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Article type: Research Article
Authors: Saeidi, Majida | Niknam, Tahera | Aghaei, Jamshida | Zare, Mohsenb; *
Affiliations: [a] Department of Electrical and Electronic Engineering, Shiraz University of Technology, Shiraz, Iran | [b] Department of Electrical Engineering, Faculty of Engineering, Jahrom University, Jahrom, Iran
Correspondence: [*] Corresponding author. Mohsen Zare, Department of Electrical Engineering, Faculty of Engineering, Jahrom University, Jahrom, Iran. E-mail: [email protected].
Abstract: Distribution network operators have been generally engaged over the last few decades toward distribution system automation to enhance reliability and efficiency of power systems. From the viewpoint of reliability, optimal sectionalizing switch placement is an effective strategy since it mitigates both power network asset cost and number of customers not supplied by outages. From efficiency perspective, introducing capacitors and distributed generations (DGs) and DGs optimal sitting in power distribution systems with the goal of volt/var control can reduce system loss and voltage deviation. In this regard, this paper proposes a methodology to determine the optimal location of sectionalizing switches and DG units while the concept of Volt/Var control problem is also considered. The objective functions are formulated to enhance the network condition during normal and contingency conditions. A new enhanced sine cosine algorithm is proposed for providing the best compromise solution. A self-adaptive probabilistic mutation strategy is appended into the original algorithm to balance exploitation and exploration in order to achieve the promising search space and ultimately converge to the global or near-global optimum. A 33-bus IEEE test system is deployed to assess the superiority of the proposed framework.
Keywords: Distributed generator (DG) placement, multi-objective optimization, sine cosine algorithm, switch placement, volt/var control
DOI: 10.3233/JIFS-18631
Journal: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 6605-6617, 2019
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