The optimal dispatching of integrated energy systems can effectively reduce energy costs and decrease carbon emissions. The accuracy of the load forecasting method directly determines the dispatching outcomes, yet considering the stochastic and non-periodic characteristics of port electricity load, traditional load forecasting methods may not be suitable due to the weak historical regularity of the load data themselves. Therefore, this paper proposes a method for forecasting the electricity load of container ports based on ship arrival and departure schedules as well as port handling tasks. By finely modeling the electricity consumption behavior of port machinery, effective prediction of the main electricity load of ports is achieved. On this basis, the overall structure of an integrated port energy system (IPES) including renewable energy systems, electricity/thermal/cooling/hydrogen energy storage systems, integrated energy dispatching equipment, and integrated loads is studied. Furthermore, a dispatching model considering demand response for the optimal operation of the IPES is established, and the day-ahead optimal dispatching of the IPES is achieved based on the forecasted load. The experimental results indicate that the developed method can ensure the operational efficiency of IPES, reduce port energy costs, and decrease carbon emissions.

This paper describes the development of unmanned surface vessel (USV) collision avoidance technology, introduces the basic principles and key technologies of image recognition technology, analyzes the shortcomings of traditional collision avoidance technology, and explains the research status of the image recognition technology in the collision avoidance of unmanned surface vessel. The design ideas of the existing research and development results are summarized. Advantages and disadvantages are analyzed and compared. This paper focuses on the techniques of stereo vision, deep learning, multi-sensor fusion, and the method of unmanned surface vessel collision avoidance based on image recognition technology. The future development trend of this field is also discussed.

Adaptive education is the basic content of ideological and political education in universities. It not only affects students' growth and development, but also affects universities to complete the fundamental task of enhancing morality and fostering talents. Taking a university of technology in Wuhan as an example, this paper investigates the adaptability of freshmen through questionnaire survey, and analyzes the problems of adaptive education in universities through literature retrieval. On this basis, an adaptive education mode for freshmen based on the concept of refinement is explored.