Antwerp Euroterminal (AET) and Envision Digital have partnered to provide critical support for AET’s plans to transition to use 100 per cent renewable energy sources, comprising a mix of wind and solar energy.
AET is the largest multipurpose terminal in the Port of Antwerp, and Envision Digital is the global decarbonisation software leader headquartered in Singapore.
Ranked 13th in the top 20 container ports worldwide, and the second largest port in Europe, the port of Antwerp-Bruges’ CO2 emissions amount to 17 million tonnes each year.
Accounting for 10 per cent of Belgium’s total carbon emissions, the port plans to become the world’s most sustainable port and achieve carbon neutrality by 2050 by exploring the use of green energy.
Under the partnership, AET will leverage Envision Digital’s proprietary Artificial Intelligence of Things (AloT) operating system, EnOS, to improve its energy storage management.
This will enable AET to reduce up to 25 per cent of peak power demand and achieve cost savings of up to eight per cent on total electricity costs through the effective management of both imported and renewable energy prices.
The EnOS system will also reportedly enhance the capabilities of its electricity grid to withstand and recover from natural disasters and extreme weather events rapidly.
This will further support the optimisation of AET’s energy generation, consumption, and storage in real-time, ensuring the efficient integration of renewable resources.
“This project marks an essential progression towards decentralisation, digitalisation, and optimisation of our infrastructure,” stated Yves de Larivière, Managing Director at Antwerp Euroterminal NV.
“By incorporating microgrids and smart grids into our operations, we are making energy consumption smarter and more adaptive to supply conditions, enabling us to become more efficient and sustainable.”
Maher Chebbo, Europe Managing Director at Envision Digital, said: “We are thrilled to support AET’s decarbonisation journey with the deployment of our AloT operating system across their renewable energy systems and infrastructure.
“Furthermore, the implementation of predictive analytics and machine learning algorithms will also help AET generate valuable insights around their carbon footprint.”