@article { author = {Marami Dizaji, A. and Saniee, M. and Zare, K.}, title = {Resilient Operation Scheduling of Microgrid Using Stochastic Programming Considering Demand Response and Electrical Vehicles}, journal = {Journal of Operation and Automation in Power Engineering}, volume = {7}, number = {2}, pages = {157-167}, year = {2019}, publisher = {University of Mohaghegh Ardabili}, issn = {2322-4576}, eissn = {2423-4567}, doi = {10.22098/joape.2019.5350.1396}, abstract = {Resilient operation of microgrid is an important concept in modern power system. Its goal is to anticipate and limit the risks, and provide appropriate and continuous services under changing conditions. There are many factors that cause the operation mode of micogrid changes between island and grid-connected modes. On the other hand, nowadays, electric vehicles (EVs) are desirable energy storage systems (ESSs) because of clean transportation. Besides, energy storage systems are helpful to decrease power generation fluctuations arising from renewable energy sources (RESs) in new power systems. In addition, both sides (EV and RESs’ owners) can gain a good profit by integrating EVs and RESs. Therefore, in this paper, a resilient operation model for microgrid is presented considering disasters and islands from the grid. In the proposed formulation, microgrid (MG) operator schedules its energy resources, EVs and ESSs in minimum cost considering demand response (DR) program and resiliency of the microgrid to islanding and uncertainties in market price, load, and generation of RESs. The impact of uncertainties is modeled in the scenario based framework as stochastic programming. The efficiency of presented method is validated on IEEE standard test system and discussed in two cases.}, keywords = {demand response,Microgrid,optimal resilient operation,Stochastic programming,Uncertainty}, title_fa = {Resilient operation scheduling of microgrid using stochastic programming considering demand response and electrical vehicles}, abstract_fa = {}, keywords_fa = {}, url = {https://joape.uma.ac.ir/article_769.html}, eprint = {https://joape.uma.ac.ir/article_769_670a87172cea2883e90d5fcba3922469.pdf} }