Non-convex security constrained optimal power flow by a new solution method composed of Benders decomposition and special ordered sets

SUMMARYThis paper presents a comprehensive formulation for the security constrained optimal power flow (SCOPF) problem considering valve loading effect, multiple fuel option, and prohibited operating zones of units as well as alternating current network modeling and contingency constraints. Also, th...

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Published inInternational transactions on electrical energy systems Vol. 24; no. 6; pp. 842 - 857
Main Authors Amjady, Nima, Ansari, Mohammad Reza
Format Journal Article
LanguageEnglish
Published Hoboken Blackwell Publishing Ltd 01.06.2014
John Wiley & Sons, Inc
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ISSN2050-7038
2050-7038
DOI10.1002/etep.1742

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Abstract SUMMARYThis paper presents a comprehensive formulation for the security constrained optimal power flow (SCOPF) problem considering valve loading effect, multiple fuel option, and prohibited operating zones of units as well as alternating current network modeling and contingency constraints. Also, the SCOPF formulation includes the integer variables, such as discrete transformer tap settings, in addition to continuous variables, such as generation of units. Thus, the suggested SCOPF model is a mixed integer, nonlinear, non‐convex, and non‐smooth optimization problem. To solve this problem, a new solution method composed of Benders decomposition and special ordered sets is presented. The proposed formulation decomposes the problem into a master problem and a sub‐problem. The master problem relaxes the nonlinear constraints of the model using a convex linear outer approximation based on the concept of special ordered sets, whereas the sub‐problem contains the nonlinear and non‐convex SCOPF formulation with fixed integer and binary variables. To show the effectiveness of the proposed solution method, it is tested on the well‐known test systems and compared with several other recently published solution methods. These comparisons confirm the validity of the developed approach. Copyright © 2013 John Wiley & Sons, Ltd.
AbstractList SUMMARY This paper presents a comprehensive formulation for the security constrained optimal power flow (SCOPF) problem considering valve loading effect, multiple fuel option, and prohibited operating zones of units as well as alternating current network modeling and contingency constraints. Also, the SCOPF formulation includes the integer variables, such as discrete transformer tap settings, in addition to continuous variables, such as generation of units. Thus, the suggested SCOPF model is a mixed integer, nonlinear, non-convex, and non-smooth optimization problem. To solve this problem, a new solution method composed of Benders decomposition and special ordered sets is presented. The proposed formulation decomposes the problem into a master problem and a sub-problem. The master problem relaxes the nonlinear constraints of the model using a convex linear outer approximation based on the concept of special ordered sets, whereas the sub-problem contains the nonlinear and non-convex SCOPF formulation with fixed integer and binary variables. To show the effectiveness of the proposed solution method, it is tested on the well-known test systems and compared with several other recently published solution methods. These comparisons confirm the validity of the developed approach. Copyright © 2013 John Wiley & Sons, Ltd.
SUMMARYThis paper presents a comprehensive formulation for the security constrained optimal power flow (SCOPF) problem considering valve loading effect, multiple fuel option, and prohibited operating zones of units as well as alternating current network modeling and contingency constraints. Also, the SCOPF formulation includes the integer variables, such as discrete transformer tap settings, in addition to continuous variables, such as generation of units. Thus, the suggested SCOPF model is a mixed integer, nonlinear, non‐convex, and non‐smooth optimization problem. To solve this problem, a new solution method composed of Benders decomposition and special ordered sets is presented. The proposed formulation decomposes the problem into a master problem and a sub‐problem. The master problem relaxes the nonlinear constraints of the model using a convex linear outer approximation based on the concept of special ordered sets, whereas the sub‐problem contains the nonlinear and non‐convex SCOPF formulation with fixed integer and binary variables. To show the effectiveness of the proposed solution method, it is tested on the well‐known test systems and compared with several other recently published solution methods. These comparisons confirm the validity of the developed approach. Copyright © 2013 John Wiley & Sons, Ltd.
