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7249136 
Journal Article 
Stochastic robust optimization for smart grid considering various arbitrage opportunities 
Saffari, M; Misaghian, MS; Kia, M; Heidari, A; Zhang, D; Dehghanian, P; Aghaei, J; , 
2019 
Yes 
Electric Power Systems Research
ISSN: 0378-7796 
ELSEVIER SCIENCE SA 
LAUSANNE 
174 
WOS:000474498500004 
Because of power electronic advancements, nowadays Plug-in Electric Vehicles (PEVs) are capable to charge/discharge(absorb/inject) active(reactive) power. The storage capacity and the capability of bidirectional flowing active and reactive powers, lead PEVs to be contemplated as a viable option for energy arbitrage. By high penetration of PEVs, decentralized energy management of them, especially at peak hours causes serious problems to the network operation and service quality. Therefore, it is important PEVs to be controlled as integrated with microgrid (MG). Besides, PEVs uncertain behavior along with the prevalent uncertainties inherent to renewable resources and various pricing mechanism in electricity industry leaves the MG operators (MGOs) a challenging decision making. So, it is vital to be applied an efficient strategy in order to deal with this challenges. This paper proposes a centralized framework to co-optimize robust/stochastic optimization of MG with the PEVs energy arbitrage in both active and reactive powers exchange. The problem is a mix-integer non-linear programming (MINLP) problem, which is solved by GAMS software. The results of suggested model are investigated on IEEE 18-bus and IEEE 33-bus test systems. 
Robust/stochastic optimization; Microgrid; Plug-in electric vehicles; Mix-integer non-linear programming