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Research Article

Hybrid Dragonfly and Pattern Search Algorithm Applied to Dynamic Economic Dispatch Problem

Author(s): Arun Kumar Sahoo*, Tapas Kumar Panigrahi, Gopal Krishna Nayak and Aurobinda Behera

Volume 15, Issue 3, 2022

Published on: 26 August, 2020

Article ID: e180322185346 Pages: 14

DOI: 10.2174/2666255813999200826161924

Price: $65

Abstract

Background: In this paper, a novel hybridisation of the dragonfly algorithm (DFA) with the pattern search (PS) algorithm is applied to the dynamic economic dispatch (DED) problem. The DED problem is non-convex, non-linear, and non-smooth and considering practical constraints such as the loading effect of the valve point and ramp rate limits. The conventional DFA is stuck in the local optima and converges prematurely.

Introduction: The characteristics of the optimality of the electric power system are dependent on reliability and high economy. Economic dispatch (ED) significantly contributes in deriving the optimal solutions for the operation of a power system. ED aims to generate electric power at the optimum cost among all generating units in order to satisfy the load demand considering all practical and operational constraints. Practical constraints, such as the effect of steam valves, the dynamic behaviour of ramp rate limits, losses due to transmission of power, and prohibited operating zones, convert the linear and convex problem to a non-convex and non-linear problem.

Method: Planning and scheduling of output electric power from committed generating units to fulfill the load demand for a scheduled period are termed as DED. The practical generators of thermal power experience the effect of steam valve, real-time ramp rate limit, and technical constraints. DED satisfies all practical, technical, and operational constraints. The DFA was a newly proposed method taking the inspiration of the behaviour of dragonflies for hunting and migrating towards food. The random movement of dragonfly clusters depicts their static characteristics for exploring in the local search space for exploitation competencies, whereas the dynamic behaviour of swarms is used for exploring the global search space by moving in a single direction for a long distance.

Result: The efficiency of the proposed method is validated for six well-known benchmark functions. The hybrid technique is compared with the conventional DFA. The proposed hybrid technique combining of the DFA and PS algorithm is also applied for four different test systems with diverse generating units. The proposed technique shows better efficiency for the optimum cost as compared to other recently applied techniques.

Conclusion: To overcome difficulties, a PS method is hybridised with the original DFA. The application of the proposed technique improves the capability of search and convergence property The validation of the proposed method by applying to the DED problem shows its effectiveness for generation scheduling and estimating.

Keywords: Dynamic Economic Dispatch (DED), Dragonfly Algorithm (DFA), Pattern Search Algorithm (PS), Hybrid Dragon fly algorithm with pattern search algorithm (hDFA-PS), Ramprate limits, Economic Dispatch (ED)