Author Ansari, Mohammad Reza
Amjady, Nima
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References Abido MA. Optimal power flow using particle swarm optimization. Elec. Power Energy Syst., Oct. 2002; 24(7):563-571.
Chiang CL. Improved genetic algorithm for power economic dispatch of units with valve-point effects and multiple fuels. IEEE Trans. Power Syst., Nov. 2005; 20(4):1690-1699.
Yamin H, Al-Agtash S, Shahidehpour M. Security-constrained optimal generation scheduling for GENCOs. IEEE Trans. Power Syst., Aug. 2004, 19(3):1365-1372.
Thitithamrongchai C, Eua-arporn B. Self-adaptive differential evolution based optimal power flow for units with non-smooth fuel cost functions. Journal of Electrical Systems, June 2007, 3(2):88-99.
Mahdad B, Srairi K, Bouktir T. Optimal power flow for large-scale power system with shunt FACTS using efficient parallel GA. Int. J. Elec. Power Energy Syst., June 2010; 32(5):507-517.
Aoki K, Kanesashi H. A Modified Newton Method For Optimal Power Flow Using Quadratic Approximated Power Flow. Electrical Engineering in Japan, Sept. 1984; 104(5):115-122.
Tang Wj, Li MS, Wu QH, Saunders JR. Bacterial foraging algorithm for optimal power flow in dynamic environments. IEEE Transactions on Circuits and Systems I: Regular Papers, Sept. 2008; 55(8):2433-2442.
Lee FN, Breipohl AM. Reserve constrained economic dispatch with prohibited operating zones. IEEE Trans. Power Syst., 8(1):246-254, Feb. 1993.
Olofsson M, Andersson G, Soder L. Linear programming based optimal power flow using second order sensitivities. IEEE Trans. Power Syst., Aug. 1995, 10(3):1691-1697.
Bouktir T, Slimani L, Mahdad B. Optimal power dispatch for large-scale power system using stochastic search algorithms. Int. J. Power & Energy Syst., 2008; 28(2):118-127.
Capitanescu F, Wehenkel L. A new iterative approach to the corrective security-constrained optimal power flow problem. IEEE Trans. Power Syst., Nov. 2008; 23(4):1533-1541.
Devaraj D, Yegnanarayana B. Genetic-algorithm-based optimal power flow for security enhancement. IEE Proc. -Gener. Transm. Distrib., Nov. 2005; 152(6):899-905.
O˜nate Yumbla PE, Ramirez JM, Coello Coello CA. Optimal power flow subject to security constraints solved with a particle swarm optimizer. IEEE Trans. Power Syst., Feb. 2008; 23(1):33-40.
Capitanescu F, Glavic M, Ernst D, Wehenkel J. Contingency filtering techniques for preventive security-constrained optimal power flow. IEEE Trans. Power Syst., Nov. 2007; 22(4):1690-1697.
Sivasubramani S, Swarup KS. Sequential quadratic programming based differential evolution algorithm for optimal power flow problem. IET Generation, Transmission and Distribution, Nov. 2011; 5(11):1149-1154.
Min W, Shengsong L. A trust region interior point algorithm for optimal power flow problems. Int. J. Elec. Power Energy Syst., May. 2005, 24(4):293-300.
AlRashidi MR, El-Hawary ME. Hybrid particle swarm optimization approach for solving the discrete OPF problem considering the valve loading effects. IEEE Trans. Power Syst., Nov. 2007; 22(4):2030-2038.
Giang ZL . Constrained optimal power flow by mixed-integer particle swarm optimization. Proc. IEEE Power Eng. Soc. General Meeting, San Francisco, CA, 1:243-250, June 2005.
Guan X, Liu WHE, Papalexopoulos AD. Application of a fuzzy set method in an optimal power flow. Elec. Power Syst. Res., July 1995; vol. 34(1):11-18.
Ongsakul W, Tantimaporn T. Optimal power flow by improved evolutionary programming. Elec. Power Comp. Syst., Jan. 2006; 34(1):79-95.
