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Kavitha, M., Mahendra, S.J., Chupradit, S., Nurrohkayati, A.S., Kadhim, S.B., Mustafa, Y.F., Jalil, A.T., Ali, M.H., Sunarsi, D., Akhmetov, L.. (1401). A Novel Improved HBMO Algorithm Regarding Generation Expansion Planning in Deregulated Energy Networks. سامانه مدیریت نشریات علمی, 11(Special Issue (Open)), -. doi: 10.22098/joape.2023.10221.1725
M. Kavitha; S.J. Mahendra; S. Chupradit; A.S. Nurrohkayati; S.B. Kadhim; Y.F. Mustafa; A.T. Jalil; M.H. Ali; D. Sunarsi; L. Akhmetov. "A Novel Improved HBMO Algorithm Regarding Generation Expansion Planning in Deregulated Energy Networks". سامانه مدیریت نشریات علمی, 11, Special Issue (Open), 1401, -. doi: 10.22098/joape.2023.10221.1725
Kavitha, M., Mahendra, S.J., Chupradit, S., Nurrohkayati, A.S., Kadhim, S.B., Mustafa, Y.F., Jalil, A.T., Ali, M.H., Sunarsi, D., Akhmetov, L.. (1401). 'A Novel Improved HBMO Algorithm Regarding Generation Expansion Planning in Deregulated Energy Networks', سامانه مدیریت نشریات علمی, 11(Special Issue (Open)), pp. -. doi: 10.22098/joape.2023.10221.1725
Kavitha, M., Mahendra, S.J., Chupradit, S., Nurrohkayati, A.S., Kadhim, S.B., Mustafa, Y.F., Jalil, A.T., Ali, M.H., Sunarsi, D., Akhmetov, L.. A Novel Improved HBMO Algorithm Regarding Generation Expansion Planning in Deregulated Energy Networks. سامانه مدیریت نشریات علمی, 1401; 11(Special Issue (Open)): -. doi: 10.22098/joape.2023.10221.1725

A Novel Improved HBMO Algorithm Regarding Generation Expansion Planning in Deregulated Energy Networks

Journal of Operation and Automation in Power Engineering
دوره 11، Special Issue (Open)، خرداد 2023  XML اصل مقاله (438.44 K)
نوع مقاله: Special issue
شناسه دیجیتال (DOI): 10.22098/joape.2023.10221.1725
نویسندگان
M. Kavitha email 1؛ S.J. Mahendra2؛ S. Chupradit3؛ A.S. Nurrohkayati4؛ S.B. Kadhim5؛ Y.F. Mustafa6؛ A.T. Jalil7، 8، 9؛ M.H. Ali10؛ D. Sunarsi11؛ L. Akhmetov12
1Department of ECE, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences
22 Department of Medical Electronics, Ramaiah Institute of Technology, Bengaluru, E-mail: mahendra.j@msrit.edu
3Department of Occupational Therapy, Faculty of Associated Medical Sciences
4Department of Mechanical Engineering, Universitas Muhammadiyah Kalimantan Timur, Samarinda, Indonesia
5College of Dentistry, Al-Ayen University, Thi-Qar, Iraq
6Department of Pharmaceutical Chemistry, College of Pharmacy, University of Mosul, Mosul, Iraq
7Faculty of Biology and Ecology, Yanka Kupala State University of Grodno, 230023 Grodno, Belarus
8College of technical engineering, The Islamic University, Najaf, Iraq
9Department of Dentistry, Kut University College, Kut, Wasit, 52001, Iraq
10Al-Nisour University College, Baghdad, Iraq
11Universitas Pamulang, Tangerang Selatan, Banten, Indonesia
12Kazan Federal University, Russia
چکیده
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 30-bus test system. The results of the current study served as an example of the effectiveness of the suggested methodology.
کلیدواژه‌ها
Benders decomposition؛ generation expansion planning؛ MHBMO؛ optimization
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