2014, 4(4): 341-351. doi: 10.3934/naco.2014.4.341

Essential issues on solving optimal power flow problems using soft-computing

1. 

Department of Electrical and Computer Engineering, Curtin University, Perth, Australia, Australia

2. 

Business School, Central South University, Changsha, China

3. 

Department of Mathematics and Statistics, Curtin University, Perth, Australia

Received  July 2014 Revised  December 2014 Published  December 2014

Optimal power flow (OPF) problems are important optimization problems in power systems which aim to minimize the operation cost of generators so that the load demand can be met and the loadings are within the feasible operating regions of the generators. This brief paper emphasizes two essential issues related to solving the OPF problems and which are rarely addressed in recent research into power systems: 1) the necessity to validate operational constraints on OPF, which determine the feasibility of power systems designed for the OPF problems; and 2) and the necessity to develop conventional methods for solving OPF problems which can be more effective than the commonly-used heuristic methods.
Citation: Kit Yan Chan, Changjun Yu, Kok Lay Teo, Sven Nordholm. Essential issues on solving optimal power flow problems using soft-computing. Numerical Algebra, Control & Optimization, 2014, 4 (4) : 341-351. doi: 10.3934/naco.2014.4.341
References:
[1]

A. G. Bakirtzis, P. N. Biskas, C. E. Zoumas and V. Petridis, Optimal power flow by enhanced genetic algorithm,, IEEE Transactions on Power Systems, 17 (2002), 229.

[2]

K. T. Chatuervedi, Manjaree Pandit and L. Srivastava, Self-organizing hierarchical particle swarm optimization for nonconvex economic dispatch,, IEEE Transactions on Power Systems, 23 (2008), 1079.

[3]

C. L. Chiang, Improved genetic algorithm for power economic dispatch of units with valve-point effects and multiple fuels,, IEEE Transactions on Power Systems, 24 (2005), 1690.

[4]

M. Clerc and J. Kennedy, The particle swarm explosion, stability, and convergence in a multidimensional complex space,, IEEE Transactions on Evolutionary Computations, 6 (2002), 58.

[5]

D. Devaraj and B. Yegnanarayana, Genetic-algorithm-based optimal power flow for security enhancement,, IEE Proceedings: Generation, 152 (2005), 899.

[6]

R. Eberhart and J. Kennedy, A new optimizer using particle swarm theory,, in Proceedings 6th International Symposium on Micro Machine and Human Science, (1995), 39.

[7]

A. A. A. Esmin, G. L. Torres and A. C. Zamhroni, A hybrid particle swarm optimization applied to loss power minimization,, IEEE Transactions on Power Systems, 20 (2005), 859.

[8]

L. K. Kirchmayer, Economic Operation of Power Systems,, Wiley, (1958).

[9]

K. F. Man, K. S. Tang and S. Kwong, Genetic algorithm: concepts and applications,, IEEE Transactions on Industrial Electronics, 43 (1996), 519.

[10]

K. Meng, H. G. Wang, Z. Y. Dong and K. P. Wong, Quantum inspired particle swarm optimization for valve point economic load dispatch,, IEEE Transactions on Power Systems, 25 (2010), 215.

[11]

N. Mo, Z. Y. Zou, K. W. Chan and G. T. Y. Pong, Transient stability constrained optimal power flow using particle swarm optimization,, IET Proceedings Generation, 1 (2007), 476.

[12]

S. R. Paranjothi and K. Anburaja, Optimal power flow using refined genetic algorithm,, Electric Power Components and Systems, 30 (2002), 1055.

[13]

J. Pilgrim, F. Li and R. K. Aggarwal, Genetic algorithms for optimal reactive power compensation on the national grid system,, Proceedings of IEEE Power Engineering Society Transmission and Distribution Conference 2000, (2000), 524.

[14]

M. J. D. Powell, A fast algorithm for nonlinearly constrained optimization calculations,, Numerical Analysis, 630 (1977), 144.

[15]

M. J. D. Powell, Algorithms for nonlinear constraints that use lagrangian functions,, Mathematical Programming, 14 (1978), 224.

[16]

M. J. D. Powell, The convergence of variable metric methods for nonlinearly constrained optimization calculations,, In Proceedings of Nonlinear Programming 3 (1978), 3 (1978), 27.

