Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
The integration of renewable energy sources into power grids presents challenges related to spatial distribution, resource variability, and grid stability. This paper explores a novel approach using Multi-Agent Systems (MAS) for geospatial optimization of renewable energy deployment. By leveraging agent-based modeling, geographic information systems (GIS), and optimization techniques, the proposed system enhances energy efficiency, grid resilience, and sustainability. The framework is evaluated through simulations that assess optimal energy distribution, balancing supply and demand across diverse geographic regions. Future research will explore the integration of real-time data and artificial intelligence for enhanced predictive capabilities.
"Multi-Agent Geospatial Optimization for Renewable Energy Integration", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 6, page no.a109-a111, June-2025, Available :http://www.ijrti.org/papers/IJRTI2506015.pdf
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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