A rolling multi-objective ship speed optimization strategy for energy efficiency and operating cost control in dynamic waterway conditions - Yupeng Yuan; Xiaodong Guo; Zhe Xiong; Daogui Tang; Liang Tong; Chi Zhang; Zhengmao Li; Joshua Y. Kim (Ocean Engineering, 2026)

A New Energy Management Strategy Supported by Reinforcement Learning: A Case Study of a Multi-Energy Cruise Ship - Xiaodong Guo; Daogui Tang; Yupeng Yuan; Chengqing Yuan; Boyang Shen; Josep M. Guerrero (Journal of Marine Science and Engineering, 2025)
Hybrid ships offer significant advantages in energy efficiency and environmental sustainability. However, their complex structures present challenges in developing effective energy management strategies to ensure optimal power distribution and stable, efficient operation of the power system. This study establishes a mathematical model of a hybrid system for a specific ship and proposes an energy management strategy based on the deep deterministic policy gradient (DDPG) algorithm, a reinforcement learning technique. The proposed strategy’s feasibility and effectiveness are validated through comparisons with alternative energy management strategies and real-world ship data. Simulation results demonstrate that the DDPG-based strategy optimizes the diesel engine’s operating conditions and reduces total fuel consumption by 3.6% compared to a strategy based on the deep Q-network (DQN) algorithm.

The Role of Integrated Multi-Energy Systems Toward Carbon-Neutral Ports: A Data-Driven Approach Using Empirical Data - Shaohua Yu; Zhaoliang Huang; Daogui Tang; Weiming Ma; Josep M. Guerrero (Journal of Marine Science and Engineering, 2025)
Ports are critical hubs in the global supply chain, yet they face mounting challenges in achieving carbon neutrality. Port Integrated Multi-Energy Systems (PIMESs) offer a comprehensive solution by integrating renewable energy sources such as wind, photovoltaic (PV), hydrogen, and energy storage with traditional energy systems. This study examines the implementation of a real-word PIMES, showcasing its effectiveness in reducing energy consumption and emissions. The findings indicate that in 2024, the PIMES enabled a reduction of 1885 tons of CO2 emissions, with wind energy contributing 84% and PV 16% to the total decreases. The energy storage system achieved a charge–discharge efficiency of 99.15%, while the hydrogen production system demonstrated an efficiency of 63.34%, producing 503.87 Nm3/h of hydrogen. Despite these successes, challenges remain in optimizing renewable energy integration, expanding storage capacity, and advancing hydrogen technologies. This paper highlights practical strategies to enhance PIMESs’ performances, offering valuable insights for policymakers and port authorities aiming to balance energy efficiency and sustainability and providing a blueprint for carbon-neutral port development worldwide.

Sustainable mega-seaports with integrated multi-energy systems: Life-cycle environmental and economic evaluation - Daogui Tang; Zhe Chen; Wuyou Zhao; Yupeng Yuan; Chengqing Yuan; Josep M. Guerrero; Enrico Zio (Journal of Cleaner Production, 2024)

Modeling and Optimization of the Air-Supported Membrane Coal Shed Structure in Ports - Mingwang Dong; Huimin Zhang; Daogui Tang; Xiaohai Guo; Yong Gu; Lei Qiao; Josep M. Guerrero (Journal of Marine Science and Engineering, 2024)
The air-supported membrane coal shed is widely used in bulk cargo terminals. It not only effectively protects goods from adverse weather conditions but also helps reduce coal dust and harmful gas emissions, promoting the green and sustainable development of ports. However, in practical engineering, the design parameters of the coal shed are often based on experience, making it difficult to accurately assess the quality of the structural design. The flexibility of the membrane material also makes the structure susceptible to deformation or tearing. This paper mainly focuses on modeling and solving the optimization design issues of air-supported membrane coal shed structures. According to the evaluation criteria for the form of air-supported membrane coal sheds, a multi-objective structural optimization model is established to minimize the maximum stress on the membrane surface, ensure uniform stress distribution, maximize structural stiffness, and minimize costs. The study utilizes a combined optimization approach using ANSYS 19.0 and MATLAB 2016a, incorporating an improved NSGA-II algorithm program developed in MATLAB into ANSYS for structural form analysis and load calculation. The research results indicate that the optimal solution reduces the maximum stress on the loaded membrane surface by 5.36%, shortens the maximum displacement by 30.3%, and saves on economic costs by 9.85%. Compared to traditional empirical design methods, the joint use of MATLAB and ANSYS for optimization design can provide more superior solutions, helping ports to achieve environmental protection and economic efficiency goals.

