Researchers at the N. S. Solomenko Institute of Transport Problems of the Russian Academy of Sciences (RAS) have developed an algorithm capable of adapting to changing operating modes of maritime transport equipment while reducing the carbon footprint in coastal areas. The breakthrough was announced by the Russian Ministry of Science and Higher Education.

Energy consumption in ports often relies on non-steady-state power sources and is subject to seasonal factors, as well as sharp fluctuations driven by vessel berthing cycles and crane operations. According to the researchers, intelligent forecasting methods are key to improving the efficiency of port infrastructure management.

The research team developed a mathematical model to create computer software capable of managing energy flows in ports with a high degree of accuracy. The method's key advantage is that it does not rely on fixed parameters. Instead of using rigid templates, the system dynamically identifies the appropriate number of neighboring energy consumers and relevant temporal changes in real time, adapting to local data characteristics.

The new method is expected to support a wide range of factors affecting fluctuating electricity demand for shore-side power supply to vessels. It could help optimize the operation of diesel-generator and hybrid power systems, reduce operating costs and harmful emissions in coastal areas, improve the reliability of electricity supply for critical consumers, and facilitate the integration of renewable energy sources, including wind, tidal and solar power, without compromising the stability of port microgrids.

The method does not require high-performance computing systems, is highly energy-efficient, and has outperformed a number of modern forecasting models in terms of accuracy, the researchers said.