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Extraction of photovoltaic module model’s parameters using an improved hybrid differential evolution/electromagnetism-like algorithm

Abstract In this paper, an improved differential evolution with adaptive mutation per iteration algorithm (DEAM) is proposed for extracting PV module’s model parameters. DEAM utilizes the attraction–repulsion concept which is used in the electromagnetism to boost the mutation operation of the original differential evolution (DE). Furthermore, a new formula to adjust the mutation scaling factor and crossover rate for each generation is proposed. The proposed method has been validated by experimental data and other previous methods. The results of the proposed method show a high agreement between the experimental and simulated I – V characteristics. The average root mean square error, mean bias error, coefficient of determination and CPU-execution time of the proposed method are 1.744%, 0.158%, 99.21% and 18.5975 s respectively. According to the results, the proposed method offers better performance than other methods in terms of accuracy, CPU-execution time and convergence.
- Universiti Tenaga Nasional Malaysia
- Al Maaref University College Iraq
- An-Najah National University Palestinian-administered areas
- Universiti Tenaga Nasional Malaysia
- Al Maaref University College Iraq
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).69 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
