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International Journal for Research Trends and Innovation
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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
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Issue Published : 115
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Total Authors : 21252
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| Paper Title: | A Renewable Energy Integration with Microgrid Optimization Using Machine Learning |
| Authors Name: | Yash Babu Dhangar , Vivek Sudhir Lawhale , Shivam Ramagya Yadav , Deepa Agrawal |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_202488
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| Published Paper Id: | IJRTI2504184 |
| Published In: | Volume 10 Issue 4, April-2025 |
| DOI: | http://doi.one/10.1729/Journal.44894 |
| Abstract: | They're Integrating renewable energy sources into the power grid represents challenges in terms of efficiency, stability and optimization. This study focuses on microgrid optimization using machine learning techniques to improve the use of renewable energy. The proposed system uses extreme gradient increase (xgboost) to optimize performance distribution within the microgrid to ensure maximum energy efficiency. Implements a system of models for front-end and Python-based machine learning back-end processing, providing real-time insights to network operators and energy planners. The results show that XGBoost significantly improves energy distribution efficiency and grid stability compared to traditional methods. Implemented with a Python-based backend and an interactive powerlift frontend, the system processes data in real time, providing intelligent insights and decision-making tools for energy drivers. Through rigorous model assessments and data testing in the real world, the results show that XGBoost significantly improves energy efficiency, reduces losses, and improves the resilience of microgrid systems. This research contributes to the development of sustainable AI-controlled energy management solutions for the future. |
| Keywords: | Microgrid, xgboost, Machine Learning, Energy Optimization, Electric Lighting, Python, Grid Stability, Smart Grid, Energy Prediction, Energy Management, Power Distribution, Database Energy Systems, IoT in Energy Management. |
| Cite Article: | "A Renewable Energy Integration with Microgrid Optimization Using Machine Learning", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.b677-b681, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504184.pdf |
| Downloads: | 000424 |
| 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: IJRTI2504184
Registration ID:202488
Published In: Volume 10 Issue 4, April-2025
DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.44894
Page No: b677-b681 Country: Mumbai, maharastra, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2504184 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2504184 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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