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Since multi-energy microgrid (MEMG) can coordinate various resources to operate as a virtual power plant (VPP), it is an important way to maintain the stable and economic operation of the power systems and decrease the impact of intermittence of distributed energy resources (DERs). However, the potential of MEMG as a VPP has not been thoroughly explored since auxiliary service (AS) market is not fully open for MEMG at present. The relevant challenges include balancing conflict of interests among multiple energy entities, motivating users to adjust flexible loads, integrating multiple flexible resources in energy supply/demand sides and formulating specific policies, etc. To handle these tasks, an optimal operation strategy for MEMG participating in AS is proposed by considering Stackelberg game theory and integrated demand response (IDR). The feasibility of the proposed strategy is validated by a practical MEMG in Hunan, China. The results show that the economic benefits of energy entities are effectively raised and the peak-shaving AS is realized while user satisfaction is also maintained. This work would give reference to the constructor of future AS market to formulate polices about the operation modes and pricing schemes of MEMG.

With the development of electric vehicle (EV), there is a huge demand for electric vehicle charging station (EVCS). The utilization of renewable energy sources (RES) in EVCS can not only decrease the energy fluctuation by participating in peakload reduction of the grid, but also reduce the pollution to the environment by cutting down the use of fossil fuels. In this paper, the optimal planning for grid-connected EVCS with RES is studied by considering EV load uncertainty. Nine scenarios are set based on a different characteristic of EV load to reveal the impact of EV load on net present cost (NPC) and to express the relationship between optimal capacity and energy flow. Moreover, since electricity price also plays an important role in EVCS planning, an economic comparison between different cases with different electricity price for peak-valley-flat period is carried out. The results reveal the economic benefits of applying RES in EVCS, and demonstrate that EV load with different characteristics would influence the capacity of each device (PV, battery, converter) in the EVCS optimal planning.