| Resumo: | Renewable energy resources such as wind and solar are increasingly more important in distribution net-works and microgrids as their presence keeps flourishing. They help to reduce the carbon footprint ofpower systems, but on the other hand, the intermittency and variability of these resources pose seri-ous challenges to the operation of the grid. Meanwhile, more flexible loads, distributed generation, andenergy storage systems are being increasingly used. Moreover, electric vehicles impose an additionalstrain on the uncertainty level, due to their variable demand, departure time and physical location. Thispaper formulates a two-stage stochastic problem for energy resource scheduling to address the chal-lenge brought by the demand, renewable sources, electric vehicles, and market price uncertainty. Theproposed method aims to minimize the expected operational cost of the energy aggregator and is basedon stochastic programming. A realistic case study is presented using a real distribution network with201-bus from Zaragoza, Spain. The results demonstrate the effectiveness and efficiency of the stochasticmodel when compared with a deterministic formulation and suggest that demand response can play asignificant role in mitigating the uncertainty.
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