Abstract
Ports, as key nodes for marine renewable energy consumption and integration with marine
industries, are facing the dual pressures of low-carbon transformation and efficient energy utilization. To
solve fossil fuel reliance and high carbon emissions from disconnected port berth scheduling and energy
optimization, this study proposes a two-stage framework combining the improved Cuckoo Search
Algorithm (ICSA) and Stackelberg game. In the first stage, a vessel-centric optimization framework is
proposed, which integrates the time-of-use electricity pricing mechanism to coordinate ship operating
decisions and port low-carbon objectives. The ICSA is employed to solve the low-carbon berth allocation
problem, while synchronously generating the time-series load data of key port handling equipment. In the
second stage, a demand response load matrix is established by fully exploiting the battery swapping
characteristics of electric trucks and the cold load shifting capability of refrigerated containers. A tripartite
Stackelberg game is then conducted among the port energy operator, distributed energy supplier, and port equipment aggregator to optimize energy pricing and multi-energy supply dynamically. Case studies show doubled shore power using vessels, 14% higher berth utilization, and 29.86% lower energy costs. Carbon emissions were significantly reduced, while the proportions of offshore natural gas and renewable energy saw notable increases. This study provides a new approach for the integration of marine energy into port operations, supporting the sustainable development of marine energy industries and the low-carbon transformation of coastal ports.