Abstract
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.