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Power Optimization and Prioritization in an Island Supplied by a Rotating Machine Based Distributed Generator Using Artificial Bee Colony Algorithm
International Journal of Energy and Power Engineering
Volume 5, Issue 1, February 2016, Pages: 15-21
Received: Jan. 5, 2016; Accepted: Jan. 14, 2016; Published: Feb. 23, 2016
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L. Mogaka, Electrical and Electronics Department, Technical University of Mombasa, Mombasa, Kenya
D. K. Murage, Electrical and Electronics Department, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
M. J. Saulo, Electrical and Electronics Department, Technical University of Mombasa, Mombasa, Kenya
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Currently the greatest threat to the power systems reliability and security is the cascading of electric system failures thus causing power blackouts. For quite some time now, the world has been encountering many power blackouts as a result of these cascading failures. The cascading power failure instances pose great risks towards the integrity of power system network. This may finally lead to the splitting of the power system into various small unintentional islands. Hence, intentional or controlled islanding is then utilized as a preventive measure to mitigate the losses caused by unintentional islanding of the power system. Thus, by doing this, the entire power system is split into controlled island regions for the purposes of easy handling and control. In such situation, each islanded region should have sufficient generation to supply its connected loads in order to remain operative and stable. It should also be pointed out that intentional islanding is very important as it can prevent the entire power system from collapsing. The distributed generators supplying the loads in these islands may not be able to maintain the voltage and frequency within desired limits in the distribution system when it is islanded within the micro grid. There may be a power deficit within the island. This eventually leads to shedding of some loads within the island for the sake of stability of the system. Hence the main challenge here is to determine the appropriate and reliable method to optimize the power supply and the load demand in the island and thus maintain the voltage and frequency within the desired limit. In this study we focused on the determination of the minimum load amount for shedding within the islanded region and the prioritization of the buses for shedding so that electricity supply to customers could be maximized using ABC algorithm. From the results obtained, the ABC algorithm can be successfully applied for solving the optimization and prioritization problems within the island being supplied by a DG. The ABC algorithm has several merits over other algorithms which makes it suitable in this application. These advantages include; it is easily implemented, flexible, has few control parameters, easily hybridized with other optimization algorithms and can be modified very easily to suit any application. This system was simulated in MATLAB and SIMULINK using IEEE fourteen bus systems.
ABC Algorithm, Islanding, Power Prioritization and Optimization
To cite this article
L. Mogaka, D. K. Murage, M. J. Saulo, Power Optimization and Prioritization in an Island Supplied by a Rotating Machine Based Distributed Generator Using Artificial Bee Colony Algorithm, International Journal of Energy and Power Engineering. Vol. 5, No. 1, 2016, pp. 15-21. doi: 10.11648/j.ijepe.20160501.13
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Azakiah, K., Hussain, S., Erdal, B., & Tamer, K. (December 2013). A review of islanding dtection techniques for renewable distributed generation systems. Renewable and sustainable energy reviews, 28, 483-493.
Belkacem, M., & Kamel, S. (2014). Solving Practical Economic Dispatch Problems Using Improved Artificial Bee Colony Method. International Journal Intelligent Systems and Applications, 7, 36-43.
F, A., Mohamed, M., Elarini, M., & Ahmed, O. M. (2014). A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system. Journal of Advanced Research, 5, 397-408.
Hardiansyah, Junaidi, & Yohannes, M. (2012). Application of soft computing methods for economic load dispatch problems. International journal of computer applications, 58 (13).
Hemamalini, S., & Sishai, P. (2010). Artificial bee colony algorithm for economic dispatch problem with non-smooth cost functions, electric power components and systems. 38 (7), 786-803.
Karaboga, D., & Akay, B. (2009). A comparative study of artificial bee colony algorithm. Applied Mathematics and Computation, 214 (1), 108-132.
Karaboga, D., & Basturk, B. (2007). A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. Journal of Global Optimization, 39 (3), 459-471.
Laghari, J., Mokhlis, H., Karimi, M., Bakar, A. H., & Hasmaini, M. (2014). Computational Intelligence based techniques for islanding detection of distributed generation in distribution network: A review. Energy Conversion and Management, 88, 139-152.
Luong, D., Dieu, N., & Pandian, V. (2013). Artificial bee colony algorithm for solving optimal power flow algorithm. The scientific world journal, 2013.
Mahani, Z. A. (2000). Malaysian economic recovery measures: A response to crisis management and for long-term economic sustainability. ASEAN university network's conference on economic crisis in southeast Asia: Its social, political and cultural impacts. Bangkok, Thailand.
Martin, J. (2009). Distributed vs. centralized electricity generation: are we witnessing a change of paradigm? paris.
Mogaka, L. O., Murage, D. K., & Saulo, M. J. (2015). Rotating Machine based DG islanding Detection Analysis using Wavelet Transform. International Journal of Energy and Power Engineering, 4 (5), 257-267.
Mogaka, L. O., Murage, D. K., & Saulo, M. J. (2015). Rotating Machine Based Islanding Detection Using Fuzzy Logic Method. International Journal of Energy and Power Engineering, 4 (5), 311-316.
Murthy, G., Sivanagaraju, S., Satyanarayana, S., & Rao, H. (2013). Optimal placement of DG in distribution system to mitigate power quality disturbances. World academy of science, engineering and technology, 7, 204-209.
Pukar, M., Zhe, C., & Birgitte, B. J. (2008). Review on islanding operation of distribution system with distributed generation. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Nanjing, china.
Rao, R., Narasimham, S., & Ramalingaraju, M. (2008). Optimization of distribution network configuration for lossr eduction using artificial bee colony algorithm. International Journal of Electrical Power and Energy Systems, 1 (2), 116-122.
Singh, A. (2009). An artificial bee colony algorithm for the leaf constrained minimum spanning tree problem. Applied Soft Computing Journal, 9 (2), 625-631.
Sumpavakup, C., Srikun, I., & Chusanapiputt, S. (2010). A Solution to the Optimal Power Flow Using Artificial Bee Colony Algorithm. International Conference on Power System Technology, 1-5.
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