Abstract
Economic dispatch (ED) is an important part in the economic operation of power systems. It is an NP-hard problem with multiple practical constraints. This paper proposes a novel approach that combines a swarm intelligence algorithm with a constraint-handling mechanism to solve the ED problem. First, we design a comprehensive learning cuckoo search algorithm with two strengthen strategies. A comprehensive learning strategy is designed to give the algorithm advanced learning ability in high-dimensional and multi-modal environment and thus enhance the search ability. A duplicate elimination strategy is utilized as an elite strategy to improve the evolving efficiency of the algorithm. Then, we propose a constraint-based population generation method named chaos-lambda method to reduce the searching complexity, and a solution repair method to repair unfeasible solutions that violate the constraints. The proposed approach is tested on 5 systems with different benchmarks and compared with the state-of-the-art algorithms. Our approach achieves the best performance on every test.
Similar content being viewed by others
References
Al-Betar MA, Awadallah MA, Khader AT, Bolaji AL (2016) Tournament-based harmony search algorithm for non-convex economic load dispatch problem. Appl Soft Comput 47:449– 459
Al-Betar MA, Awadallah MA, Khader AT, Bolaji AL, Almomani A (2018) Economic load dispatch problems with valve-point loading using natural updated harmony search. Neural Comput Applic 29(10):767–781
Bai T, Yb Kan, Jx Chang, Huang Q, Chang FJ (2017) Fusing feasible search space into pso for multi-objective cascade reservoir optimization. Appl Soft Comput 51:328–340
Barani F, Mirhosseini M, Nezamabadi-Pour H (2017) Application of binary quantum-inspired gravitational search algorithm in feature subset selection. Appl Intell 47(2):304–318
Basu M (2015) Modified particle swarm optimization for nonconvex economic dispatch problems. International Journal of Electrical Power & Energy Systems 69:304–312
Basu M (2016) Kinetic gas molecule optimization for nonconvex economic dispatch problem. International Journal of Electrical Power & Energy Systems 80:325–332
Chen G, Ding X (2015) Optimal economic dispatch with valve loading effect using self-adaptive firefly algorithm. Appl Intell 42(2):276–288
Cheng J, Wang L, Jiang Q, Xiong Y (2018) A novel cuckoo search algorithm with multiple update rules. Appl Intell 48(11):4192–4211
Del Ser J, Osaba E, Molina D, Yang XS, Salcedo-Sanz S, Camacho D, Das S, Suganthan PN, Coello CAC, Herrera F (2019) Bio-inspired computation: Where we stand and what’s next. Swarm and Evolutionary Computation 48:220–250
Dieu VN, Schegner P, Ongsakul W (2011) A newly improved particle swarm optimization for economic dispatch with valve point loading effects. In: 2011 IEEE Power and Energy Society General Meeting, IEEE, pp 1–8
Duman S, Yorukeren N, Altas IH (2015) A novel modified hybrid psogsa based on fuzzy logic for non-convex economic dispatch problem with valve-point effect. International Journal of Electrical Power & Energy Systems 64:121–135
Elsayed W, Hegazy Y, El-Bages M, Bendary F (2017) Improved random drift particle swarm optimization with self-adaptive mechanism for solving the power economic dispatch problem. IEEE Trans Ind Inform PP(99):1–1
Gaing ZL (2003) Particle swarm optimization to solving the economic dispatch considering the generator constraints. IEEE Trans Power Syst 18(3):1187–1195
Gaing ZL (2004) Closure to” discussion of’particle swarm optimization to solving the economic dispatch considering the generator constraints’”. IEEE Trans Power Syst 19(4):2122–2123
He X, Rao Y, Huang J (2016) A novel algorithm for economic load dispatch of power systems. Neurocomputing 171:1454–1461
Hosseinnezhad V, Rafiee M, Ahmadian M, Ameli MT (2014) Species-based quantum particle swarm optimization for economic load dispatch. International Journal of Electrical Power & Energy Systems 63:311–322
Kumar M, Dhillon J (2018) Hybrid artificial algae algorithm for economic load dispatch. Appl Soft Comput 71:89–109
Liang JJ, Qin AK, Suganthan PN, Baskar S (2006) Comprehensive learning particle swarm optimizer for global optimization of multimodal functions. IEEE Trans Evolut Comput 10(3):281–295
Mandal B, Roy PK, Mandal S (2014) Economic load dispatch using krill herd algorithm. International Journal of Electrical Power & Energy Systems 57:1–10
Meng X, Chang J, Wang X, Wang Y (2019) Multi-objective hydropower station operation using an improved cuckoo search algorithm. Energy 168:425–439