Graphical Abstract

[1]
J.S. Dhillon, and D.P. Kothari, Power System Optimization., Preintce Hall of India Private Limited, 2010.
[2]
D.W. Ross, and S. Kim, "Dynamic economic dispatch of generation", IEEE Trans. Power Apparatus Syst, vol. 6, pp. 2060-2068, Nov 1980.
[http://dx.doi.org/10.1109/TPAS.1980.319847]
[3]
K.S. Hindi, and M.R. Ab Ghani, "Dynamic economic dispatch for large scale power systems: A Lagrangian relaxation approach", Int. J. Electr. Power Energy Syst., vol. 13, no. 1, pp. 51-56, 1991.
[http://dx.doi.org/10.1016/0142-0615(91)90018-Q]
[4]
R.A. Jabr, A.H. Coonick, and B.J. Cory, "A homogeneous linear programming algorithm for the security constrained economic dispatch problem", IEEE Trans. Power Syst., vol. 15, no. 3, pp. 930-936, 2000.
[http://dx.doi.org/10.1109/59.871715]
[5]
C.L. Chen, "Non-convex economic dispatch a direct search approach", Energy Convers. Manage., vol. 48, no. 1, pp. 219-225, 2007.
[http://dx.doi.org/10.1016/j.enconman.2006.04.010]
[6]
J.C. Lee, W.M. Lin, G.C. Liao, and T.P. Tsao, "Quantum genetic algorithm for dynamic economic dispatch with valve-point effects and including wind power system", Int. J. Electr. Power Energy Syst., vol. 33, no. 2, pp. 189-197, Feb 2011.
[http://dx.doi.org/10.1016/j.ijepes.2010.08.014]
[7]
R. Balamurugan, and S. Subramanian, "Differential evolution-based dynamic economic dispatch of generating units with valve-point effects", Electr. Power Compon. Syst., vol. 36, no. 8, pp. 828-843, June 2008.
[http://dx.doi.org/10.1080/15325000801911427]
[8]
R.J. Hemparuva, S.P. Simon, S. Kinattingal, and S.R. Panugothu, "Gravitational search algorithm-based dynamic economic dispatch by estimating transmission system losses using A-loss coefficients", Turk. J. Electr. Eng. Comput. Sci., vol. 24, no. 5, pp. 3769-3781, June 2016.
[http://dx.doi.org/10.3906/elk-1412-152]
[9]
L. Han, C.E. Romero, and Z. Yao, "Economic dispatch optimization algorithm based on particle diffusion", Energy Convers. Manage., vol. 105, pp. 1251-1260, Nov 2015.
[http://dx.doi.org/10.1016/j.enconman.2015.08.071]
[10]
V.R. Pandi, and B.K. Panigrahi, "Dynamic economic load dispatch using hybrid swarm intelligence based harmony search algorithm", Expert Syst. Appl., vol. 38, no. 7, pp. 8509-8514, July 2011.
[http://dx.doi.org/10.1016/j.eswa.2011.01.050]
[11]
S. Hemamalini, and P.S. Sishaj, "Dynamic economic dispatch using artificial bee colony algorithm for units with valve‐point effect", Eur. Trans. Electr. Power, vol. 21, no. 1, pp. 70-81, Jan 2011.
[http://dx.doi.org/10.1002/etep.413]
[12]
B. Mandal, P.K. Roy, and S. Mandal, "Economic load dispatch using krill herd algorithm", Int. J. Electr. Power Energy Syst., vol. 57, pp. 1-10, May 2014.
[http://dx.doi.org/10.1016/j.ijepes.2013.11.016]
[13]
D.N. Vo, P. Schegner, and W. Ongsakul, "Cuckoo search algorithm for non-convex economic dispatch", IET Gener. Transm. Distrib., vol. 7, no. 6, pp. 645-654, June 2013.
[http://dx.doi.org/10.1049/iet-gtd.2012.0142]
[14]
K. Bhattacharjee, A. Bhattacharya, and S. Halder, "Chemical reaction optimisation for different economic dispatch problems", IET Gener. Transm. Distrib., vol. 8, no. 3, pp. 530-541, Mar 2013.
[15]
