A Novel Hybrid Statistical Particle Swarm Optimization for Multimodal Functions and Frequency Control of Hybrid Wind-Solar System
作者： Harish Kumar Verma , Cheshta Jain
DOI: 10.1007/S40031-015-0213-5
关键词: Benchmark (computing) 、 Convergence (routing) 、 Control theory 、 Mathematical optimization 、 Statistical parameter 、 Hybrid system 、 Particle swarm optimization 、 Maxima and minima 、 Hybrid algorithm 、 Engineering 、 Multi-swarm optimization
摘要: In this article, a hybrid algorithm of particle swarm optimization (PSO) with statistical parameter (HSPSO) is proposed. Basic PSO for shifted multimodal problems have low searching precision due to falling into number local minima. The proposed approach uses characteristics update the velocity avoid minima and help particles search global optimum improved convergence. performance newly developed verified using various standard multimodal, multivariable, composition benchmark problems. Further, comparative analysis HSPSO variants tested control frequency renewable energy system which comprises solar system, wind diesel generator, aqua electrolyzer ultra capacitor. A significant improvement in convergence characteristic over other observed solving
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Millie Pant, Radha Thangaraj, Ajith Abraham, None, Particle Swarm Optimization: Performance Tuning and Empirical Analysis foundations of computational intelligence. pp. 101- 128 ,(2009) , 10.1007/978-3-642-01085-9_5
Zhongping Wan, Guangmin Wang, Bin Sun, A hybrid intelligent algorithm by combining particle swarm optimization with chaos searching technique for solving nonlinear bilevel programming problems Swarm and evolutionary computation. ,vol. 8, pp. 26- 32 ,(2013) , 10.1016/J.SWEVO.2012.08.001
Ahmad Nickabadi, Mohammad Mehdi Ebadzadeh, Reza Safabakhsh, A novel particle swarm optimization algorithm with adaptive inertia weight soft computing. ,vol. 11, pp. 3658- 3670 ,(2011) , 10.1016/J.ASOC.2011.01.037
Pragya Nema, R.K. Nema, Saroj Rangnekar, A current and future state of art development of hybrid energy system using wind and PV-solar: A review Renewable & Sustainable Energy Reviews. ,vol. 13, pp. 2096- 2103 ,(2009) , 10.1016/J.RSER.2008.10.006
P. Anderson, Anjan Bose, Stability Simulation Of Wind Turbine Systems IEEE Power & Energy Magazine. ,vol. 102, pp. 3791- 3795 ,(1983) , 10.1109/TPAS.1983.317873
P.S. Dokopoulos, A.C. Saramourtsis, A.G. Bakirtzis, Prediction and evaluation of the performance of wind-diesel energy systems IEEE Transactions on Energy Conversion. ,vol. 11, pp. 385- 393 ,(1996) , 10.1109/60.507650
Jiuzhong Zhang, Xueming Ding, A Multi-Swarm Self-Adaptive and Cooperative Particle Swarm Optimization Engineering Applications of Artificial Intelligence. ,vol. 24, pp. 958- 967 ,(2011) , 10.1016/J.ENGAPPAI.2011.05.010
Weilin Du, Bin Li, Multi-strategy ensemble particle swarm optimization for dynamic optimization Information Sciences. ,vol. 178, pp. 3096- 3109 ,(2008) , 10.1016/J.INS.2008.01.020
P. Acharjee, S.K. Goswami, Chaotic particle swarm optimization based robust load flow International Journal of Electrical Power & Energy Systems. ,vol. 32, pp. 141- 146 ,(2010) , 10.1016/J.IJEPES.2009.06.020
Dulal Ch. Das, A.K. Roy, N. Sinha, GA based frequency controller for solar thermal–diesel–wind hybrid energy generation/energy storage system International Journal of Electrical Power & Energy Systems. ,vol. 43, pp. 262- 279 ,(2012) , 10.1016/J.IJEPES.2012.05.025