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Novel TPPO Based Maximum Power Point Method for Photovoltaic SystemABBASI, M. A. , ZIA, M. F.
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DC-DC power converters, maximum power point trackers, photovoltaic cells, solar energy, solar power generation
optimization(18), algorithm(18), artificial(13), colony(12), comput(8), jasoc(6), swarm(5), soft(5), search(5), jins(5)
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About this article
Date of Publication: 2017-08-31
Volume 17, Issue 3, Year 2017, On page(s): 95 - 100
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.03012
Web of Science Accession Number: 000410369500012
SCOPUS ID: 85028570193
Photovoltaic (PV) system has a great potential and it is installed more when compared with other renewable energy sources nowadays. However, the PV system cannot perform optimally due to its solid reliance on climate conditions. Due to this dependency, PV system does not operate at its maximum power point (MPP). Many MPP tracking methods have been proposed for this purpose. One of these is the Perturb and Observe Method (P&O) which is the most famous due to its simplicity, less cost and fast track. But it deviates from MPP in continuously changing weather conditions, especially in rapidly changing irradiance conditions. A new Maximum Power Point Tracking (MPPT) method, Tetra Point Perturb and Observe (TPPO), has been proposed to improve PV system performance in changing irradiance conditions and the effects on characteristic curves of PV array module due to varying irradiance are delineated. The Proposed MPPT method has shown better results in increasing the efficiency of a PV system.
|References|||||Cited By «-- Click to see who has cited this paper|
| D. Karaboga, "An idea based on honey bee swarm for numerical optimization," Erciyes University, Kayseri, Turkey, Tech. Rep., TR06, 2005.
 J. Kennedy, R. Eberhart, "Particle swarm optimization," in 1995 IEEE international conference on neural networks proceedings, Vols. 16 pp. 19421948, 1995
[CrossRef] [Web of Science Times Cited 19906] [SCOPUS Times Cited 1]
 M. Dorigo, V. Maniezzo, A. Colorni, "Ant system: Optimization by a colony of cooperating agents," IEEE Transactions on Systems Man and Cybernetics Part B, Cybernetics, 26(1), 1996, pp. 2941.
[CrossRef] [Web of Science Times Cited 4797] [SCOPUS Times Cited 6683]
 X. S. Yang, S. Deb, "Engineering optimization by cuckoo search," Int. J. Math. Model. Numer. Opt. 1, pp. 330343, 2010
 X. S. Yang, "Firefly algorithm, stochastic test functions and design optimisation," International Journal of Bio-Inspired Computation, 2(2), pp. 7884, 2010
[CrossRef] [Web of Science Times Cited 545] [SCOPUS Times Cited 717]
 Z. W. Geem, J. H. Kim, G. V. Loganathan, "A new heuristic optimization algorithm: Harmony search. Simulation," 76(2), pp. 6068, 2001
[CrossRef] [SCOPUS Times Cited 2529]
 Uymaz S. A. , Tezel G., Yel E., Artificial algae algorithm (AAA) for nonlinear global optimization, Applied Soft Computing, Volume 31, June 2015, pp. 153-171, ISSN 1568-4946,
[CrossRef] [Web of Science Times Cited 18] [SCOPUS Times Cited 21]
 H. M. Harmanani, F. Drouby, S. B. Ghosn, A parallel genetic algorithm for the open-shop scheduling problem using deterministic and random moves, International Journal of Artificial Intelligence, vol. 14, no. 1, pp. 130-144, 2016.
 Z. C. Johanyák, O. Papp, "A hybrid algorithm for parameter tuning in fuzzy model identification," Acta Polytechnica Hungarica, vol. 9, no. 6, pp. 153-165, 2012.
 R.-E. Precup, R.-C. David, E. M. Petriu, S. Preitl, M.-B. Radac, "Novel adaptive charged system search algorithm for optimal tuning of fuzzy controllers," Expert Systems with Applications, vol. 41, no. 4, pp. 1168-1175, 2014
[CrossRef] [Web of Science Times Cited 43] [SCOPUS Times Cited 53]
 A. Basgumus, M. Namda, R, G. Yilmaz, A. Altuncu, "Performance comparison of the differential evolution and particle swarm optimization algorithms in free-space optical communications systems," Advances in Electrical and Computer Engineering, vol. 15, no. 2, pp. 17-22, 2015.
