In the context of harsh emission control and ecological environment protection, the shipping industry is transforming and upgrading towards greening, decarburization, and electrification. Battery-powered all-electric inland ships have been attracting increasingly attention. However, its initial investment cost is much more expensive than a traditional diesel-driven mechanical ship because lithium-ion batteries are currently expensive. Hence, a suitable battery size and efficient energy management strategy for ship sailing are very important for a battery-powered ship. In this paper, a novel joint optimization method of the sailing speed and battery capacity, which considers the interaction between battery size and sailing speed as well as multiple operation factors, such as freight demand and battery life, and port electricity price, is proposed to fully exploit the battery-powered ships’ application potential. Moreover, a joint optimization model of the sailing speed and battery energy consumption model considers the battery-powered ship’s characteristics and waterway characteristics. Next, a solution algorithm for the proposed joint optimization model is established to achieve joint decision-making regarding the sailing speed and battery size. Finally, case studies are conducted to demonstrate the flexibility and effectiveness of the proposed method. The results show that the proposed method can obtain the optimal sailing speed and the corresponding battery capacity synchronously when the actual transportation scenario is fixed. Moreover, the battery initial investment cost can be effectively reduced with the prosed method.

In order to achieve carbon peak and neutrality goals, many low-carbon operations are implemented in ports. Integrated energy systems that consist of port electricity and cooling loads, wind and PV energy devices, energy storage, and clean fuels are considered as a future technology. In addition, ports are important hubs for the global economy and trade; logistics optimization is also part of their objective, and most port facilities have complex logistics. This article proposes an energy–logistics collaborative optimization method to fully tap the potential of port-integrated energy systems. A logistics–energy system model is established by deeply examining the operational characteristics of logistics systems and their corresponding energy consumption patterns, considering ships’ operational statuses, quay crane distribution constraints, and power balances. To better represent the ship–energy–logistics optimization problem, a hybrid system modeling technique is employed. The case of Shanghai Port is studied; the results show that costs can be reduced by 3.27% compared to the traditional optimization method, and a sensitivity analysis demonstrates the robustness of the proposed method.

Variational Mode Decomposition (VMD) decomposes the signal into a series of Intrinsic Mode Type Functions (IMTFs) according with variational model and fluctuating characteristics of the signal itself, thus very suitable for the analysis of nonlinear and non-stationary Electrocardiogram (ECG) signal. Energy of ECG signal has certain distribution rules, but which could be affected by diseases; therefore, the study of ECG energy distribution change is of great importance to the research and clinical diagnosis of heart diseases. In this paper, firstly, ECG signals are decomposed into a series IMTFs with VMD and the fluctuating characteristics and physical meanings of ECG signals on different time scale are analyzed by observing the fluctuation rule of IMTFs. Then, the energy vectors of ECG signals are obtained by calculating the energy of each IMTF and a comparative analysis of energy vectors is conducted between healthy people and three kinds of heart disease patients. It can be seen according to the experimental results that heart disease could cause high-frequency components of the VMD energy vector to drop significantly and the VMD energy vector can well reflect the impacts of age and disease on ECG energy distribution, which can be used as a reference for heart disease diagnosis.