A. Bhattacharya, and P.K. Chattopadhyay, "Biogeography-based optimization for different economic load dispatch problems", IEEE Trans. Power Syst., vol. 25, no. 2, pp. 1064-1077, Dec 2009.
[http://dx.doi.org/10.1109/TPWRS.2009.2034525]
[16]
M. Basu, "Artificial immune system for dynamic economic dispatch", Int. J. Electr. Power Energy Syst., vol. 33, no. 1, pp. 131-136, Jan 2011.
[http://dx.doi.org/10.1016/j.ijepes.2010.06.019]
[17]
P. Lu, J. Zhou, H. Zhang, R. Zhang, and C. Wang, "Chaotic differential bee colony optimization algorithm for dynamic economic dispatch problem with valve-point effects", Int. J. Electr. Power Energy Syst., vol. 62, pp. 130-143, Nov 2014.
[http://dx.doi.org/10.1016/j.ijepes.2014.04.028]
[18]
H. Liu, "The economic dispatch of wind integrated power system based on an improved differential evolution algorithm", Recent Adv. Electr. Electron. Eng. (Former. Recent Pat. Electr. Electron. Eng.), vol. 13, no. 3, pp. 384-395, May 2020.
[19]
E.E. Elattar, "A hybrid genetic algorithm and bacterial foraging approach for dynamic economic dispatch problem", Int. J. Electr. Power Energy Syst., vol. 69, pp. 18-26, July 2015.
[http://dx.doi.org/10.1016/j.ijepes.2014.12.091]
[20]
J.K. Pattanaik, M. Basu, and D.P. Dash, "Improved real coded genetic algorithm for dynamic economic dispatch", J. Electr. Syst. Inf. Technol., vol. 5, no. 3, pp. 349-362, Dec 2018.
[http://dx.doi.org/10.1016/j.jesit.2018.03.002]
[21]
Y. Zhang, D.W. Gong, N. Geng, and X.Y. Sun, "Hybrid bare-bones PSO for dynamic economic dispatch with valve-point effects", Appl. Soft Comput., vol. 18, pp. 248-260, May 2014.
[http://dx.doi.org/10.1016/j.asoc.2014.01.035]
[22]
T.A. Victoire, and A.E. Jeyakumar, "A modified hybrid EP–SQP approach for dynamic dispatch with valve-point effect", Int. J. Electr. Power Energy Syst., vol. 27, no. 8, pp. 594-601, Oct 2005.
[http://dx.doi.org/10.1016/j.ijepes.2005.06.006]
[23]
T. Niknam, and F. Golestaneh, "Enhanced adaptive particle swarm optimisation algorithm for dynamic economic dispatch of units considering valve-point effects and ramp rates", IET Gener. Transm. Distrib., vol. 6, no. 5, pp. 424-435, May 2012.
[http://dx.doi.org/10.1049/iet-gtd.2011.0219]
[24]
Q. Niu, H. Zhang, K. Li, and G.W. Irwin, "An efficient harmony search with new pitch adjustment for dynamic economic dispatch", Energy, vol. 65, pp. 25-43, Feb 2014.
[http://dx.doi.org/10.1016/j.energy.2013.10.085]
[25]
B.K. Panigrahi, V.R. Pandi, and S. Das, "Adaptive particle swarm optimization approach for static and dynamic economic load dispatch", Energy Convers. Manage., vol. 49, no. 6, pp. 1407-1415, June 2008.
[http://dx.doi.org/10.1016/j.enconman.2007.12.023]
[26]
S. Mirjalili, "Dragonfly algorithm: A new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems", Neural Comput. Appl., vol. 27, no. 4, pp. 1053-1073, May 2016.
[http://dx.doi.org/10.1007/s00521-015-1920-1]
[27]
Y. Bao, Z. Hu, and T. Xiong, "A PSO and pattern search based memetic algorithm for SVMs parameters optimization", Neurocomputing, vol. 117, pp. 98-106, Oct 2013.
[http://dx.doi.org/10.1016/j.neucom.2013.01.027]
[28]
