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In view of the fact that the current integrated port energy system (IPES) considers neither the time scale difference of refrigerated containers in port scheduling nor the impact of renewable energy and load uncertainty, this paper proposes a day-ahead and intra-day two-stage rolling optimization scheduling method for a container IPES. In day-ahead scheduling, based on the temperature rise process of refrigerated containers, a port cold chain energy demand model is established, which is combined with the logistics process after the arrival of refrigerated containers. Then, the day-ahead output values of each unit in the system are obtained with the goal of the lowest operating cost. In intra-day scheduling, a two-layer rolling model is proposed to obtain the adjusted output of the port energy equipment, which considers the prediction error of shore power load and renewable energy as well as the different response speeds of cooling, heating and power. The calculation results show that the collaborative optimization scheduling of refrigerated containers and the container IPES can effectively reduce the port operation cost and carbon emissions. The two-stage day-ahead and intra-day rolling optimization scheduling can improve the economy and stability of the system.

Aimed at the problem of the inertia power allocation due to different indexes when multiple optical storage units are running together, a cooperative control strategy of multiple optical storage units is proposed by using adaptive virtual inertia control as a means to improve power quality. According to the charging and discharging characteristics of the battery, the inertia provided by the system is adjusted. As high-frequency disturbance occurs in the system, the super capacitor is the first choice to provide inertia support. As low-frequency disturbance occurs in the system, the battery provides inertia power support, and the distance algorithm of the superior and inferior solutions is introduced. As cooperative control is performed, indicators such as the allowable power fluctuation range of the converter and the allowable power fluctuation range of the energy storage device are selected as the evaluation reference, the coordination among multi virtual synchronous generator (VSG) units in multi-index comprehensive evaluation is realized. Finally, an AC system with multi VSG units is built on the experiment platform, and the effectiveness of the proposed control strategy is verified.