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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Volume 10 | Issue 12
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19445
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
Total Countries : 144
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| Paper Title: | Optimizing Solar Energy Predictions with ARO and AI |
| Authors Name: | Raghavi K Bhujang , Vinay V |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_200448
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| Published Paper Id: | IJRTI2501082 |
| Published In: | Volume 10 Issue 1, January-2025 |
| DOI: | |
| Abstract: | Sunlight is a vital source of renewable energy that can power future smart grids with large amounts of electricity. However, the unpredictable and inconsistent nature of solar energy poses challenges for these systems. The unpredictability of solar power makes it difficult to optimize and plan future smart grids effectively. To mitigate this, accurately predicting photovoltaic (PV) power generation is essential, as it can help reduce potential disruptions to the grid caused by the addition of PV plants.To address this, we propose a Convolutional Neural Network (CNN) architecture for short-term power forecasting, utilizing transfer learning and AlexNet. The input data includes past power output, sunlight radiation, wind speed, and temperature readings. We use the artificial rabbit algorithm to select the optimal hyperparameters for AlexNet (ARO). Additionally, the selective opposition method is incorporated into ARO to improve the tracking efficiency of existing local solutions. All input parameters are converted into 2D feature maps and fed into the CNN to extract features.After thoroughly evaluating the model using real PV data from Limberg, Belgium, the numerical results demonstrate the effectiveness of our approach in PV schemes. |
| Keywords: | Convolutional Neural Network; Artificial rabbit algorithm; Power systems; Lévy flight; AlexNet |
| Cite Article: | "Optimizing Solar Energy Predictions with ARO and AI", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 1, page no.a676-a682, January-2025, Available :http://www.ijrti.org/papers/IJRTI2501082.pdf |
| Downloads: | 000406 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2501082
Registration ID:200448
Published In: Volume 10 Issue 1, January-2025
DOI (Digital Object Identifier):
Page No: a676-a682 Country: Bangalore, Karnataka, India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2501082 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2501082 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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