Blending of Genetic Algorithm with Fletcher Reeves Method to Solve Reactive Power Problem
Year 2015,
Volume: 3 Issue: 3, 154 - 157, 30.12.2015
Kanagasabai Lenin
,
Bhumanapally Ravindhranath Reddy
M. Surya Kalavathi
Abstract
In this study a hybrid algorithm - Fletcher Reeves method and advanced Genetic Algorithm (GA) are suggested to solve reactive power problem. In this approach, each of the G Fletcher Reeves method again with progressive operators are calculated step length. These approaches are extended to a set of multi-point access instead of single point approximation to avoid the convergence of the available method at local optimum and a new method, named Population Based Fletcher Reeves Method (PFR), are proposed to solve the reactive power problem. PFR was tested in standard IEEE 30 bus test system and simulation results demonstrate obviously about the best performance of the recommended algorithm in reducing the real power loss with control variables within the limits.
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technique,” IEEE Transactions on Power Systems, vol.15, no.2, pp.
844-851, may 2000.
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method based on an improved hybrid evolutionary programming
technique,” IEEE Transactions on Power Systems, vol. 19, no. 2, pp.
913 – 918, may 2004.
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algorithminterior point method for optimal reactive power flow,” IEEE
Transactions on Power Systems, vol.21, no.3, pp.1163-1169, Aug.
2006.
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piecewiseoptimal reactive power-flow model and its algorithm for acdc
systems,” IEEE Transactions on Power Systems, vol.23, no.1, pp.
170-176, Feb. 2008.
[18] F. Capitanescu, “Assessing reactive power reserves with respect to
operating constraints and voltage stability,” IEEE Transactions on
Power Systems, vol.26, no.4, pp.2224–2234, nov.2011.
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dispatch: Formulation and solution method,” International Journal of
Electrical Power and Energy Systems, vol.32, no.6, pp.615-621, 2010.
[20] Kargarian, M. Raoofat, and M. Mohammadi, “Probabilistic reactive
power procurement in hybrid electricity markets with uncertain loads,”
Electric Power Systems Research, vol.82, no. , pp. 68-80, 2012.
[21] Li Zhang, Weijun Zhou , Donghui Li, “Global convergence of a
modified Fletcher–Reeves conjugate gradient method with Armijo-type
line search”, Numerische Mathematik, October 2006, vol.104, no.4,
pp.561-572
[22] K. Deb, A. Anand, and D. Joshi, A computationally efficient
evolutionary algorithm for realparameter optimization. Evolutionary
computation, Vol.10, No.4, pp.371-395, 2002.
[23] K. Deb, and M.Thakur, A new crossover operator for real coded genetic
algorithms. Applied Mathematics and Computation, vol.188(1),
pp.895-911, 2007.
[24] Q.H. Wu, Y.J.Cao, and J.Y. Wen. Optimal reactive power dispatch
using an adaptive genetic algorithm. Int. J. Elect. Power Energy Syst.
vol 20. pp.563-569, Aug 1998.
[25] B. Zhao, C. X. Guo, and Y.J. CAO.Multiagent-based particle swarm
optimization approach for optimal reactive power dispatch. IEEE Trans.
Power Syst. Vol.20, no.2, pp.1070-1078, May 2005.
[26] Mahadevan. K, Kannan P. S. “Comprehensive Learning Particle Swarm
Optimization for Reactive Power Dispatch”, Applied Soft Computing,
Vol.10, No.2, pp.641–52, March 2010.
[27] A.H. Khazali, M. Kalantar, “Optimal Reactive Power Dispatch based
on Harmony Search Algorithm”, Electrical Power and Energy Systems,
vol.33, no.3, pp.684-692, March 2011.
[28] S. Sakthivel, M. Gayathri, V. Manimozhi, “A Nature Inspired
Optimization Algorithm for Reactive Power Control in a Power
System”, International Journal of Recent Technology and Engineering
(IJRTE) , vol.2, no.1, pp.29-33, March 2013.
Year 2015,
Volume: 3 Issue: 3, 154 - 157, 30.12.2015
Kanagasabai Lenin
,
Bhumanapally Ravindhranath Reddy
M. Surya Kalavathi
References
- [1] O. Alsac, and B. Scott, “Optimal load flow with steady state security”,
IEEE Transaction. PAS, pp.745-751, 1973.
[2] K.Y. Lee, Y.M. Paru, J.L. Oritz –A united approach to optimal real and
reactive power dispatch , IEEE Transactions on power Apparatus and
systems, PAS-104, pp.1147-1153, 1985.
[3] A.Monticelli , M .V.F Pereira ,and S. Granville , “Security constrained
optimal power flow with post contingency corrective rescheduling” ,
IEEE Transactions on Power Systems, PWRS-2, no.1, pp.175-
182,1987.
[4] DeebN ,Shahidehpur S.M ,Linear reactive power optimization in a large
power network using the decomposition approach. IEEE Transactions
on power system, vol.5, no.2, pp.428-435, 1990.
[5] E. Hobson ,’Network consrained reactive power control using linear
programming, ‘ IEEE Transactions on power systems PAS -99 (4), pp
868-877, 1980
[6] K.Y. Lee, Y.M Park, and J.L Oritz, “Fuel –cost optimization for both
real and reactive power dispatches” , IEE Proc; 131C,(3), pp.85-93.