B. Mohanty, "Hybrid flower pollination and pattern search algorithm optimized sliding mode controller for deregulated AGC system", J. Ambient Intell. Humaniz. Comput., vol. 11, no. 2, pp. 763-776, Feb 2020.
[http://dx.doi.org/10.1007/s12652-019-01348-5]
[29]
D. He, L. Yang, X. Tian, and Z. Wang, "An overlapped decomposition optimization method for dynamic economic dispatch", IEEE Access, vol. 6, pp. 45804-45820, Aug 2018.
[http://dx.doi.org/10.1109/ACCESS.2018.2866253]
[30]
Y. Chen, J. Wen, L. Jiang, and S. Cheng, "Hybrid algorithm for dynamic economic dispatch with valve-point effects", IET Gener. Transm. Distrib., vol. 7, no. 10, pp. 1096-1104, Oct 2013.
[http://dx.doi.org/10.1049/iet-gtd.2012.0726]
[31]
B. Mohammadi-ivatloo, A. Rabiee, and M. Ehsan, "Time-varying acceleration coefficients IPSO for solving dynamic economic dispatch with non-smooth cost function", Energy Convers. Manage., vol. 56, pp. 175-183, Apr 2012.
[http://dx.doi.org/10.1016/j.enconman.2011.12.004]
[32]
Y. Wang, B. Li, T. Weise, J. Wang, B. Yuan, and Q. Tian, "Self-adaptive learning based particle swarm optimization", Inf. Sci., vol. 181, no. 20, pp. 4515-4538, 2011.
[http://dx.doi.org/10.1016/j.ins.2010.07.013]
[33]
Y. Sonmez, H.T. Kahraman, M.K. Dosoglu, U. Guvenc, and S. Duman, "Symbiotic organisms search algorithm for dynamic economic dispatch with valve-point effects", J. Exp. Theor. Artif. Intell., vol. 29, no. 3, pp. 495-515, 2017.
[http://dx.doi.org/10.1080/0952813X.2016.1198935]
[34]
F. Zaman, S.M. Elsayed, T. Ray, and R.A. Sarker, "Configuring two-algorithm-based evolutionary approach for solving dynamic economic dispatch problems", Eng. Appl. Artif. Intell., vol. 53, pp. 105-125, Aug 2016.
[http://dx.doi.org/10.1016/j.engappai.2016.04.001]
[35]
M.F. Zaman, S.M. Elsayed, T. Ray, and R.A. Sarker, "Evolutionary algorithms for dynamic economic dispatch problems", IEEE Trans. Power Syst., vol. 31, no. 2, pp. 1486-1495, May 2015.
[http://dx.doi.org/10.1109/TPWRS.2015.2428714]
[36]
B. Mohammadi-Ivatloo, A. Rabiee, and A. Soroudi, "Nonconvex dynamic economic power dispatch problems solution using hybrid immune-genetic algorithm", IEEE Syst. J., vol. 7, no. 4, pp. 777-785, May 2013.
[http://dx.doi.org/10.1109/JSYST.2013.2258747]
[37]
R. Azizipanah-Abarghooee, "A new hybrid bacterial foraging and simplified swarm optimization algorithm for practical optimal dynamic load dispatch", Int. J. Electr. Power Energy Syst., vol. 49, pp. 414-429, July 2013.
[http://dx.doi.org/10.1016/j.ijepes.2013.01.013]
[38]
G. Xiong, and D. Shi, "Hybrid biogeography-based optimization with brain storm optimization for non-convex dynamic economic dispatch with valve-point effects", Energy, vol. 157, pp. 424-435, Aug 2018.
[http://dx.doi.org/10.1016/j.energy.2018.05.180]
[39]
X. Yuan, A. Su, Y. Yuan, H. Nie, and L. Wang, "An improved PSO for dynamic load dispatch of generators with valve-point effects", Energy, vol. 34, no. 1, pp. 67-74, Jan 2009.
[http://dx.doi.org/10.1016/j.energy.2008.09.010]
[40]
T. Niknam, R. Azizipanah-Abarghooee, and J. Aghaei, "A new modified teaching-learning algorithm for reserve constrained dynamic economic dispatch", IEEE Trans. Power Syst., vol. 28, no. 2, pp. 749-763, 2012.
[http://dx.doi.org/10.1109/TPWRS.2012.2208273]
