Special Issue on AI-Driven Innovations for Renewable Energy and Environmental Sustainability

Journal of Computing and Information Science in Engineering

Artificial Intelligence (AI) is playing a transformative role in advancing renewable energy technologies and addressing climate change challenges. As the world shifts towards sustainable energy, the need to integrate AI into renewable systems has become vital for managing unpredictability and optimizing performance. Renewable energy sources like solar, wind, and wave power face challenges such as intermittency, grid integration, and real-time decision-making. AI techniques, including machine learning, deep learning, and reinforcement learning, offer cutting-edge solutions by enhancing prediction models, optimizing power generation, and developing adaptive control strategies in dynamic environmental conditions.

By leveraging AI, renewable energy systems can achieve higher efficiency, improve reliability, and significantly reduce the environmental impact associated with fossil fuels. AI-driven approaches, such as predictive algorithms based on sensor and weather data, optimize resource utilization while minimizing emissions. Additionally, evolutionary and genetic algorithms enable multi-objective optimization, balancing cost, efficiency, and environmental factors. As decentralized energy systems grow, AI plays a crucial role in demand response management, energy storage, and grid stability, supporting global climate change mitigation efforts. 

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Topic Areas

THE SCOPE OF THIS ISSUE INCLUDES BUT IS NOT LIMITED TO: