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Smart Renewable Energy Systems for Future Applications

Author(s) Jayashri Ravishankar
Country Australia
Abstract The transition toward renewable energy has become increasingly important because of growing energy demand, environmental concerns, resource constraints, and the need for resilient and sustainable energy systems. Conventional energy infrastructure can face challenges associated with variable renewable generation, demand fluctuations, grid congestion, storage requirements, and complex energy-management processes. Smart renewable energy systems integrate renewable generation technologies with artificial intelligence, Internet of Things devices, advanced forecasting, energy storage, smart grids, digital twins, and intelligent optimization to improve energy production, distribution, consumption, and management. This study examines smart renewable energy systems for future applications, focusing on intelligent energy forecasting, renewable integration, storage optimization, smart-grid management, distributed generation, demand response, and sustainable energy planning. A qualitative descriptive and conceptual research design was adopted using secondary academic literature. The analysis indicates that intelligent technologies can improve renewable-energy utilization by forecasting generation and demand, identifying operational anomalies, optimizing storage, and coordinating distributed energy resources.
AI-based models can analyze weather, historical generation, and consumption information to support predictive energy management. IoT technologies can provide real-time information from solar, wind, storage, buildings, and grid infrastructure, while digital twins can support scenario-based energy planning. However, implementation challenges include intermittency, infrastructure investment, data quality, cybersecurity, interoperability, storage limitations, regulatory barriers, and technical skill requirements. Effective smart renewable energy systems require integration of advanced digital technologies with reliable energy infrastructure, appropriate forecasting, flexible storage, and human-centered management. Future research should explore autonomous renewable-energy optimization, AI-based forecasting, hybrid energy storage, peer-to-peer energy management, digital twins, microgrids, and integrated renewable-energy platforms. Smart renewable energy systems can support more flexible, efficient, resilient, and sustainable energy infrastructures when technological innovation is combined with appropriate system design and responsible governance.
Keywords Renewable Energy, Smart Energy Systems, Artificial Intelligence, Smart Grid, Energy Storage, Energy Forecasting, IoT, Distributed Energy, Sustainable Energy, Energy Optimization.
Field Engineering
Published In Volume 8, Issue 2, March-April 2026
Published On 2026-04-26
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