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Optimal scheduling of electric vehicles considering uncertain RES generation using interval optimization

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Abstract

The penetration of renewable energy sources (RES) has been increased throughout the world. The main characteristic of RESs is that their generating powers are intermittent and unpredictable. This paper presents an interval optimization method to optimally schedule electric vehicles (EV) with considering the uncertainty of RES generation and loads. For this purpose, the RES generation (including photovoltaic and wind power) and loads are considered as interval parameters, and the charging/discharging power of EV is expressed as an interval variable to be optimally computed. The capability of RES inverters to regulate voltages is also considered in the interval optimization model. The objective function is to minimize the network active power losses and total voltage magnitude deviation with considering overall system constraints. The proposed method is tested on a 33-bus distribution system with uncertain RESs and loads, and the optimal day-ahead scheduling of EV is performed. Different case studies are carried out to test the effectiveness of the proposed method. It is demonstrated that the proposed interval optimization method can accurately represent the uncertain problem, and it provides further information compared with the deterministic optimization.

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Authors and Affiliations

  1. Department of Electrical Engineering, South Valley University, Qena, 83523, Egypt

    Abdelfatah Ali

  2. Department of Electric Power Engineering, Budapest University of Technology and Economics, Budapest, 1111, Hungary

    Abdelfatah Ali & David Raisz

  3. Department of Electrical Engineering, Aswan University, Aswan, 81542, Egypt

    Karar Mahmoud

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  1. Abdelfatah Ali
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  2. David Raisz
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  3. Karar Mahmoud
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Correspondence to Abdelfatah Ali.

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Ali, A., Raisz, D. & Mahmoud, K. Optimal scheduling of electric vehicles considering uncertain RES generation using interval optimization. Electr Eng 100, 1675–1687 (2018). https://doi.org/10.1007/s00202-017-0644-x

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  • DOI: https://doi.org/10.1007/s00202-017-0644-x

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