Abstract
This paper proposed a procedure to solve the optimal reactive power dispatch (ORPD) problem using ant colony optimization (ACO) algorithm. The objective of the ORPD problem is to minimize the transmission power losses under control and dependent variable constraints. Proposed sensitivity parameters of reactive power at generation and switchable sources are derived based on a modified model of fast decoupled power flow. The proposed ACO-based algorithm is applied to the IEEE standard 14-bus, 30-bus systems, and a real power system at West Delta Network as a part of the Unified Egyptian Network. The obtained simulation results are compared with those of conventional linear programming, genetic algorithm, and particle swarm optimization technique. Simulation results show the capability of the proposed ACO-based algorithm for solving the ORPD problem, especially with increasing the system size.
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References
Li F, Pilgrim JD, Dabeedin C, Chebbo A, Aggarwal RK (2005) Genetic algorithms for optimal reactive power compensation on the national grid system. IEEE Trans Power Syst 20: 493–500
Subbaraj P, Rajnarayanan PN (2009) Optimal reactive power dispatch using self-adaptive real coded genetic algorithm. Electr Power Syst Res 79: 374–381
Zhang Y, Ren Z (2005) Optimal reactive power dispatch considering costs of adjusting the control devices. IEEE Trans Power Syst 20: 1349–1356
Yan W, Lu S, Yu DC (2004) A novel optimal reactive power dispatch method based on an improved hybrid evolutionary programming technique. IEEE Trans Power Syst 19: 913–918
Zhao B, Guo CX, Cao YJ (2005) A multiagent-based particle swarm optimization approach for optimal reactive power dispatch. IEEE Trans Power Syst 20: 1070–1078
Yan W, Lu S, Yu DC (2004) A novel optimal reactive power dispatch method based on an improved hybrid evolutionary programming technique. IEEE Trans Power Syst 19: 913–918
Dai C, Chen W, Zhu Y, Zhang X (2009) Reactive power dispatch considering voltage stability with seeker optimization algorithm. Electr Power Syst Res 79: 1462–1471
Dorigo M (1992) Optimization, learning and natural algorithms. PhD dissertation, Department of Electronics, Politecnico di Milano, Milan
Dorigo M, Stützle T (2004) Ant colony optimization. MIT Press, New York
Dorigo M, Gambardella LM (1997) Ant colonies for the traveling salesman problem. Biosystems 43: 73–81
Yu I-K, Chou CS, Song YH (1998) Application of the ant colony search algorithm to short-term generation scheduling problem of thermal units. In: Proceedings of international conference on power system technology, vol 1, POWERCON ’98, Aug 1998, Beijing, China, pp 552–556
Song YH, Chou CSV, Min Y (1999) Large-scale economic dispatch by artificial ant colony search algorithms. Electr Power Compon Syst 27: 679–690
Hou YH, Wu YW, Lu LJ, Xiong XY (2002) Generalized ant colony optimization for economic dispatch of power systems. IEEE Int Conf Power Syst Technol 1: 225–229
EL-Sharkh MY, Sisworahardjo NS, Rahman A, Alam MS (2006) An improved ant colony search algorithm for unit commitment application. In: IEEE power systems conference and exposition, pp 1741–1746
Vlachogiannis JG, Hatziargyriou ND, Lee KY (2005) Ant colony system-based algorithm for constrained load flow problem. IEEE Trans Power Syst 20: 1241–1249
Meziane R, Massim Y, Zeblah A, Ghoraf A, Rahli R (2005) Reliability optimization using ant colony algorithm under performance and cost constraints. Electr Power Syst Res 76: 1–8
Favuzza S, Graditi G, Sanseverino ER (2006) Adaptive and dynamic ant colony search algorithm for optimal distribution systems reinforcement strategy. Appl Intell 24: 31–42
Carpaneto E, Chicco G (2008) Distribution system minimum loss reconfiguration in the hyper-cube ant colony optimization framework. Electr Power Syst Res 78: 2037–2045
Niknam T (2008) A new approach based on ant colony optimization for daily Volt/Var control in distribution networks considering distributed generators. Energy Convers Manage 49: 3417–3424
Lenin K, Mohan MR (2006) Ant colony search algorithm for optimal reactive power optimization. Serbian J Electr Eng 3: 77–88
Ketabi A, babaee AA, Feuillet R (2010) Application of the ant colony search algorithm to reactive power pricing in an open electricity market. Electr Power Energy Syst 32: 622–628
Pechač P (2002) Electromagnetic wave propagation modeling using the ant colony optimization algorithm. Radio Eng 11: 1–6
Lee KY, Vlachogiannis JG (2005) Optimization of power systems based on ant colony system algorithms: an overview. In: 13th international conference on intelligent systems application to power systems, 6–10 Nov 2005, pp 22–35
Washington University. http://www.ee.washington.edu/research/pstca/
El-Sehiemy RA (2008) Performance of transmission network under deregulated electrical power system. PhD thesis, Faculty of Engineering, Minoufiya University, Egypt
Abou El-Ela AA, Allam SM, Shatla MM (2010) Maximal optimal benefits of distributed generation using genetic algorithms. Electr Power Syst Res 80: 869–877
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Abou El-Ela, A.A., Kinawy, A.M., El-Sehiemy, R.A. et al. Optimal reactive power dispatch using ant colony optimization algorithm. Electr Eng 93, 103–116 (2011). https://doi.org/10.1007/s00202-011-0196-4
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DOI: https://doi.org/10.1007/s00202-011-0196-4