[7] M.K. Mangoli, and K.Y. Lee, “Optimal real and reactive power control
using linear programming”, Electr.Power Syst. Res, vol.26, pp.1-10,
1993.
[8] C.A. Canizares , A.C.Z.de Souza and V.H. Quintana, “ Comparison of
performance indices for detection of proximity to voltage collapse”, vol.
11, no.3, pp.1441-1450, Aug 1996 .
[9] S.R.Paranjothi ,andK.Anburaja, “Optimal power flow using refined
genetic algorithm”, Electr.PowerCompon.Syst, vol.30, pp.1055-1063,
2002.
[10] D. Devaraj, and B. Yeganarayana, “Genetic algorithm based optimal
power flow for security enhancement”, IEE proc-
Generation.Transmission and. Distribution; 152, 6 November 2005.
[11] A.Berizzi, C. Bovo, M. Merlo, and M. Delfanti, “A ga approach to
compare orpf objective functions including secondary voltage
regulation,” Electric Power Systems Research, vol.84, no.1, pp.187-
194, 2012.
[12] C.-F. Yang, G. G. Lai, C.-H. Lee, C.-T. Su, and G. W. Chang, “Optimal
setting of reactive compensation devices with an improved voltage
stability index for voltage stability enhancement,” International Journal
of Electrical Power and Energy Systems, vol.37, no.1, pp. 50 -57, 2012.
[13] P. Roy, S. Ghoshal, and S. Thakur, “Optimal var control for
improvements in voltage profiles and for real power loss minimization
using biogeography based optimization,” International Journal of
Electrical Power and Energy Systems, vol.43, no.1, pp.830-838, 2012.
[14] B. Venkatesh, G. Sadasivam, and M. Khan, “A new optimal reactive
power scheduling method for loss minimization and voltage stability
margin maximization using successive multi-objective fuzzy lp
technique,” IEEE Transactions on Power Systems, vol.15, no.2, pp.
844-851, may 2000.
[15] W. Yan, S. Lu, and D. Yu, “A novel optimal reactive power dispatch
method based on an improved hybrid evolutionary programming
technique,” IEEE Transactions on Power Systems, vol. 19, no. 2, pp.
913 – 918, may 2004.
[16] W. Yan, F. Liu, C. Chung, and K. Wong, “A hybrid genetic
algorithminterior point method for optimal reactive power flow,” IEEE
Transactions on Power Systems, vol.21, no.3, pp.1163-1169, Aug.
2006.
[17] J. Yu, W. Yan, W. Li, C. Chung, and K. Wong, “An unfixed
piecewiseoptimal reactive power-flow model and its algorithm for acdc
systems,” IEEE Transactions on Power Systems, vol.23, no.1, pp.
170-176, Feb. 2008.
[18] F. Capitanescu, “Assessing reactive power reserves with respect to
operating constraints and voltage stability,” IEEE Transactions on
Power Systems, vol.26, no.4, pp.2224–2234, nov.2011.
[19] Z. Hu, X. Wang, and G. Taylor, “Stochastic optimal reactive power
dispatch: Formulation and solution method,” International Journal of
Electrical Power and Energy Systems, vol.32, no.6, pp.615-621, 2010.
[20] Kargarian, M. Raoofat, and M. Mohammadi, “Probabilistic reactive
power procurement in hybrid electricity markets with uncertain loads,”
Electric Power Systems Research, vol.82, no. , pp. 68-80, 2012.
[21] Li Zhang, Weijun Zhou , Donghui Li, “Global convergence of a
modified Fletcher–Reeves conjugate gradient method with Armijo-type
line search”, Numerische Mathematik, October 2006, vol.104, no.4,
pp.561-572
[22] K. Deb, A. Anand, and D. Joshi, A computationally efficient
evolutionary algorithm for realparameter optimization. Evolutionary
computation, Vol.10, No.4, pp.371-395, 2002.
[23] K. Deb, and M.Thakur, A new crossover operator for real coded genetic
algorithms. Applied Mathematics and Computation, vol.188(1),
pp.895-911, 2007.
[24] Q.H. Wu, Y.J.Cao, and J.Y. Wen. Optimal reactive power dispatch
using an adaptive genetic algorithm. Int. J. Elect. Power Energy Syst.
vol 20. pp.563-569, Aug 1998.
[25] B. Zhao, C. X. Guo, and Y.J. CAO.Multiagent-based particle swarm
optimization approach for optimal reactive power dispatch. IEEE Trans.
Power Syst. Vol.20, no.2, pp.1070-1078, May 2005.
[26] Mahadevan. K, Kannan P. S. “Comprehensive Learning Particle Swarm
Optimization for Reactive Power Dispatch”, Applied Soft Computing,
Vol.10, No.2, pp.641–52, March 2010.
[27] A.H. Khazali, M. Kalantar, “Optimal Reactive Power Dispatch based
on Harmony Search Algorithm”, Electrical Power and Energy Systems,
vol.33, no.3, pp.684-692, March 2011.
[28] S. Sakthivel, M. Gayathri, V. Manimozhi, “A Nature Inspired
Optimization Algorithm for Reactive Power Control in a Power
System”, International Journal of Recent Technology and Engineering
(IJRTE) , vol.2, no.1, pp.29-33, March 2013.