[17]

C. R. Reeves, Genetic algorithms and neighbourhood search,, Evolutionary Computing: AISB Workshop, (1994), 115.

[18]

W. Y. Sun and Y. X. Yuan, Optimization Theory and Methods: Nonlinear Programming,, Springer, (2006).

[19]

R. J. M. Vaessens, E. H. L. Aarts and J. K. Lenstra, A local search template,, Proceedings of parallel problem-solving from nature, 2 (1992), 65.

[20]

K. L. Teo, C. J. Goh and K. H. Wong, A Unified Computational Approach to Optimal Control Problems,, New York: Longman Scientific & Technical, (1991).

[21]

M. Todorovski and D. Rajicic, An initialization procedure in solving optimal power flow by genetic algorithm,, IEEE Transactions on Power Systems, 21 (2006), 480.

[22]

R. J. M. Vaessens, E. H. L. Aarts and J. K. Lenstra, A local search template,, Proceedings of Parallel Problem-Solving from Nature, 2 (1992), 65.

[23]

A. J. Wood and B. F. Wollenberg, Power Generation, Operation, and Control,, New York, (1996).

[24]

J. Yuryevich and K. P. Wong, Evolutionary programming based optimal power flow algorithm,, IEEE Transactions on Power Systems, 14 (1999), 1245.

[25]

C. J. Yu, K. L. Teo, L. S. Zhang and Y. Q. Bai, On a refinement of the convergence analysis for the new exact penalty function method for continuous inequality constrained optimization problem,, Journal of Industrial Management and Optimization, 8 (2012), 485. doi: 10.3934/jimo.2012.8.485.

[26]

C. J. Yu, K. L. Teo, L. S. Zhang and Y. Q. Bai, A new exact penalty function method for continuous inequality constrained optimization problems,, Journal of Industrial Management and Optimization, 6 (2010), 895. doi: 10.3934/jimo.2010.6.895.

show all references

References:
[1]

A. G. Bakirtzis, P. N. Biskas, C. E. Zoumas and V. Petridis, Optimal power flow by enhanced genetic algorithm,, IEEE Transactions on Power Systems, 17 (2002), 229.

[2]

K. T. Chatuervedi, Manjaree Pandit and L. Srivastava, Self-organizing hierarchical particle swarm optimization for nonconvex economic dispatch,, IEEE Transactions on Power Systems, 23 (2008), 1079.

[3]

C. L. Chiang, Improved genetic algorithm for power economic dispatch of units with valve-point effects and multiple fuels,, IEEE Transactions on Power Systems, 24 (2005), 1690.

[4]

M. Clerc and J. Kennedy, The particle swarm explosion, stability, and convergence in a multidimensional complex space,, IEEE Transactions on Evolutionary Computations, 6 (2002), 58.

[5]

D. Devaraj and B. Yegnanarayana, Genetic-algorithm-based optimal power flow for security enhancement,, IEE Proceedings: Generation, 152 (2005), 899.

[6]

R. Eberhart and J. Kennedy, A new optimizer using particle swarm theory,, in Proceedings 6th International Symposium on Micro Machine and Human Science, (1995), 39.

[7]

A. A. A. Esmin, G. L. Torres and A. C. Zamhroni, A hybrid particle swarm optimization applied to loss power minimization,, IEEE Transactions on Power Systems, 20 (2005), 859.

[8]

L. K. Kirchmayer, Economic Operation of Power Systems,, Wiley, (1958).

[9]

K. F. Man, K. S. Tang and S. Kwong, Genetic algorithm: concepts and applications,, IEEE Transactions on Industrial Electronics, 43 (1996), 519.

[10]

K. Meng, H. G. Wang, Z. Y. Dong and K. P. Wong, Quantum inspired particle swarm optimization for valve point economic load dispatch,, IEEE Transactions on Power Systems, 25 (2010), 215.

[11]

N. Mo, Z. Y. Zou, K. W. Chan and G. T. Y. Pong, Transient stability constrained optimal power flow using particle swarm optimization,, IET Proceedings Generation, 1 (2007), 476.

[12]

S. R. Paranjothi and K. Anburaja, Optimal power flow using refined genetic algorithm,, Electric Power Components and Systems, 30 (2002), 1055.

