Nanogrids are expected to play a significant role in managing the ever-increasing distributed renewable energy sources. If an off-grid nanogrid can supply fullycharged batteries to a battery swapping station (BSS) serving regional electric vehicles (EVs), it will help establish a structure for implementing renewable-energyto-vehicle systems. A capacity planning problem is formulated to determine the optimal sizing of photovoltaic (PV) generation and battery-based energy storage system (BESS) in such a nanogrid. The problem is formulated based on the mixed-integer linear programming (MILP) and then solved by a robust optimization approach. Flexible uncertainty sets are employed to adjust the conservativeness of the robust optimization, and Monte Carlo simulations are carried out to compare the performance of the solutions. Case studies demonstrate the merits of the proposed applications and verify our approach.

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Conventional environmental-economic power dispatch methods constrain the total amount of emissions of power plants, and they succeed in reducing emissions from the power sector. However, they fail to address the mismatch between emission reductions and the resulting changes in regional air quality. This paper proposes an ecology-and security-constrained unit commitment (Eco-SCUC) model considering the differentiated impacts of generation-associated emissions on regional air quality. A Gaussian puff dispersion model is applied to capture the temporal-spatial transport of air pollutants. Additionally, an air pollutant intensity (API) index is defined for assessing the impacts of emissions on the air quality in regions with differentiated atmospheric environmental capacities. Then the API constraints are formulated based on air quality forecast and included in SCUC model. Moreover, the stochastic optimization is employed to accommodate wind power uncertainty, and the Benders decomposition technique is used to solve the formulated mixed-integer quadratic programming (MIQP) problem. Case studies demonstrate that the Eco-SCUC can cost-effectively improve air quality for densely-populated regions via shifting generation among units and can significantly reduce the person-hours exposed to severe air pollution. Furthermore, the benefits of wind power for air quality control are investigated.

With an increasing number of microgrids being integrated into active distribution networks (ADN), it becomes a challenge how to efficiently coordinate the operations of multiple microgrids (MGs) which are individual entities seeking for their self‐interests. In this paper, a bi‐level noncooperative game‐theoretical model is proposed for MGs operation in ADN based on the distribution system operator (DSO) market and distribution locational marginal prices (DLMPs). The upper level is modeled as a game among MGs who develop their optimal strategies to bid into the DSO market aiming at maximizing their own payoffs. In the lower‐level, the DSO of the ADN implements the market‐clearing and calculates the DLMPs. An iterative solving algorithm is proposed to find the Nash equilibrium of the game model. The case studies show that through the proposed model, the coordinated operation of MGs is achieved while satisfying the security constraints of the ADN.