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Enhancing system reliability by optimally integrating PHEV charging station and renewable distributed generators: A Bi-Level programming approach

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  • Raja S, Charles
  • Kumar N M, Vijaya
  • J, Senthil kumar
  • Nesamalar J, Jeslin Drusila

Abstract

A hybrid bi-level programming approach is presented in this paper to enhance the system reliability by optimally integrating the Vehicle Charging Stations (VCS) of Plug-in Hybrid Electric Vehicle (PHEV) and the Renewable Distributed Generation (RDG) simultaneously. A wide spectrum of requirement exists among the customers to have a continuity of supply in the presence of the fluctuating nature of RDS. Thus, a non-linear objective function is formulated to minimize the Energy Not Supplied (ENS) to the customers based on the various contingency analysis. Two notable contributions distinguish this work with existing endeavours. Firstly, Simultaneous selection of optimal place for both RDG and charging station are recognized. Succeeded by the consideration of simultaneous integration of VCS and RDG, a Hybrid Nelder-Mead Cuckoo Search (HNM-CS) algorithm based method is put into operation to minimize the ENS, which seamlessly diminishes the power loss and enhances the voltage magnitude of the system. The distribution systems of standard IEEE 33-bus and real time TamilNadu (TN) 84 bus are considered with different RDGs such as photovoltaic and fuel cell systems. Further, the operational cost of PHEVs scheduling in the VCS is analysed for a 24-h scenario. From the results obtained, the proposed method provides maximum advantage to the vehicle holder by placing and utilizing more RDGs and meanwhile it satisfies their preferences also.

Suggested Citation

  • Raja S, Charles & Kumar N M, Vijaya & J, Senthil kumar & Nesamalar J, Jeslin Drusila, 2021. "Enhancing system reliability by optimally integrating PHEV charging station and renewable distributed generators: A Bi-Level programming approach," Energy, Elsevier, vol. 229(C).
    • Handle: RePEc:eee:energy:v:229:y:2021:i:c:s0360544221009944
    DOI: 10.1016/j.energy.2021.120746
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    References listed on IDEAS

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    Cited by:

    1. Ch. S. V. Prasad Rao & A. Pandian & Ch. Rami Reddy & A. Giri Prasad & Ahmad Alahmadi & Yasser Alharbi, 2022. "A Hybrid AOSAOA Scheme Based on the Optimal Location for Electric Vehicle Parking Lots and Capacitors in a Grid to Care of Voltage Profile and Power Loss," Energies, MDPI, vol. 15(12), pages 1-23, June.
    2. Ruisheng Wang & Zhong Chen & Qiang Xing & Ziqi Zhang & Tian Zhang, 2022. "A Modified Rainbow-Based Deep Reinforcement Learning Method for Optimal Scheduling of Charging Station," Sustainability, MDPI, vol. 14(3), pages 1-14, February.

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