[41]
B. Mohammadi-Ivatloo, A. Rabiee, A. Soroudi, and M. Ehsan, "Imperialist competitive algorithm for solving non-convex dynamic economic power dispatch", Energy, vol. 44, no. 1, pp. 228-240, Aug 2012.
[http://dx.doi.org/10.1016/j.energy.2012.06.034]
[42]
M. Ghasemi, E. Akbari, M. Zand, M. Hadipour, S. Ghavidel, and L. Li, "An efficient modified HPSO-TVAC-Based dynamic economic dispatch of generating units", Electr. Power Compon. Syst., vol. 47, no. (19-20), pp. 1826-1840, Dec 2019.
[43]
T. Niknam, R. Azizipanah-Abarghooee, and A. Roosta, "Reserve constrained dynamic economic dispatch: A new fast self-adaptive modified firefly algorithm", IEEE Syst. J., vol. 6, no. 4, pp. 635-646, May 2012.
[http://dx.doi.org/10.1109/JSYST.2012.2189976]
[44]
M.Q. Wang, H.B. Gooi, S.X. Chen, and S. Lu, "A mixed integer quadratic programming for dynamic economic dispatch with valve point effect", IEEE Trans. Power Syst., vol. 29, no. 5, pp. 2097-2106, Feb 2014.
[http://dx.doi.org/10.1109/TPWRS.2014.2306933]
[45]
Z. Wu, J. Ding, Q.H. Wu, Z. Jing, and J. Zheng, "Reserve constrained dynamic economic dispatch with valve-point effect: A two-stage mixed integer linear programming approach", CSEE J. Power Energy Syst., vol. 3, no. 2, pp. 203-211, July 2017.
[http://dx.doi.org/10.17775/CSEEJPES.2017.0025]
[46]
D.C. Secui, "A method based on the ant colony optimization algorithm for dynamic economic dispatch with valve‐point effects", Int. Trans. Electr. Energy Syst., vol. 25, no. 2, pp. 262-287, Feb 2015.
[http://dx.doi.org/10.1002/etep.1841]
[47]
T. Niknam, and F. Golestaneh, "Enhanced bee swarm optimization algorithm for dynamic economic dispatch", IEEE Syst. J., vol. 7, no. 4, pp. 754-762, Apr 2012.
[http://dx.doi.org/10.1109/JSYST.2012.2191831]
[48]
Y. Wang, J. Zhou, Y. Lu, H. Qin, and Y. Wang, "Chaotic self-adaptive particle swarm optimization algorithm for dynamic economic dispatch problem with valve-point effects", Expert Syst. Appl., vol. 38, no. 11, pp. 14231-14237, Oct 2011.
[http://dx.doi.org/10.1016/j.eswa.2011.04.236]
[49]
G. Xiong, L. Yinhong, J. Chen, D. Shi, and X. Duan, "Polyphyletic migration operator and orthogonal learning aided biogeography-based optimization for dynamic economic dispatch with valve-point effects", Energy Convers. Manage., vol. 80, pp. 457-468, Apr 2014.
[http://dx.doi.org/10.1016/j.enconman.2013.12.052]
[50]
R. Arul, G. Ravi, and S. Velusami, "Chaotic self-adaptive differential harmony search algorithm based dynamic economic dispatch", Int. J. Electr. Power Energy Syst., vol. 50, pp. 85-96, Sep 2013.
[http://dx.doi.org/10.1016/j.ijepes.2013.02.017]
[51]
A.I. Selvakumar, "Enhanced cross-entropy method for dynamic economic dispatch with valve-point effects", Int. J. Electr. Power Energy Syst., vol. 33, no. 3, pp. 783-790, Mar 2011.
[http://dx.doi.org/10.1016/j.ijepes.2011.01.001]
[52]
Y. Wang, J. Zhou, H. Qin, and Y. Lu, "Improved chaotic particle swarm optimization algorithm for dynamic economic dispatch problem with valve-point effects", Energy Convers. Manage., vol. 51, no. 12, pp. 2893-2900, Dec 2010.
[http://dx.doi.org/10.1016/j.enconman.2010.06.029]

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