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Disorderly charging of large-scale electric vehicles (EVs) would result in the peak electricity consumption, damaging the safe and economic operation of power systems. As an important managing technique of distributed energy resources (DERs), virtual power plant (VPP) can effectively improve the charging strategies of EVs. With this, this paper proposes a bi-level optimal scheduling model of VPP with aggregated plug-in electric vehicles (PEVs) and a battery swapping station, and to optimize the charging/discharging of PEVs and batteries in battery swapping station. Based on the Stackelberg game, the leader is a VPP operator. It guides the charging/discharging behavior of PEVs using reasonable prices. As the followers, PEV owners adjust their charging/discharging strategies based on the leader’s price information. The Karush-Kuhn-Tucker (KKT) conditions are used to transform the bi-level model into a single-level formulation. Numerical results demonstrate that the proposed model can effectively improve overall economic benefits of the VPP, while respecting the interest of each PEV owners. Besides, charging/discharging of EVs are improved sustaining the safe operation of power systems.

With the rapid development of distributed renewable energy generation, the requirement of flexibility is also increasing. The traditional solution to increase flexibility is to conFigure energy storage. However, this method has some problems, such as high investment cost and large-area occupation. Therefore, it is a better method to fully exploit the flexibility of existing resources. This paper proposes an optimal dispatch method of the virtual power plant that aggregates distributed renewable energy resources and building water supply systems. It aims to explore the flexibility of building water supply systems. The proposed model is a mixed-integer non-linear programming model. Thus, a piecewise linearization method is applied to convert the proposed model to a mixedinteger linear programming model to make the model tractable. Simulation results show that the proposed method can not only increase operation economics of the virtual power plant but also enhance demand-side flexibility.

Due to the volatility of renewable energy and randomness of electricity load in virtual power plant (VPP), VPP will inevitably deviate from the pre-planned reference points in real-time operation process. Thus, real-time active power dispatch is essential to re-determine the power output of VPP’ components. Indeed, distributed resources of VPP often belong to different individuals. Coordinating various components of different individuals to participate in VPP realtime scheduling can realize incentive compatibility between VPP and individuals. To this end, this paper proposes real-time active power dispatch for VPP via a multi-agent leaderfollower game approach to achieve the purpose of real-time power balance and economic operation of VPP. In the multiagent leader-follower game, fuzzy control technology is used to generate bidding strategies for various individuals. Simulation results demonstrate the economy and effectiveness of the proposed real-time active power dispatching model for VPP.