| Title of Article |
Parameter estimation of solar PV models using self-adaptive differential evolution with dynamic mutation and pheromone strategy |
| Date of Acceptance |
10 June 2023 |
| Journal |
| Title of Journal |
International Journal of Mathematics and Computer Science |
| Standard |
SCOPUS |
| Institute of Journal |
Badih Ghusayni |
| ISBN/ISSN |
1814-0424 |
| Volume |
19 |
| Issue |
1 |
| Month |
|
| Year of Publication |
2024 |
| Page |
13-21 |
| Abstract |
In this paper we investigate the parameter estimation of solar photovoltaic (PV) models using the self-adaptive differential evolution algorithm with dynamic fitness-ranking mutation and pheromone strategy (SDE-FMP). The dynamic mutation divides the population into three groups according to fitness values and selects groups and their vectors with adaptive probabilities to create a mutant vector. The algorithm also encodes scaling factor and crossover rate values into target vectors to use in mutation and crossover operations and adjusts them with pheromones in the selection process. Experimental results show that the SDE-FMP algorithm can give the solutions with the
lowest errors and is overall competitive with the compared methods regarding the mean errors. |
| Keyword |
Parameter estimation, Solar photovoltaic models, Self-adaptive differential evolution, Pheromone strategy, Mutation strategy. |
| Author |
|
| Reviewing Status |
มีผู้ประเมินอิสระ |
| Status |
ได้รับการตอบรับให้ตีพิมพ์ |
| Level of Publication |
นานาชาติ |
| citation |
false |
| Part of thesis |
true |
| Attach file |
|
| Citation |
0
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Publication
Journal Publication
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