This validation case focuses on addressing grid-aware planning for green seaports. The first part validates the robustness of energy demand forecasting for cold ironing, a crucial aspect of green seaport operations. Experiments will focus on validating AI-driven grid-aware cold ironing planning algorithms to optimize shore-to-ship power supply operations. Using both real and open-source datasets, these algorithms will be tested for their effectiveness in reducing emissions and improving energy efficiency in port electrification. The testing will assess various factors, including predictive load balancing, renewable energy integration, and grid stability under different operational scenarios. By leveraging AI-driven insights, these experiments will contribute to the development of smart, adaptive grid solutions that enhance the sustainability and efficiency of modern power systems. In addition, this validation case includes a specific focus on seaport electrification strategies, with Varna port in Bulgaria as a key case study. The planning involves:
Analysis and Scenarios: Conducting analyses and developing scenarios for seaport electrification, considering factors like energy demand, grid capacity, and environmental impact.
Cold Ironing Optimization: Implementing solutions to optimize cold ironing operations, which involve providing shore power to ships while they are docked, reducing emissions and improving air quality in the port area.
Grid Integration: Ensuring that the electrification plans are well-integrated with the existing grid infrastructure to maintain stability and reliability.
To validate AI-driven forecasting and optimization models for efficient cold ironing (shore-to-ship power supply) and electric vehicle (EV) charging while ensuring grid stability and sustainable port electrification
