NEXT-E project to provide 252 chargers for electric vehicles until 2020
Region/EU November 15, 2017
By the end of 2020 Czech Republic, Slovakia, Croatia, Hungary, Slovenia, and Romania will get 222 fast (50 kW) and 30 ultra-fast (150-350 kW) chargers for electric vehicles as part of the NEXT-E project.
Chargers will be installed along main highways, with a maximum distance of 150 km which will for the first time enable long-distance travel, powered 100% on electricity, across six Central and Eastern Europe (CEE) countries.
During 2018 and 2019 59 will be built in Hungary, 58 in Croatia, 40 in Romania, 38 in the Czech Republic, 32 in Slovenia and 25 Slovakia.
In July 2017, the NEXT-E project was selected by the European Commission for co-financing through the Connecting Europe Facility (CEF). The NEXT-E project is implemented by electricity and oil companies MOL, E.ON, Power utility Hrvatska elektroprivreda (HEP), Petrol, and two automakers, Nissan and BMW.
A few days ago the NEXT-E consortium signed a grant agreement with European Commission’s Innovation and Networks Executive Agency (INEA) and received EUR 18.84 million to implement the project. This is the largest grant ever given by the EU’s Connecting Europe Facility for any EV project.
Herald Ruijters, Director of the Directorate B – Investment, Innovative & Sustainable Transport in the Directorate for Mobility and Transport of the European Commission, said that the objective of EU policy is to finally allow citizens to travel with alternatively fueled vehicles across the entire EU.
“The deployment of fast chargers is expected to start in 2018, while the installation of the ultra-chargers is planned for 2019 in order to prepare for the arrival of a new generation of long-distance EVs. The full deployment is expected to be concluded by the end of 2020”, MOL Group said in a statement.
The Connecting Europe Facility (CEF) is a key EU funding instrument developed specifically to direct investment into European transport, energy, and digital infrastructures to address identified missing links and bottlenecks.