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

ASME 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.

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

AI-based models for renewable energy resource forecasting
Machine learning and deep learning techniques for power estimation and optimization
AI-driven predictive maintenance in renewable energy infrastructure
AI models assessing climate change impacts on renewable energy systems
AI in environmental risk mitigation for renewable energy projects
Optimization of grid integration and energy storage systems using AI
AI techniques for balancing energy demand and supply in renewable grids
AI for reducing environmental footprints in renewable energy systems

Special Issue Publication Dates:
Paper submission deadline: June 30, 2025
Initial review completed: August 30, 2025
Publication date: May 2026

Submission Instructions:
Papers should be submitted electronically to the journal through the ASME Journal Tool. If you already have an account, log in as an author and select Submit Paper. If you do not have an account, you can create one here.

Once at the Paper Submittal page, select the Journal of Computing and Information Science in Engineering, and then select the Special Issue on AI-Driven Innovations for Renewable Energy and Environmental Sustainability.

Papers received after the deadline or papers not selected for the Special Issue may be accepted for publication in a regular issue.

Guest Editors
Amir H. Gandomi, University of Technology Sydney, Australia (gandomi@uts.edu.au)
Mohammad Reza Nikoo, Sultan Qaboos University, Oman (m.reza@squ.edu.om)
Rouzbeh Nazari, University of Memphis, USA (RNazari@memphis.edu)