About
Smart energy grids represent the future of energy distribution, where advanced technologies enable efficient, reliable, and environmentally friendly energy management. This program explores the critical role of artificial intelligence in transforming traditional grids into intelligent, adaptive systems capable of real-time monitoring, energy forecasting, and demand-response strategies. Participants will learn how AI can enhance grid resilience, optimize power distribution, and reduce energy waste, contributing to a more sustainable energy landscape.
This program covers AI applications in integrating renewable energy sources like wind and solar into smart grids, ensuring efficient energy distribution while minimizing environmental impact.
Aim
This program aims to provide participants with an in-depth understanding of how artificial intelligence (AI) can be applied to optimize smart energy grids. It focuses on AI-driven technologies for energy demand forecasting, load management, and integrating renewable energy sources, offering sustainable solutions for modern energy challenges.
Program Objectives
- Understand the fundamentals of AI and its role in smart energy grids.
- Explore AI applications for real-time monitoring and energy demand forecasting.
- Learn AI techniques for integrating renewable energy sources into smart grids.
- Analyze case studies of AI-driven smart energy grid projects globally.
Program Structure
Week 1: Introduction to AI in Smart Energy Systems
Overview of traditional energy grid challenges.
Limitations of traditional grids in handling energy demand and renewable sources.
Introduction to smart energy grids and their features.
Role of AI in optimizing smart grids.
Environmental benefits of AI-driven smart grids.
Week 2: The Science Behind AI Applications in Energy Grids
AI for energy demand forecasting and load management.
Integration of renewable energy sources into smart grids.
Grid monitoring and real-time data processing for resilience.
Week 3: Market Dynamics and Practical Applications
Market trends in AI for energy management.
Case studies of AI-enhanced smart grids.
Regulatory and ethical considerations.
Week 4: Future Trends and Career Opportunities
Innovations in AI for energy systems.
Career pathways in AI for energy grids.
Future outlook for AI in driving global sustainability transitions.
Participant’s Eligibility
- Undergraduate degree in Electrical Engineering, Environmental Science, or Computer Science.
- Professionals in the energy sector or smart grid technology.
- Individuals interested in renewable energy and AI applications in energy management.
Program Outcomes
- Mastery of AI techniques for smart grid optimization.
- Ability to apply AI for real-time energy demand forecasting and load management.
- Practical skills in integrating renewable energy sources into smart energy grids.
- Knowledge of AI-driven strategies for enhancing grid resilience and sustainability.
Program Deliverables
- Access to e-LMS
- Real-Time Project for Dissertation
- Project Guidance
- Paper Publication Opportunity
- Self Assessment
- Final Examination
- e-Certification
- e-Marksheet
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