The Journal of Artificial Intelligence in Smart Energy Systems (JAISES) is an international, peer-reviewed, open access journal published by the Institute of Smart Energy Systems Press (ISESP). The journal is dedicated to advancing research on the development, application, and evaluation of artificial intelligence, machine learning, and intelligent computational methods for smart energy systems.
The journal provides an interdisciplinary platform for researchers, engineers, academics, and industry professionals working at the intersection of artificial intelligence and energy systems. It aims to promote innovative AI-driven approaches that enhance the intelligence, efficiency, reliability, resilience, flexibility, and sustainability of modern energy infrastructures.
The journal welcomes theoretical, methodological, computational, and applied research addressing the use of artificial intelligence for the analysis, forecasting, planning, operation, control, management, and optimization of energy systems. Particular attention is given to research that demonstrates a clear contribution of AI-based methods to solving emerging challenges in smart grids, renewable energy systems, distributed energy resources, energy storage, and intelligent energy management.
The scope of the journal includes, but is not limited to:
Artificial Intelligence in Energy Systems, including AI-based methods for intelligent planning, operation, monitoring, and management;
Machine Learning for Energy Applications, including supervised, unsupervised, semi-supervised, and reinforcement learning approaches;
Deep Learning in Energy Systems, including neural networks and advanced learning architectures for energy-related applications;
Intelligent Energy Management, including AI-enabled energy management, demand-side management, and intelligent coordination of energy resources;
AI-Based Energy Forecasting, including load, demand, price, renewable generation, and other energy-related forecasting applications;
Smart Energy Systems, including AI applications in smart grids, microgrids, distributed energy systems, and integrated energy infrastructures;
AI-Driven Control and Optimization, including intelligent control, reinforcement learning, adaptive optimization, and autonomous energy-system operation;
Predictive Analytics for Energy Systems, including predictive modeling, fault detection, diagnostics, condition monitoring, and predictive maintenance;
Intelligent Decision Support Systems, including AI-assisted decision-making for energy planning, operation, resource allocation, and system management;
AI for Renewable Energy Integration, including intelligent methods for integrating, forecasting, coordinating, and managing renewable and distributed energy resources.
The journal also encourages interdisciplinary research involving explainable and trustworthy AI, generative AI, digital twins, edge and cloud intelligence, Internet of Things, autonomous energy systems, and other emerging intelligent technologies, provided that the work demonstrates a clear and substantive application to smart energy systems.
The journal welcomes original research articles, review articles, systematic review articles, case studies, and letters to the editor that contribute to the advancement and responsible application of artificial intelligence in energy systems.
Research focused solely on general artificial intelligence or computer science without a substantive energy-system application, as well as energy research that does not include a meaningful artificial intelligence or intelligent computational component, is outside the primary scope of the journal.
Institute of Smart Energy Systems Press