M. Kavitha - Department of ECE, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences
S.J. Mahendra - ۲ Department of Medical Electronics, Ramaiah Institute of Technology, Bengaluru, E-mail: mahendra.j@msrit.edu
S. Chupradit - Department of Occupational Therapy, Faculty of Associated Medical Sciences
A.S. Nurrohkayati - Department of Mechanical Engineering, Universitas Muhammadiyah Kalimantan Timur, Samarinda, Indonesia
S.B. Kadhim - College of Dentistry, Al-Ayen University, Thi-Qar, Iraq
Y.F. Mustafa - Department of Pharmaceutical Chemistry, College of Pharmacy, University of Mosul, Mosul, Iraq
A.T. Jalil - Faculty of Biology and Ecology, Yanka Kupala State University of Grodno, ۲۳۰۰۲۳ Grodno, Belarus
M.H. Ali - Al-Nisour University College, Baghdad, Iraq
D. Sunarsi - Universitas Pamulang, Tangerang Selatan, Banten, Indonesia
L. Akhmetov - Kazan Federal University, Russia

Electric energy demand is increasing rapidly in developing countries, making the installation of additional generating units necessary. Private generating stations are encouraged to add new generations in deregulated energy networks. Planning for transmission expansion must ensure increased market competition while maintaining high levels of dependability and system operation safety. New objectives and demands have been made for the transmission expansion issue as a result of the deregulation of the energy network. This study has attempted to provide a new population-base algorithm; called Modified Honey Bee Mating Optimization (MHBMO) for expansion development in deregulated energy systems that are applied in multi-objective processes. In addition, to diminish the elaborateness of the issue the benders decomposition is used in this study which categorize the original issue into two subproblems. First maximizing the profits of each PBGEP (GENCO) and second, satisfying security network constraints (SCGEP). Therefore, using the suggested MHBMO algorithm, value of each GENCO's profit and overall profit could be obtained. To demonstrate the viability and capabilities of the suggested algorithm, the planning methodology has been evaluated using the IEEE ۳۰-bus test system. The results of the current study served as an example of the effectiveness of the suggested methodology.

Benders decomposition, Generation Expansion Planning, MHBMO, optimization