Amorim EA, Hoshimoto SHM, Lima FGM, Mantovani JRS. Multi objective evolutionary algorithm applied to the optimal power flow problem. Latin America Transactions, IEEE (Revista IEEE America Latina), June 2010; 8(3):236-244.
Biskas PN, Ziogos NP, Tellidou A, Zoumas CE, Bakirtzis AG, Petridis V. Comparison of two metaheuristics with mathematical programming methods for the solution of OPF. IEE Proc. Gener. Transm. Distrib., Jan. 2006, 153(1):16-24.
Roa-Sepulveda CA, Pavez-Lazo BJ. A solution to the optimal power flow using simulated annealing. Elec. Power Energy Syst., Jan 2003; 25(1):47-57.
Amjady N, Sharifzadeh H. Security constrained optimal power flow considering detailed generator model by a new robust differential evolution algorithm. Elec. Power Syst. Res., Feb. 2011; 81(2):740-749.
Capitanescu F, Martinez Ramos JL, Panciatici P, Kirschen D, Marano Marcolini A, Platbrood L, Wehenkel L. State-of-the-art, challenges, and future trends in security constrained optimal power flow. Elec. Power Syst. Res., Aug. 2011; 81(8):1731-1741.
Amjady N, Nasiri-Rad H. Non-convex economic dispatch with AC constraints by a new real coded genetic algorithm. IEEE Trans. Power Syst., Aug. 2009; 24(3):1489-1502.
Condren J, Gedra TW. Expected-security-cost optimal power flow with small-signal stability constraints. IEEE Trans. Power Syst., Nov. 2006; 21(4):1736-1743.
Amjady N, Fatemi H, Zareipour H. Solution of optimal power flow subject to security constraints by a New improved bacterial foraging method. IEEE Trans. Power Syst., Aug. 2012; 27(3):1311-1323.
Abido MA. Optimal power flow using tabu search algorithm. Elec. Power Comp. Syst., May. 2002; 30(5):469-83.
Varadarajan M, Swarup KS. Network loss minimization with voltage security using differential evolution. Elec. Power Syst. Res., May. 2008; 78(5):815-823.
Sun Y, Xinlin Y, Wang HF. Approach for optimal power flow with transient stability constraints. IEE Proc. Gener. Transm. Distrib., Jan. 2004; 151(1):8-18.
Todorovski M, Rajicic D. An initialization procedure in solving optimal power flow by genetic algorithm. IEEE Trans. Power Syst., May 2006; 21(2):480-487.
Capitanescu F, Wehenkel L. Improving the statement of the corrective security-constrained optimal power-flow problem. IEEE Trans. Power Syst., May. 2007; 22(2):887-889.
Bakirtzis AG, Biskas PN, Zoumas CE, Petridis V. Optimal power flow by enhanced genetic algorithm. IEEE Trans. Power Syst., May. 2002; 17(2):229-236.
Sayah S, Zehar K. Modified differential evolution algorithm for optimal power flow with non-smooth cost functions. Energy Conversion and Management, Nov. 2008; 49(11):3036-3042.
Gaing ZL, Chang RF. Security-constrained optimal power flow by mixed-integer genetic algorithm with arithmetic operators. IEEE Power Eng. Soc. General Meeting, Oct. 2006,1-8.
AlRashidi MR, El-Hawary ME. Applications of computational intelligence techniques for solving the revived optimal power flow problem. Elec. Power Syst. Res., Apr. 2009; 79(4):694-702.
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2006; 153
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References_xml – reference: Sun Y, Xinlin Y, Wang HF. Approach for optimal power flow with transient stability constraints. IEE Proc. Gener. Transm. Distrib., Jan. 2004; 151(1):8-18.
– reference: Capitanescu F, Wehenkel L. A new iterative approach to the corrective security-constrained optimal power flow problem. IEEE Trans. Power Syst., Nov. 2008; 23(4):1533-1541.