Optimal Planning for Wind Turbines in Mega Seaports Considering Practical Application Constraints: A Case Study of Ningbo-Zhoushan Port - Qianneng Zhang; Yipeng Jiang; Haidong Ren; Hao Tang; Daogui Tang; Chengqing Yuan; Josep M. Guerrero (Journal of Marine Science and Engineering, 2024)
In the context of global carbon neutrality, ports face significant electricity demand for cargo handling and pressure to reduce carbon emissions. The abundant wind energy resources in port areas make wind power highly promising for port applications. The optimal selection of site and turbine types for wind power systems can effectively reduce emissions in ports, achieving sustainability and improving economic benefits. The practical implementation of wind energy systems considering practical constraints holds significant research significance. Taking Ningbo-Zhoushan Port as an example, this paper analyzes the wind energy resources in the port area and provides an overview of wind power system construction sites. Based on the actual conditions of the port area, this paper comprehensively reviews the site selection of wind turbines from the perspectives of wind resources, specific climates, and noise impacts. With the consideration of engineering preferences, this paper selects performance indicators based on the four mainstream turbine models and proposes a comprehensive weight determination method using the entropy weight method and analytic hierarchy process (AHP) to determine the weights of the indicators. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is then employed to score and compare four turbine plans, enabling the turbine selection process to consider both engineering preferences and objectivity, thereby enhancing the accuracy and reliability of wind turbine planning and achieving significant ecological and economic benefits through benefit analysis.

Energy consumption and emissions analysis of large container seaports considering the impact of COVID-19: A case study of Ningbo Zhoushan Port - Daogui Tang; Zhe Chen; Chaoyuan Xu; Yupeng Yuan; Xiaohui Zhong; Chengqing Yuan (Ocean & Coastal Management, 2023)

Assessing the Potential for Energy Efficiency Improvement through Cold Ironing: A Monte Carlo Analysis with Real Port Data - Daogui Tang; Tao Jiang; Chaoyuan Xu; Zhe Chen; Yupeng Yuan; Wuyou Zhao; Josep M. Guerrero (Journal of Marine Science and Engineering, 2023)
Ports in China are facing significant pressure to reduce carbon emissions in alignment with carbon peak and carbon neutrality goals. Onshore power supply (OPS) is regarded as a promising approach to accomplish these targets, necessitating a thorough evaluation of its impact for port authorities to make informed decisions regarding its adoption. This research focuses on Ningbo Zhoushan Port, the largest port globally, as a case study. Two metrics are proposed to quantify the energy efficiency of ships powered by onshore energy while berthed. The installation and connection status of OPS in the port area are analyzed. Subsequently, the energy demand of berthed ships is assessed, and the potential for energy efficiency improvement resulting from OPS implementation is evaluated using Monte Carlo methods. The findings reveal untapped potential in the studied port area, with OPS demonstrating the ability to improve energy efficiency of berthed ships at a rate parallel to the connection rate, excluding indirect emissions. However, considering indirect emissions and energy loss diminishes the effectiveness of OPS. The paper discusses practical implications for enhancing the energy efficiency of OPS, enabling port authorities to make well-informed decisions. These findings are invaluable for Chinese port authorities striving to achieve carbon reduction goals and enhance sustainability in the maritime industry.

A Combined Wind Forecasting Model Based on SSA and WNN: Application on Real Case of Ningbo Zhoushan Port - Yong Gu; Wenhao Xu; Daogui Tang; Yuji Yuan; Ziyi Chai; Yao Ke; Josep M. Guerrero (Journal of Marine Science and Engineering, 2023)
Wind energy is an effective way to reduce emissions in ports. However, port wind power generation exhibits strong intermittency and randomness. Predicting port wind speed enables timely scheduling of port operations and improves wind energy utilization efficiency. To achieve high accuracy and rapid prediction of port wind speed, this paper proposes a wind speed prediction model based on the Sparrow Search Algorithm (SSA) optimized Wavelet Neural Network (WNN). Firstly, the SSA is used to optimize the Mean Squared Error (MSE) as the fitness function during the training process of the WNN model, obtaining the optimal fitness value corresponding to the network parameters. Then, the obtained parameters are used as the network model parameters of WNN for wind speed prediction. To validate the effectiveness of the proposed method, the model is validated using the measured wind speed data from the Chuanshan Port Area of Ningbo-Zhoushan Port throughout 2022, and its performance is compared with three other models: SSA–BP, SSA–LSTM, and WNN. The results demonstrate that the proposed prediction model exhibits good performance in port wind speed prediction and outperforms the other comparative models in terms of prediction accuracy and convergence speed.