Advancing AI Literacy Lessons

Understanding AI in Renewable Energy Systems

Environmental Science | 9-12
Duration: 75 minutes
Author: Leslie Llamas, Science, Robotics, and CTE Teacher

In this introductory lesson, students explore how artificial intelligence (AI) is transforming renewable energy systems. Through collaborative research and scaffolded activities, students will define key concepts such as smart grids, predictive maintenance, and energy equity. They will investigate real-world applications of AI in solar, wind, and water systems, and begin to consider the ethical and environmental implications of these technologies. This lesson builds foundational knowledge and prepares students for deeper analysis and solution design.

Lesson Plan Series

Lesson Objectives

Analyze how artificial intelligence enhances renewable energy systems through smart grid optimization, predictive maintenance, and resource management.
Evaluate the benefits and limitations of AI applications in sustainability, including their environmental and societal impacts.
Interpret real-world data and case studies to explain how AI contributes to energy efficiency and reliability.
Critique ethical considerations such as energy equity, data privacy, and environmental trade-offs in AI-driven energy systems.
Synthesize research findings into a coherent visual representation that communicates key concepts and implications of AI in renewable energy.

Essential Questions

How can we interpret the role of artificial intelligence in transforming renewable energy systems?
In what ways does AI contribute to or challenge sustainability and energy equity?
What patterns or trends emerge when analyzing real-world applications of AI in solar, wind, or water systems?
How might we evaluate the ethical implications of using AI in environmental decision-making?
What strategies can we develop to communicate complex AI concepts clearly and responsibly?