2013
DOI: 10.1016/j.enconman.2013.03.033
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm

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Cited by 290 publications
(131 citation statements)
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“…The method proposed in this paper combines the GA, which is a common method for calculating the five parameters (I ph , I s , η, R s , R h ) [12,17], with some explicit equations that are also used to calculate the SDM parameters in a direct way [10,11], i.e., without requiring iterative algorithms. Both methods, when applied independently, require the knowledge of the current and voltage values in the MPP and the values of I sc and V oc for the actual environmental condition.…”
Section: The Optimized Sdm Parameter Identification Methods Based On Gmentioning
confidence: 99%
See 1 more Smart Citation
“…The method proposed in this paper combines the GA, which is a common method for calculating the five parameters (I ph , I s , η, R s , R h ) [12,17], with some explicit equations that are also used to calculate the SDM parameters in a direct way [10,11], i.e., without requiring iterative algorithms. Both methods, when applied independently, require the knowledge of the current and voltage values in the MPP and the values of I sc and V oc for the actual environmental condition.…”
Section: The Optimized Sdm Parameter Identification Methods Based On Gmentioning
confidence: 99%
“…It is worth noting that in [12,17], the fitness function is calculated by selecting test points from I sc to V oc ; in this paper, instead, all the points are concentrated close to the MPP. Figure 2 shows the difference and highlights that the new approach allows reducing the power loss significantly because the system is controlled to operate not too far from the MPP.…”
Section: Genetic Algorithm Fitness Function Calculationmentioning
confidence: 99%
“…Fig. 3 The flowchart of proposed algorithm To sum up, at each iteration first the new locations are calculated from (11) and their qualities are evaluated through (12). Then, necessary substitutions are performed and the selection probabilities are calculated from (13).…”
Section: Summary Of Abc Algorithmmentioning
confidence: 99%
“…For example, application of genetic algorithm (GA) [11][12][13], particle swarm optimization (PSO) [14][15][16], simulated annealing (SA) [17], differential evolution (DE) [18][19][20][21][22], pattern search (PS) [23], harmony search (HS) [24], artificial bee swarm optimization (ABSO) [25], bird mating optimizer (BMO) [26], bacterial foraging optimization (BFO) [27], artificial bee colony (ABC) [28], biogeography-based optimization algorithm with mutation strategies (BBO-M) [29] and teaching-learning based optimization (TLBO) [30] for this purpose can be found in the literature.…”
Section: Introductionmentioning
confidence: 99%
“…The optimization and maximum power tracking of solar PV are intensively explained in [28], [29] and [30]. The optimal energy scheduling for a practical application in NZEBs still seems infeasible owing to constraints on technology, integration and operations, as mentioned in [18].…”
Section: Introductionmentioning
confidence: 99%