Optimal Network Reconfiguration with Distributed Generation and Electric Vehicle Charging Stations
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Published:2021-07-18
Issue:4
Volume:6
Page:1174-1185
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ISSN:2455-7749
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Container-title:International Journal of Mathematical, Engineering and Management Sciences
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language:en
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Short-container-title:Int J Math, Eng, Manag Sci
Affiliation:
1. Department of Railroad Electrical Systems, Woosong University, Daejeon, 34606, Republic of Korea.
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.
Publisher
International Journal of Mathematical, Engineering and Management Sciences plus Mangey Ram
Subject
General Engineering,General Business, Management and Accounting,General Mathematics,General Computer Science
Reference36 articles.
1. Altun, T., Madani, R., Yadav, A.P., Nasir, A., & Davoudi, A. (2020). Optimal reconfiguration of dc networks. IEEE Transactions on Power Systems, 35(6), 4272-4284. 2. Amin, A., Tareen, W.U.K., Usman, M., Memon, K.A., Horan, B., Mahmood, A., & Mekhilef, S. (2020). An integrated approach to optimal charging scheduling of electric vehicles integrated with improved medium-voltage network reconfiguration for power loss minimization. Sustainability, 12(21), 1-15. 3. Asrari, A., Lotfifard, S., & Payam, M.S. (2016). Pareto dominance-based multiobjective optimization method for distribution network reconfiguration. IEEE Transactions on Smart Grid, 7(3), 1401-1410. 4. Babu, P.V.K., & Swarnasri, K. (2020). Multi-objective optimal allocation of electric vehicle charging stations in radial distribution system using teaching learning based optimization. International Journal of Renewable Energy Research, 10(1), 366-377. 5. Cui, Z., Bai, X., Li, P., Li, B., Cheng, J., Su, X., & Zheng, Y. (2020). Optimal strategies for distribution network reconfiguration considering uncertain wind power. CSEE Journal of Power and Energy Systems, 6(3), 662-671.
Cited by
11 articles.
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