an algorithm to determine whether an e-car is present at this measuring point. The charging power should be disaggregated from the household consumption. Within the framework of a project, we have made initial evaluations and found that massively more e-cars were detected than were known to the distribution network operator.

Future questions are: Is it possible to detect charging using the load curves measured at transformation stations? How much better is the disaggregation if we use high-resolution data instead of 15-minute values?

Challenge Owner: aliunid AG und EKZ