Neto JXV, Reynoso-Meza G, Ruppel TH, Mariani VC, dos Santos Coelho L (2017) Solving non-smooth economic dispatch by a new combination of continuous grasp algorithm and differential evolution. International Journal of Electrical Power & Energy Systems 84:13–24
Niknam T, Mojarrad HD, Meymand HZ (2011) Non-smooth economic dispatch computation by fuzzy and self adaptive particle swarm optimization. Appl Soft Comput 11(2):2805–2817
Niu Q, Zhang H, Wang X, Li K, Irwin GW (2014) A hybrid harmony search with arithmetic crossover operation for economic dispatch. International Journal of Electrical Power & Energy Systems 62:237–257
Park JB, Jeong YW, Shin JR, Lee KY (2010) An improved particle swarm optimization for nonconvex economic dispatch problems. IEEE Trans Power Syst 25(1):156–166
Pradhan M, Roy PK, Pal T (2016) Grey wolf optimization applied to economic load dispatch problems. International Journal of Electrical Power & Energy Systems 83:325–334
Qin Q, Cheng S, Chu X, Lei X, Shi Y (2017) Solving non-convex/non-smooth economic load dispatch problems via an enhanced particle swarm optimization. Appl Soft Comput 59:229–242
Reddy AS, Vaisakh K (2013) Shuffled differential evolution for large scale economic dispatch. Electr Power Syst Res 96:237–245
Sayed GI, Khoriba G, Haggag MH (2018) A novel chaotic salp swarm algorithm for global optimization and feature selection. Appl Intell 48(10):3462–3481
Secui DC (2016) A modified symbiotic organisms search algorithm for large scale economic dispatch problem with valve-point effects. Energy 113:366–384
Sinha N, Chakrabarti R, Chattopadhyay P (2003) Evolutionary programming techniques for economic load dispatch. IEEE Trans Evolut Comput 7(1):83–94
Tharwat A, Hassanien AE (2018) Chaotic antlion algorithm for parameter optimization of support vector machine. Appl Intell 48(3):670–686
Thirugnanasambandam K, Prakash S, Subramanian V, Pothula S, Thirumal V (2019) Reinforced cuckoo search algorithm-based multimodal optimization. Appl Intell 49(6):2059–2083
Wang X, Chang J, Meng X, Wang Y (2017) Research on multi-objective operation based on improved nsga-ii for lower yellow river. J Hydraul Eng 48:135–145
Wood AJ, Wollenberg BF et al (2013) Power generation, operation, and control. John Wiley & Sons
Xiong G, Shi D (2018) Orthogonal learning competitive swarm optimizer for economic dispatch problems. Appl Soft Comput 66:134–148
Yang XS (2014) Nature-inspired optimization algorithms. Elsevier
Yang XS, Deb S (2009) Cuckoo search via lévy flights. In: 2009 World Congress on Nature & Biologically Inspired Computing, NaBIC, IEEE, pp 210–214
Yang XS, Hosseini SSS, Gandomi AH (2012) Firefly algorithm for solving non-convex economic dispatch problems with valve loading effect. Appl soft Comput 12(3):1180– 1186
Yang Y, Wei B, Liu H, Zhang Y, Zhao J, Manla E (2018) Chaos firefly algorithm with self-adaptation mutation mechanism for solving large-scale economic dispatch with valve-point effects and multiple fuel options. IEEE Access 6:45907–45922
Yu JT, Kim CH, Wadood A, Khurshiad T, Rhee SB (2019) Self-adaptive multi-population jaya algorithm with lévy flights for solving economic load dispatch problems. IEEE Access
Zhao J, Liu S, Zhou M, Guo X, Qi L (2018) Modified cuckoo search algorithm to solve economic power dispatch optimization problems. IEEE/CAA Journal of Automatica Sinica 5(4):794– 806
Zhong H, Xia Q, Wang Y, Kang C (2013) Dynamic economic dispatch considering transmission losses using quadratically constrained quadratic program method. IEEE Trans Power Syst 28(3):2232–2241
Zhu H, Qi X, Chen F, He X, Chen L, Zhang Z (2019) Quantum-inspired cuckoo co-search algorithm for no-wait flow shop scheduling. Appl Intell 49(2):791–803
Acknowledgements
This work is supported in part by NSFC (61472229, 616-02279, and 71704096), Sci. & Tech. Development Fund of Shandong Province of China (ZR2017BF015 and ZR2017M-F027), the Humanities and Social Science Research Project of the Ministry of Education (18YJAZH017), the Taishan Scholar Climbing Program of Shandong Province, and SDUST Research Fund (2015TDJH102).
Author information
Authors and Affiliations
Corresponding authors
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Huang, Z., Zhao, J., Qi, L. et al. Comprehensive learning cuckoo search with chaos-lambda method for solving economic dispatch problems. Appl Intell 50, 2779–2799 (2020). https://doi.org/10.1007/s10489-020-01654-y
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10489-020-01654-y