– reference: Roa-Sepulveda CA, Pavez-Lazo BJ. A solution to the optimal power flow using simulated annealing. Elec. Power Energy Syst., Jan 2003; 25(1):47-57.
– reference: Olofsson M, Andersson G, Soder L. Linear programming based optimal power flow using second order sensitivities. IEEE Trans. Power Syst., Aug. 1995, 10(3):1691-1697.
– reference: Bakirtzis AG, Biskas PN, Zoumas CE, Petridis V. Optimal power flow by enhanced genetic algorithm. IEEE Trans. Power Syst., May. 2002; 17(2):229-236.
– reference: Biskas PN, Ziogos NP, Tellidou A, Zoumas CE, Bakirtzis AG, Petridis V. Comparison of two metaheuristics with mathematical programming methods for the solution of OPF. IEE Proc. Gener. Transm. Distrib., Jan. 2006, 153(1):16-24.
– reference: Capitanescu F, Wehenkel L. Improving the statement of the corrective security-constrained optimal power-flow problem. IEEE Trans. Power Syst., May. 2007; 22(2):887-889.
– reference: Amjady N, Nasiri-Rad H. Non-convex economic dispatch with AC constraints by a new real coded genetic algorithm. IEEE Trans. Power Syst., Aug. 2009; 24(3):1489-1502.
– reference: Gaing ZL, Chang RF. Security-constrained optimal power flow by mixed-integer genetic algorithm with arithmetic operators. IEEE Power Eng. Soc. General Meeting, Oct. 2006,1-8.
– reference: Min W, Shengsong L. A trust region interior point algorithm for optimal power flow problems. Int. J. Elec. Power Energy Syst., May. 2005, 24(4):293-300.
– reference: Capitanescu F, Martinez Ramos JL, Panciatici P, Kirschen D, Marano Marcolini A, Platbrood L, Wehenkel L. State-of-the-art, challenges, and future trends in security constrained optimal power flow. Elec. Power Syst. Res., Aug. 2011; 81(8):1731-1741.
– reference: Giang ZL . Constrained optimal power flow by mixed-integer particle swarm optimization. Proc. IEEE Power Eng. Soc. General Meeting, San Francisco, CA, 1:243-250, June 2005.
– reference: AlRashidi MR, El-Hawary ME. Hybrid particle swarm optimization approach for solving the discrete OPF problem considering the valve loading effects. IEEE Trans. Power Syst., Nov. 2007; 22(4):2030-2038.
– reference: Devaraj D, Yegnanarayana B. Genetic-algorithm-based optimal power flow for security enhancement. IEE Proc. -Gener. Transm. Distrib., Nov. 2005; 152(6):899-905.
– reference: Tang Wj, Li MS, Wu QH, Saunders JR. Bacterial foraging algorithm for optimal power flow in dynamic environments. IEEE Transactions on Circuits and Systems I: Regular Papers, Sept. 2008; 55(8):2433-2442.
– reference: Lee FN, Breipohl AM. Reserve constrained economic dispatch with prohibited operating zones. IEEE Trans. Power Syst., 8(1):246-254, Feb. 1993.
– reference: Capitanescu F, Glavic M, Ernst D, Wehenkel J. Contingency filtering techniques for preventive security-constrained optimal power flow. IEEE Trans. Power Syst., Nov. 2007; 22(4):1690-1697.
– reference: Varadarajan M, Swarup KS. Network loss minimization with voltage security using differential evolution. Elec. Power Syst. Res., May. 2008; 78(5):815-823.
– reference: AlRashidi MR, El-Hawary ME. Applications of computational intelligence techniques for solving the revived optimal power flow problem. Elec. Power Syst. Res., Apr. 2009; 79(4):694-702.
– reference: Amjady N, Sharifzadeh H. Security constrained optimal power flow considering detailed generator model by a new robust differential evolution algorithm. Elec. Power Syst. Res., Feb. 2011; 81(2):740-749.
