OPF Solution for Thermal Power Plant Generating Units with Valve-Point Loading Effects and Multiple Fuels Using IGSA
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In this paper, a new solution method, which is an improved version of gravitational search algorithm (IGSA), is proposed to solve discrete optimal power flow (OPF) problem that has both discrete and continuous variables considering valve-point loading effects and multiple fuels .IGSA is based on the Newton’s law of gravity and mass interactions. In the proposed algorithm, the searcher agents are a collection of masses that interact with each other using laws of gravity and motion of Newton. The OPF problem is formulated as a single-objective mix-integer nonlinear problem, where optimal setting of the OPF control variables for minimization of total fuel cost considering without valve point loading effects, with valve point loading effects and multiple fuels are obtained .The IEEE 30-bus test system is presented to demonstrate the application of the proposed problem .The obtained results are compared to other methods recently published in the literatures and the superiority of the proposed approach over other methods is verified.
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J.A. Momoh ,”A generalized quadratic-based model for optimal power flow”, in proc. Int. Conf. Systems, Man, Cybernetics, vol.1, Nov.1989, pp.261-271.
R.C. Burchett, H.H Happ, and K.A. Wirgau , Large-Scale optimal power flow, IEEE Trans. Power App. Syst,vol.PAS-101,no.10,pp-3722-3732,oct.1982.
J.A. Momoh and J.Z. Zhu ,Improved Interior point method for OPF problems, IEEE Trans. Power App. Syst, vol. 14, no.4, pp.1114-1120, Aug 1999.
Ezzati, S.M., Vahedi, H., Yousefi, G.R., Pedram, M.M., Security constrained optimal power flow solved by Mixed Integer Non Linear Programming, (2011) International Review of Electrical Engineering (IREE), 6 (7), pp. 3051-3057.
A.G. Bakirtzis, P.N Biskas, C.E. Zoumas, and V. Petridis, Optimal Power Flow by enhanced genetic algorithm, IEEE Trans. Power Syst. vol.17, no.2, May 2002, pp.229-236.
J. Yuryevich and K.P.Wong, “Evolutionary programming based optimal power flow algorithm,” IEEE Trans.Power Syst. vol.14, no.4, ,Nov. 1999, pp.1245-1250.
Abido MA. Optimal power flow using particle swarm optimization. Electr Power Energy Syst. 24: 2002; 563-71.
Abou El Ela AA, Abido MA, Spea SR. Optimal power flow using differential evolution algorithm. Electr power Syst Res; 80: 2010 878-85.
Bhattacharya A, Chattopadhyay PK. Application of biogeography-based optimisation to solve different optimal power flow problems. IET Gener Transm Distrib 5(1): 2011; 70–80.
Sayah S, Zehar K. Modified differential evolution algorithm for optimal power flow with non-smooth cost functions. Energy Conversion and Management; 49: 20083036–42.
Lai LL, Ma JT, Yokoyama R, Zhao M. Improved genetic algorithms for optimal power flow under normal and contingent operation states. Int J Electr Power Energy Syst;19(5): 1997, 287–92.
Lee KY, Park YM, Ortiz JL. A united approach to optimal real and reactive power dispatch. IEEE Trans Power Appar Syst PAS; 104(5): 1985,1147–53.
Vaisakh K, Srinivas LR. Evolving ant direction differential evolution for OPF with non-smooth cost functions. Eng Appl. Artificial Intelligence; 24: 2011,426–36.
Vaisakh K, Srinivas LR. ‘‘Genetic evolving ant direction HDE for OPF with nonsmooth cost functions and statistical analysis. Expert Syst Appl.; 38: 2011, 2046–62.
Bakirtzis AG, Biskas PN, Zournas CE, Petridis V. Optimal power flow by enhanced genetic algorithm. IEEE Trans Power Syst;17(2): 2002,229–36.
Ayan, K., Kilic, U., Solution of multi-objective optimal power flow with chaotic artificial bee colony algorithm, (2011) International Review of Electrical Engineering (IREE), 6 (3), pp. 1365-1371.
Ghanizadeh, A.J., Mokhtari, G., Abedi, M., Gharehpetian, G.B., Optimal power flow based on imperialist competitive algorithm, (2011) International Review of Electrical Engineering (IREE), 6 (4), pp. 1847-1852.
Kwannetr, U., Leeton, U., Kulworawanichpong, T., Optimal power flow solution using artificial bees colony algorithms, (2011) International Review of Electrical Engineering (IREE), 6 (4), pp. 1870-1882.
Duman Serhat, Guvenc Ugur, Sonmez Yusuf, Yorukeren Nuran, Optimal power flow using gravitational search algorithm. Energy Conversion and Management; 50: 2012,86-95.
Bhattacharya A, Roy P.K. Solution of multi-objective optimal power flow using gravitational search algorithm. IET Gener and Transmission Distribution.;6(8):, 2012751–763.
Rashedi E, Rashedi E, Nezamabadi-pour H, Saryazdi. GSA: a gravitational search algorithm. Inform Sci;179: 2009,2232–48.
Ceylan O, Ozdemir A, Dag H. Gravitational search algorithm for post-outagebus voltage magnitude calculations. In: International universities’ power engineering conference, Wales (UK); 31 August–3 September, 2010.
Rashedi E, Nezamabadi-pour H, Saryazdi S. BGSA: “Binary gravitational search algorithm:. Nat Comput;9: 2010,727–45.
Nayak M.R, Ray R. and Rout P.K , “Multi-objective Optimal Reactive Power Dispatch in Power system using Differential Evolution Algorithm”, International Conference on Emerging Trends in Electrical, Communication and Information Technologies, Elsevier India Pvt. Ltd. vol. 2 ,2012, pp. 16-26.Ananthapur,India.
Alsac O, Stott B. Optimal load flow with steady-state security. IEEE Trans Power Appar Syst PAS ; 93(3),1974:745–51.
Lee KY, Park YM, Ortiz JL. A united approach to optimal real and reactive power dispatch. IEEE Trans Power Appar Syst PAS; 104(5), 1985:1147–53.
Yuryevich J, Wong KP. Evolutionary programming based optimal power flow algorithm. IEEE Trans Power Syst: 14(4):1999; 1245–50.
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