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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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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 117
Article Submitted : 21305
Article Published : 8476
Total Authors : 22301
Total Reviewer : 802
Total Countries : 156
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Published Paper Details
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| Paper Title: | Framework for Designing Highly Available Multi-Zone Data Platforms on Google Cloud Kubernetes Engine for Solar Industry |
| Authors Name: | Sanchee Kaushik |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_206217
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| Published Paper Id: | IJRTI2509076 |
| Published In: | Volume 10 Issue 9, September-2025 |
| DOI: | https://doi.org/10.56975/ijrti.v10i9.206217 |
| Abstract: | The integration of Artificial Intelligence (AI) in solar energy systems over the past decade has opened new frontiers in renewable energy optimization. This review presents a comprehensive synthesis of AI methods including machine learning (ML), deep learning (DL), reinforcement learning (RL), and hybrid techniques used to enhance solar power forecasting, fault detection, energy output prediction, and intelligent control. Through comparative analysis of key studies, experimental results, and performance evaluations, it becomes evident that AI-driven models, particularly LSTM networks and convolutional neural networks (CNNs), outperform traditional methods in both accuracy and adaptability. However, critical challenges remain, such as data scarcity, interpretability, model generalization, and integration with real-time systems. This review not only outlines the evolution and current state of AI in solar energy optimization but also offers future directions to guide further interdisciplinary research. By bridging engineering, data science, and sustainability goals, AI has the potential to significantly accelerate the transition to smarter, greener solar energy infrastructures. |
| Keywords: | Solar energy optimization, Artificial Intelligence, Deep Learning, Machine Learning, Forecasting, Photovoltaics, Reinforcement Learning, Energy Systems, Smart Grids, LSTM, CNN. |
| Cite Article: | "Framework for Designing Highly Available Multi-Zone Data Platforms on Google Cloud Kubernetes Engine for Solar Industry", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 9, page no.a670-a680, September-2025, Available :http://www.ijrti.org/papers/IJRTI2509076.pdf |
| Downloads: | 0001375 |
| 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 |
| Publication Details: |
Published Paper ID: IJRTI2509076
Registration ID:206217
Published In: Volume 10 Issue 9, September-2025
DOI (Digital Object Identifier): https://doi.org/10.56975/ijrti.v10i9.206217
Page No: a670-a680 Country: -, -, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2509076 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2509076 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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