– reference: Chiang CL. Improved genetic algorithm for power economic dispatch of units with valve-point effects and multiple fuels. IEEE Trans. Power Syst., Nov. 2005; 20(4):1690-1699.
– reference: Todorovski M, Rajicic D. An initialization procedure in solving optimal power flow by genetic algorithm. IEEE Trans. Power Syst., May 2006; 21(2):480-487.
– reference: Bouktir T, Slimani L, Mahdad B. Optimal power dispatch for large-scale power system using stochastic search algorithms. Int. J. Power & Energy Syst., 2008; 28(2):118-127.
– reference: Yamin H, Al-Agtash S, Shahidehpour M. Security-constrained optimal generation scheduling for GENCOs. IEEE Trans. Power Syst., Aug. 2004, 19(3):1365-1372.
– reference: O˜nate Yumbla PE, Ramirez JM, Coello Coello CA. Optimal power flow subject to security constraints solved with a particle swarm optimizer. IEEE Trans. Power Syst., Feb. 2008; 23(1):33-40.
– reference: Guan X, Liu WHE, Papalexopoulos AD. Application of a fuzzy set method in an optimal power flow. Elec. Power Syst. Res., July 1995; vol. 34(1):11-18.
– reference: Amjady N, Fatemi H, Zareipour H. Solution of optimal power flow subject to security constraints by a New improved bacterial foraging method. IEEE Trans. Power Syst., Aug. 2012; 27(3):1311-1323.
– reference: Condren J, Gedra TW. Expected-security-cost optimal power flow with small-signal stability constraints. IEEE Trans. Power Syst., Nov. 2006; 21(4):1736-1743.
– reference: Sayah S, Zehar K. Modified differential evolution algorithm for optimal power flow with non-smooth cost functions. Energy Conversion and Management, Nov. 2008; 49(11):3036-3042.
– reference: Sivasubramani S, Swarup KS. Sequential quadratic programming based differential evolution algorithm for optimal power flow problem. IET Generation, Transmission and Distribution, Nov. 2011; 5(11):1149-1154.
– reference: Abido MA. Optimal power flow using particle swarm optimization. Elec. Power Energy Syst., Oct. 2002; 24(7):563-571.
– reference: Abido MA. Optimal power flow using tabu search algorithm. Elec. Power Comp. Syst., May. 2002; 30(5):469-83.
– reference: Thitithamrongchai C, Eua-arporn B. Self-adaptive differential evolution based optimal power flow for units with non-smooth fuel cost functions. Journal of Electrical Systems, June 2007, 3(2):88-99.
– reference: Amorim EA, Hoshimoto SHM, Lima FGM, Mantovani JRS. Multi objective evolutionary algorithm applied to the optimal power flow problem. Latin America Transactions, IEEE (Revista IEEE America Latina), June 2010; 8(3):236-244.
– reference: Aoki K, Kanesashi H. A Modified Newton Method For Optimal Power Flow Using Quadratic Approximated Power Flow. Electrical Engineering in Japan, Sept. 1984; 104(5):115-122.
– reference: Ongsakul W, Tantimaporn T. Optimal power flow by improved evolutionary programming. Elec. Power Comp. Syst., Jan. 2006; 34(1):79-95.
– reference: Mahdad B, Srairi K, Bouktir T. Optimal power flow for large-scale power system with shunt FACTS using efficient parallel GA. Int. J. Elec. Power Energy Syst., June 2010; 32(5):507-517.
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Snippet SUMMARYThis paper presents a comprehensive formulation for the security constrained optimal power flow (SCOPF) problem considering valve loading effect,...
SUMMARY This paper presents a comprehensive formulation for the security constrained optimal power flow (SCOPF) problem considering valve loading effect,...
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wiley
istex
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StartPage 842
SubjectTerms Benders decomposition
Decomposition
mixed integer
non-convex
nonlinear
SCOPF
special order set
Title Non-convex security constrained optimal power flow by a new solution method composed of Benders decomposition and special ordered sets
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https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fetep.1742
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Volume 24
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