Photovoltaic Power Prediction with Teaching Learning Based Optimization Algorithm
Yazarlar (1)
Dr. Öğr. Üyesi Oğuz TAŞDEMİR Kırşehir Ahi Evran Üniversitesi, Türkiye
Makale Türü Açık Erişim Özgün Makale (Ulusal alan endekslerinde (TR Dizin, ULAKBİM) yayınlanan tam makale)
Dergi Adı Gazi University Journal of Science Part A: Engineering and Innovation
Dergi ISSN 2147-9542
Dergi Tarandığı Indeksler TR DİZİN
Makale Dili İngilizce Basım Tarihi 12-2024
Kabul Tarihi 12-04-2026 Yayınlanma Tarihi
Cilt / Sayı / Sayfa 11 / 4 / 780–791 DOI 10.54287/gujsa.1581828
Makale Linki https://doi.org/10.54287/gujsa.1581828
Özet
With the escalation of the energy crisis, renewable energy sources like photovoltaic (PV) power, wind energy, and hydropower have garnered significant interest from numerous nations globally. Photovoltaic (PV) electricity is a significant contributor to the continuous, steady, and cost-effective functioning of power networks among the most prevalent renewable energy sources (Lin et al., 2022). In reaction to the growing need for renewable energy, photovoltaic power generation is consistently rising. The International Renewable Energy Agency (IRENA, 2024) projects that global renewable energy capacity will attain 3870 GW by the conclusion of 2023. Solar energy has the largest share in the global total with 1419 GW of capacity. Hydropower and wind power accounted for most of the rest, with total capacities of 1268 GW and 1017 GW, respectively (IRENA, 2024). Renewable energy capacity by source is shown in Figure 1.Renewable energy capacity increased by 473 GW in 2023. Solar power continued to lead capacity growth with a large increase of 346 GW, followed by wind power with 116 GW. Solar and wind continued to dominate renewable capacity growth, together accounting for 97.6% of all net renewable capacity additions in 2023. The expansion of wind and solar energy has resulted in the highest annual increase in renewable generation capacity, as well as the highest percentage growth on record (IRENA, 2024). However, due to the randomness, uncertainty, and variability in photovoltaic power generation, there are significant challenges in connecting large-scale photovoltaic systems to the grid (Maghami et al., 2016). The …
Anahtar Kelimeler
TLBO | Photovoltaic Power | Current Developments | Photovoltaic Power Estimation
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Photovoltaic Power Prediction with Teaching Learning Based Optimization Algorithm

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