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Stochastic scheduling of local distribution systems considering high penetration of plug-in electric vehicles and renewable energy sources

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  • Tabatabaee, Sajad
  • Mortazavi, Seyed Saeedallah
  • Niknam, Taher

Abstract

This paper investigates the optimal scheduling of electric power units in the renewable based local distribution systems considering plug-in electric vehicles (PEVs). The appearance of PEVs in the electric grid can create new challenges for the operation of distributed generations and power units inside the network. In order to deal with this issue, a new stochastic optimization method is devised to let the central controll manage the power units and charging behavior of PEVs. The problem formulation aims to minimize the total cost of the network including the cost of power supply for loads and PEVs as well as the cost of energy not supplied (ENS) as the reliability costs. In order to make PEVs as opportunity for the grid, the vehicle-2-grid (V2G) technology is employed to reduce the operational costs. To model the high uncertain behavior of wind turbine, photovoltaics and the charging and discharging pattern of PEVs, a new stochastic power flow based on unscented transform is proposed. Finally, a new optimization algorithm based on bat algorithm (BA) is proposed to solve the problem optimally. The satisfying performance of the proposed stochastic method is tested on a grid-connected local distribution system.

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  • Tabatabaee, Sajad & Mortazavi, Seyed Saeedallah & Niknam, Taher, 2017. "Stochastic scheduling of local distribution systems considering high penetration of plug-in electric vehicles and renewable energy sources," Energy, Elsevier, vol. 121(C), pages 480-490.
    • Handle: RePEc:eee:energy:v:121:y:2017:i:c:p:480-490
    DOI: 10.1016/j.energy.2016.12.115
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    21. Ahmadian, Ali & Sedghi, Mahdi & Fgaier, Hedia & Mohammadi-ivatloo, Behnam & Golkar, Masoud Aliakbar & Elkamel, Ali, 2019. "PEVs data mining based on factor analysis method for energy storage and DG planning in active distribution network: Introducing S2S effect," Energy, Elsevier, vol. 175(C), pages 265-277.
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