[CrossRef] [Full Text] [Web of Science Times Cited 5] [SCOPUS Times Cited 5]
 B. Akay, D. Karaboga, "A modified artificial bee colony algorithm for real-parameter optimization," Inf. Sci. 192, pp. 120142, 2012
[CrossRef] [Web of Science Times Cited 377] [SCOPUS Times Cited 503]
 G. Zhu, S. Kwong, "Gbest-guided artificial bee colony algorithm for numerical function optimization," Appl. Math. Comput. 217, pp. 31663173, 2010
[CrossRef] [Web of Science Times Cited 405] [SCOPUS Times Cited 541]
 A. Banharnsakun, T. Achalakul, B. Sirinaovakul, "The best-so-far selection in artificial bee colony algorithm," Appl. Math. Comput. 11, pp. 28882901, 2011
[CrossRef] [Web of Science Times Cited 185] [SCOPUS Times Cited 229]
 A. Banharnsakun, B. Sirinaovakul, T. Achalakul, "The best-so-far ABC with multiple patrilines for clustering problems," Neurocomputing 116, pp. 355366, 2013
[CrossRef] [Web of Science Times Cited 16] [SCOPUS Times Cited 19]
 W. Gao, S. Liu, L. Huang, "A global best artificial bee colony algorithm for global optimization," J. Comput. Appl. Math. 236 pp. 27412753, 2012
[CrossRef] [Web of Science Times Cited 155] [SCOPUS Times Cited 194]
 M. S. Kiran, O. Findik, "A directed artificial bee colony algorithm," Appl. Soft Comput. 26, pp. 454462, 2015
[CrossRef] [Web of Science Times Cited 52] [SCOPUS Times Cited 68]
 W. Gao, S. Liu, "A modified artificial bee colony algorithm," Comput. Oper. Res. 39, pp. 687697, 2012
[CrossRef] [Web of Science Times Cited 223] [SCOPUS Times Cited 304]
 D. Karaboga, B. Gorkemli, "A quick artificial bee colony (qABC) algorithm and its performance on optimization problems," Appl. Soft Comput. 23, pp. 227238, 2014
[CrossRef] [Web of Science Times Cited 75] [SCOPUS Times Cited 94]
 N. Imanian, M.E. Shiri, P. Moradi, "Velocity based artificial bee colony algorithm for high dimensional continuous optimization problems," Eng. Appl. Artif. Intell. 36, pp. 148163, 2014
[CrossRef] [Web of Science Times Cited 28] [SCOPUS Times Cited 32]
 W. Du, B. Li "Multi-strategy ensemble particle swarm optimization for dynamic optimization," Inform. Sci., 178 (15), pp. 30963109, 2008
[CrossRef] [Web of Science Times Cited 125] [SCOPUS Times Cited 157]
 R. Mallipeddi, S. Mallipeddi, P.N. Suganthan, "Ensemble strategies with adaptive evolutionary programming," Inform. Sci., 180 (9), pp. 15711581, 2010
[CrossRef] [Web of Science Times Cited 71] [SCOPUS Times Cited 86]
 R. Mallipeddi, P.N. Suganthan, "Ensemble of constraint handling techniques," IEEE Trans. Evolut. Comput., 14(4), , pp. 561579, 2010
[CrossRef] [Web of Science Times Cited 157] [SCOPUS Times Cited 196]
 R. Mallipeddi, P.N. Suganthan, Q.K. Pan, M.F. Tasgetiren, "Differential evolution algorithm with ensemble of parameters and mutation strategies," Appl. Soft Comput., 11(2), , pp. 16791696, 2011
[CrossRef] [Web of Science Times Cited 495] [SCOPUS Times Cited 587]
 H. Wang, Z. Wu, S. Rahnamayan, H. Sun, Y. Liu, J. Pan, "Multi-strategy ensemble artificial bee colony algorithm," Inf. Sci. 279, pp. 587603, 2014
[CrossRef] [Web of Science Times Cited 50] [SCOPUS Times Cited 75]
 M. S. Kiran, H. Hakli, M. Gunduz, H. Uguz, "Artificial bee colony algorithm with variable search strategy for continuous optimization," Information Sciences 300, pp. 140157, 2010
[CrossRef] [Web of Science Times Cited 40] [SCOPUS Times Cited 54]
 W. Gao, S. Liu, L. Huang, "A novel artificial bee colony algorithm based on modified search equation and orthogonal learning," IEEE T. Syst. Man Cy. B, 2012,
[CrossRef] [Web of Science Times Cited 109] [SCOPUS Times Cited 134]
 P. N. Suganthan, N. Hansen, J.J. Liang, K. Deb, Y.-P. Chen, A. Auger, S. Tiwari, "Problem definitions and evaluation criteria for the CEC 2005 special session on real parameter optimization," Technical report, 2005005, ITT Kanpur, India, 2005.
 V. Muthiah-Nakarajan, M. M. Noel, "Galactic Swarm Optimization: A new global optimization metaheuristic inspired by galactic motion," Applied Soft Computing, Volume 38, January 2016, Pages 771-787, ISSN 1568-4946,
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 8]
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