[13]

J. Pilgrim, F. Li and R. K. Aggarwal, Genetic algorithms for optimal reactive power compensation on the national grid system,, Proceedings of IEEE Power Engineering Society Transmission and Distribution Conference 2000, (2000), 524.

[14]

M. J. D. Powell, A fast algorithm for nonlinearly constrained optimization calculations,, Numerical Analysis, 630 (1977), 144.

[15]

M. J. D. Powell, Algorithms for nonlinear constraints that use lagrangian functions,, Mathematical Programming, 14 (1978), 224.

[16]

M. J. D. Powell, The convergence of variable metric methods for nonlinearly constrained optimization calculations,, In Proceedings of Nonlinear Programming 3 (1978), 3 (1978), 27.

[17]

C. R. Reeves, Genetic algorithms and neighbourhood search,, Evolutionary Computing: AISB Workshop, (1994), 115.

[18]

W. Y. Sun and Y. X. Yuan, Optimization Theory and Methods: Nonlinear Programming,, Springer, (2006).

[19]

R. J. M. Vaessens, E. H. L. Aarts and J. K. Lenstra, A local search template,, Proceedings of parallel problem-solving from nature, 2 (1992), 65.

[20]

K. L. Teo, C. J. Goh and K. H. Wong, A Unified Computational Approach to Optimal Control Problems,, New York: Longman Scientific & Technical, (1991).

[21]

M. Todorovski and D. Rajicic, An initialization procedure in solving optimal power flow by genetic algorithm,, IEEE Transactions on Power Systems, 21 (2006), 480.

[22]

R. J. M. Vaessens, E. H. L. Aarts and J. K. Lenstra, A local search template,, Proceedings of Parallel Problem-Solving from Nature, 2 (1992), 65.

[23]

A. J. Wood and B. F. Wollenberg, Power Generation, Operation, and Control,, New York, (1996).

[24]

J. Yuryevich and K. P. Wong, Evolutionary programming based optimal power flow algorithm,, IEEE Transactions on Power Systems, 14 (1999), 1245.

[25]

C. J. Yu, K. L. Teo, L. S. Zhang and Y. Q. Bai, On a refinement of the convergence analysis for the new exact penalty function method for continuous inequality constrained optimization problem,, Journal of Industrial Management and Optimization, 8 (2012), 485. doi: 10.3934/jimo.2012.8.485.

[26]

C. J. Yu, K. L. Teo, L. S. Zhang and Y. Q. Bai, A new exact penalty function method for continuous inequality constrained optimization problems,, Journal of Industrial Management and Optimization, 6 (2010), 895. doi: 10.3934/jimo.2010.6.895.

[1]

Md. Abul Kalam Azad, Edite M.G.P. Fernandes. A modified differential evolution based solution technique for economic dispatch problems. Journal of Industrial & Management Optimization, 2012, 8 (4) : 1017-1038. doi: 10.3934/jimo.2012.8.1017

[2]

Junyuan Lin, Timothy A. Lucas. A particle swarm optimization model of emergency airplane evacuations with emotion. Networks & Heterogeneous Media, 2015, 10 (3) : 631-646. doi: 10.3934/nhm.2015.10.631

[3]

Qifeng Cheng, Xue Han, Tingting Zhao, V S Sarma Yadavalli. Improved particle swarm optimization and neighborhood field optimization by introducing the re-sampling step of particle filter. Journal of Industrial & Management Optimization, 2017, 13 (5) : 1-22. doi: 10.3934/jimo.2018038

[4]

Tao Zhang, Yue-Jie Zhang, Qipeng P. Zheng, P. M. Pardalos. A hybrid particle swarm optimization and tabu search algorithm for order planning problems of steel factories based on the Make-To-Stock and Make-To-Order management architecture. Journal of Industrial & Management Optimization, 2011, 7 (1) : 31-51. doi: 10.3934/jimo.2011.7.31

[5]

Mostafa Abouei Ardakan, A. Kourank Beheshti, S. Hamid Mirmohammadi, Hamed Davari Ardakani. A hybrid meta-heuristic algorithm to minimize the number of tardy jobs in a dynamic two-machine flow shop problem. Numerical Algebra, Control & Optimization, 2017, 7 (4) : 465-480. doi: 10.3934/naco.2017029

