Shore power (SP) is a critical solution for decarbonizing maritime transport, yet its adoption is hindered by the “high investment, low utilization” paradox, driven by high initial costs and misaligned incentives between ports and ships. While government subsidies are essential, traditional static policy designs often fail to adapt to the complex, non-linear dynamics of technology diffusion. To address this, the study proposes a dynamic evaluation framework combining System Dynamics (SD) with Evolutionary Game Theory (EGT), embedding a Rolling Horizon Optimization algorithm. Using Shanghai Port as a case study, simulation results demonstrate that optimal subsidies are highly state-dependent. Specifically, effective promotion requires prioritizing ship-side incentives during the early start-up phase, followed by facilities subsidies supporting the coordinated evolution of both ships and berths, and finally a market-driven exit. Furthermore, the proposed dynamic strategy demonstrates superior robustness against oil price volatility and demand shocks compared to static policies, while strictly complying with fiscal budget caps. This framework provides a foundation for the adaptive management of green port infrastructure, facilitating the advancement of energy-saving and environmental protection initiatives within the maritime industry. Additionally, it contributes to the forecasting and evaluation of the policy outcomes of green technology adoption.
Lin et al. (Tue,) studied this question.