International Journal of Mathematical, Engineering and Management Sciences

ISSN: 2455-7749

Optimal Network Reconfiguration with Distributed Generation and Electric Vehicle Charging Stations

Surender Reddy Salkuti
Department of Railroad Electrical Systems, Woosong University, Daejeon, 34606, Republic of Korea.

DOI https://doi.org/10.33889/IJMEMS.2021.6.4.070

Received on March 07, 2021
  ;
Accepted on June 27, 2021

Abstract

This paper proposes an optimal network reconfiguration (ONR) by integrating the renewable energy (RE) based distributed generation (DG) resources, i.e., wind and solar photovoltaic (PV) modules, and electric vehicle charging stations (EVCS). The uncertainties related to renewable energy sources (RESs) are handled by using probability analysis. In this work, wind uncertainty is handled by using Weibull probability density function (PDF), and solar PV uncertainty is modeled by using Beta PDF. This paper also models the load of EVCSs. The ONR is a tool to operate distribution systems (DSs) at optimum cost/loss. In the literature, most of the ONR problems are solved as single objective type. This neccessiate the development of multi-objective based ONR problem and solved using the multi-objective algorithms by considering multiple objectives. Therefore in this paper, total cost of operation and power losses are considered as two objectives functions. The single objective-based ONR is solved using crow search algorithm (CSA) and multi-objective-based ONR is solved using multi-objective-based CSA. As the DS is unbalanced, the power flow for the unbalanced system will include the three-phase transformer. The ONR problem has been solved by considering 17 bus unbalanced and balanced DSs.

Keywords- Electric vehicles, Distribution system, Network reconfiguration, Renewable energy, Uncertainty.

Citation

Salkuti, S. R (2021). Optimal Network Reconfiguration with Distributed Generation and Electric Vehicle Charging Stations. International Journal of Mathematical, Engineering and Management Sciences, 6(4), 1174-1185. https://doi.org/10.33889/IJMEMS.2021.6.4.070.

Conflict of Interest

The authors declare that there is no conflict for this publication.

Acknowledgements

This research work was funded by “Woosong University’s Academic Research Funding -2021”.

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