Driving Affordable & Clean Energy Through AI and Intelligent Systems (2026)

January 8, 2026

The global push for affordable and clean energy is accelerating—yet the technical challenge is growing: variable renewables, complex grids, industrial demand, EV charging, and stricter reliability expectations. In this context, Artificial Intelligence (AI) and intelligent systems are no longer “nice to have.” They are becoming practical tools for forecasting, optimization, control, and decision-making across modern energy systems.

Driving Affordable and Clean Energy Through AI and Intelligent Systems (© 2026) is a forthcoming academic reference that brings together research and applied perspectives on how AI-driven methods can support the transition to more efficient, resilient, and sustainable energy systems.

Why this topic matters now

Energy transition is not only about adding generation capacity. It is also about running complex systems better: improving efficiency, reducing waste, integrating renewables safely, and optimizing operations at scale. AI contributes by helping professionals and institutions extract value from data—turning measurement into insight, and insight into action.

International organizations working on clean energy transition

If you want to follow the global institutions shaping the clean energy agenda, these are highly relevant starting points:

International Energy Agency (IEA) — data, outlooks, and policy guidance for global energy systems.
International Renewable Energy Agency (IRENA) — renewables deployment, innovation, and transition pathways.
United Nations SDG 7 — the global framework for affordable and clean energy.
Clean Energy Ministerial (CEM) — international cooperation on clean energy policies and programs.
Mission Innovation — accelerating clean energy innovation through global collaboration.
National Renewable Energy Laboratory (NREL) — applied research on renewables, grids, storage, and systems integration.

What you can expect from the book

This volume focuses on how AI and intelligent systems can support clean and affordable energy goals through real applications and engineering-driven approaches, including:

Renewables integration and control
Energy management and decision support systems
Smart grids, power systems optimization, and distributed generation
Modern optimization approaches (including reinforcement learning and swarm-based methods)
Emerging directions such as advanced computing approaches for energy systems

Who should read it

This title is particularly relevant for engineers, researchers, graduate students, educators, policy makers, and energy professionals working on clean energy systems, power systems, intelligent control, and energy management.