title: Optimal clustering of MGs based on droop controller for improving reliability using a hybrid of harmony search and genetic algorithms.
abstract: This paper proposes a novel method to address reliability and technical problems of microgrids (MGs) based on designing a number of self-adequate autonomous sub-MGs via adopting MGs clustering thinking. In doing so, a multi-objective optimization problem is developed where power losses reduction, voltage profile improvement and reliability enhancement are considered as the objective functions. To solve the optimization problem a hybrid algorithm, named HS-GA, is provided, based on genetic and harmony search algorithms, and a load flow method is given to model different types of DGs as droop controller. The performance of the proposed method is evaluated in two case studies. The results provide support for the performance of the proposed method.
authors.affiliation: Faculty of Engineering, Department of Electrical Engineering, Bu-Ali Sina University, Hamedan, Iran. Electronic address: m_abedini_dr@yahoo.com.
authors.forename: Mohammad
authors.initials: M
authors.lastname: Abedini
authors.affiliation: Faculty of Engineering, Department of Electrical Engineering, Bu-Ali Sina University, Hamedan, Iran. Electronic address: mh_moradi@yahoo.co.uk.
authors.forename: Mohammad H
authors.initials: MH
authors.lastname: Moradi
authors.affiliation: Department of Civil, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran. Electronic address: s.hosseinian@basu.ac.ir.
authors.forename: S M
authors.initials: SM
authors.lastname: Hosseinian
keywords: Droop controller; Fuzzy; HS-GA; MGs clustering; Multi-objective optimization