[6]

Ning Lu, Ying Liu. Application of support vector machine model in wind power prediction based on particle swarm optimization. Discrete & Continuous Dynamical Systems - S, 2015, 8 (6) : 1267-1276. doi: 10.3934/dcdss.2015.8.1267

[7]

Piermarco Cannarsa, Hélène Frankowska, Elsa M. Marchini. On Bolza optimal control problems with constraints. Discrete & Continuous Dynamical Systems - B, 2009, 11 (3) : 629-653. doi: 10.3934/dcdsb.2009.11.629

[8]

Stanisław Migórski. A note on optimal control problem for a hemivariational inequality modeling fluid flow. Conference Publications, 2013, 2013 (special) : 545-554. doi: 10.3934/proc.2013.2013.545

[9]

Li-Fang Dai, Mao-Lin Liang, Wei-Yuan Ma. Optimization problems on the rank of the solution to left and right inverse eigenvalue problem. Journal of Industrial & Management Optimization, 2015, 11 (1) : 171-183. doi: 10.3934/jimo.2015.11.171

[10]

Zhong Wan, Chaoming Hu, Zhanlu Yang. A spectral PRP conjugate gradient methods for nonconvex optimization problem based on modified line search. Discrete & Continuous Dynamical Systems - B, 2011, 16 (4) : 1157-1169. doi: 10.3934/dcdsb.2011.16.1157

[11]

Ming-Jong Yao, Shih-Chieh Chen, Yu-Jen Chang. A common cycle approach for solving the economic lot and inspection scheduling problem. Journal of Industrial & Management Optimization, 2012, 8 (1) : 141-162. doi: 10.3934/jimo.2012.8.141

[12]

Yu-Jen Chang, Ming-Jong Yao. New heuristics for solving the economic lot scheduling problem with reworks. Journal of Industrial & Management Optimization, 2011, 7 (1) : 229-251. doi: 10.3934/jimo.2011.7.229

[13]

Jie Sun. On methods for solving nonlinear semidefinite optimization problems. Numerical Algebra, Control & Optimization, 2011, 1 (1) : 1-14. doi: 10.3934/naco.2011.1.1

[14]

Georg Vossen, Torsten Hermanns. On an optimal control problem in laser cutting with mixed finite-/infinite-dimensional constraints. Journal of Industrial & Management Optimization, 2014, 10 (2) : 503-519. doi: 10.3934/jimo.2014.10.503

[15]

Maria do Rosário de Pinho, Ilya Shvartsman. Lipschitz continuity of optimal control and Lagrange multipliers in a problem with mixed and pure state constraints. Discrete & Continuous Dynamical Systems - A, 2011, 29 (2) : 505-522. doi: 10.3934/dcds.2011.29.505

[16]

Hee-Dae Kwon, Jeehyun Lee, Sung-Dae Yang. Eigenseries solutions to optimal control problem and controllability problems on hyperbolic PDEs. Discrete & Continuous Dynamical Systems - B, 2010, 13 (2) : 305-325. doi: 10.3934/dcdsb.2010.13.305

[17]

Ming-Yong Lai, Chang-Shi Liu, Xiao-Jiao Tong. A two-stage hybrid meta-heuristic for pickup and delivery vehicle routing problem with time windows. Journal of Industrial & Management Optimization, 2010, 6 (2) : 435-451. doi: 10.3934/jimo.2010.6.435

[18]

Xiangyu Gao, Yong Sun. A new heuristic algorithm for laser antimissile strategy optimization. Journal of Industrial & Management Optimization, 2012, 8 (2) : 457-468. doi: 10.3934/jimo.2012.8.457

[19]

Barbara Kaltenbacher, Gunther Peichl. The shape derivative for an optimization problem in lithotripsy. Evolution Equations & Control Theory, 2016, 5 (3) : 399-430. doi: 10.3934/eect.2016011

[20]

Miriam Kiessling, Sascha Kurz, Jörg Rambau. The integrated size and price optimization problem. Numerical Algebra, Control & Optimization, 2012, 2 (4) : 669-693. doi: 10.3934/naco.2012.2.669

 Impact Factor: 

Metrics

  • PDF downloads (0)
  • HTML views (0)
  • Cited by (0)

[Back to Top]