AI & Optimization in Renewable Energy Systems Course

Inspired by Neeraj Priyadarshi et al’s: Intelligent Renewable Energy Systems Integrating Artificial Intelligence Techniques and Optimization Algorithms

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AI & Optimization in Renewable Energy Systems Course

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Course Overview:

The course is designed to equip professionals with the latest skills and knowledge in the rapidly evolving field of renewable energy. This comprehensive training covers a broad spectrum of topics, including Renewable Energy Integration, Optimization Algorithms for Renewable Energy, Chaotic PSO PV System Modelling, and AI in Smart Grid Island Detection. Participants will gain hands-on experience in Intelligent Control for EMI Reduction, Energy Management for Hybrid Renewable Systems, and the integration of RES with MPPT by SVPWM. The course also delves into the complexities of Distributed Network Planning with Renewable Energy and User Interactive PV System Design GUI. With a focus on practical applications, attendees will learn about Micro-Grid Situational Awareness, AI, and ML for Smart Grids, and Short Term Load Forecasting Using ANN. By the end of this course, participants will be proficient in implementing cutting-edge techniques such as Real-Time EVCS Scheduling with GA and leveraging AI for Enhanced Energy Management.

Target Audience:

Renewable Energy Engineers
Electrical and Electronics Engineers
Energy Managers
Project Managers in Renewable Energy Projects
Smart Grid Specialists
Sustainability Coordinators
Researchers in AI and Renewable Energy

Targeted Organizational Departments:

Research and Development
Operations and Maintenance
Project Management
Energy Management
IT and Data Analytics
Smart Grid Implementation Teams

Targeted Industries:

Renewable Energy
Utilities and Power Distribution
Smart Grid Technology
Electrical Engineering
Energy Consultancy
Sustainability and Environmental Services

Course Offerings:

By the end of this course, participants will be able to:

Implement Optimization Algorithms for Renewable Energy Integration
Utilize Chaotic PSO for PV System Modelling
Apply AI and Machine Learning Techniques in Smart Grid Island Detection
Develop Intelligent Control Techniques for EMI Reduction in DG Environments
Manage Energy in Hybrid Renewable Energy Systems
Integrate RES with MPPT using SVPWM Schemes
Plan Distributed Networks incorporating Renewable Energy Sources
Design User-Interactive PV Systems with advanced GUIs
Enhance Situational Awareness in Micro-Grids using advanced algorithms
Forecast Short Term Load Using ANN
Schedule Real-Time EVCS using GA

Training Methodology:

This course employs a blend of interactive training methodologies to ensure a comprehensive understanding of the material. Participants will engage in case studies, group work, and hands-on sessions to apply Optimization Algorithms for Renewable Energy and Chaotic PSO PV System Modelling. Interactive lectures will cover AI in Smart Grid Island Detection and Intelligent Control for EMI Reduction. Practical workshops will focus on Energy Management of Hybrid Renewable Systems and the integration of RES with MPPT by SVPWM. Real-world scenarios will be used to demonstrate Distributed Network Planning with Renewable Energy, and participants will use advanced tools for User Interactive PV System Design. Each day will conclude with a reflection and review session to consolidate learning outcomes.

Course Toolbox:

Detailed Course Workbook
Case Study Compendium
Interactive Learning Modules
Templates and Checklists for Energy Management
Online Resource Library

Course Agenda:

Day 1: Introduction to Renewable Energy Systems

Topic 1: Overview of Renewable Energy Integration and Optimization Algorithms
Topic 2: Fundamentals of Chaotic PSO PV System Modelling
Topic 3: AI in Smart Grid Island Detection
Topic 4: Intelligent Control Techniques for EMI Reduction
Topic 5: Energy Management for Hybrid Renewable Systems
Reflection & Review: Review of key topics covered, addressing questions and insights gained.

Day 2: Advanced Integration Techniques

Topic 1: RES Integration with MPPT using SVPWM
Topic 2: Managing Standalone Hybrid Wind-PV Systems
Topic 3: Distributed Network Planning with Renewable Energy
Topic 4: Designing User Interactive PV System GUIs
Topic 5: Micro-Grid Situational Awareness
Reflection & Review: Discussion of the day's topics and practical applications.

Day 3: AI and Machine Learning Applications

Topic 1: Micro-PMU and Learning Vector Quantization Algorithms
Topic 2: AI and ML Techniques for Smart Grids
Topic 3: Energy Loss Allocation in Distribution Systems
Topic 4: Enhancing Transient Response of Statcom and HVDC
Topic 5: Short Term Load Forecasting Using ANN
Reflection & Review: Consolidation of AI and ML applications discussed during the day.

Day 4: Practical Implementations and Optimization

Topic 1: Real-Time EVCS Scheduling with GA
Topic 2: Leveraging Artificial Intelligence in Renewable Energy
Topic 3: Machine Learning Techniques in Energy Systems
Topic 4: Optimization Techniques for Energy Management
Topic 5: Advanced Energy Management with AI and ML
Reflection & Review: Practical insights and reflections on the implementation techniques.

Day 5: Integration and Future Trends

Topic 1: Smart Grid Technology Integration
Topic 2: Distributed Generation Energy Management
Topic 3: Control Algorithms for Hybrid Renewable Energy
Topic 4: Future Trends in Renewable Energy Systems with AI Integration
Topic 5: Case Studies and Real-World Applications
Reflection & Review: Final reflections on course learnings, future applications, and Q&A.

How This Course is Different from Other (AI) Empowered Maintenance Courses:

This course stands out due to its unique combination of theoretical knowledge and practical applications, specifically tailored to the needs of the renewable energy sector. Unlike other courses, it provides a hands-on approach to learning with real-world case studies and interactive sessions. Participants will not only learn about Optimization Algorithms for Renewable Energy and AI applications but will also gain practical skills in Chaotic PSO PV System Modelling and Intelligent Control for EMI Reduction. The inclusion of advanced topics such as Micro-Grid Situational Awareness and Real-Time EVCS Scheduling with GA further distinguishes this course, ensuring that attendees are well-equipped to tackle the challenges of modern energy systems.

credits: 5 credit per day

Course Mode: full-time

Provider: Agile Leaders Training Center

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Location	Dates	Duration	Mode	Price
Doha	Week 44, 2025 Nov 2, 2025 - Nov 6, 2025	5 Days	Onsite	€5,500
Paris	Week 45, 2025 Nov 3, 2025 - Nov 7, 2025	5 Days	Onsite	€5,700
Manama	Week 45, 2025 Nov 9, 2025 - Nov 13, 2025	5 Days	Onsite	€4,700
Zanzibar	Week 46, 2025 Nov 16, 2025 - Nov 20, 2025	5 Days	Onsite	€5,500
Sharm El-Sheikh	Week 47, 2025 Nov 17, 2025 - Nov 21, 2025	5 Days	Onsite	€4,100
Nairobi	Week 47, 2025 Nov 23, 2025 - Nov 27, 2025	5 Days	Onsite	€4,500
Barcelona	Week 48, 2025 Nov 24, 2025 - Nov 28, 2025	5 Days	Onsite	€5,700
Athens	Week 48, 2025 Nov 30, 2025 - Dec 4, 2025	5 Days	Onsite	€6,700
London	Week 50, 2025 Dec 8, 2025 - Dec 12, 2025	5 Days	Onsite	€5,700
Cairo	Week 50, 2025 Dec 8, 2025 - Dec 12, 2025	5 Days	Onsite	€4,100
Madrid	Week 50, 2025 Dec 8, 2025 - Dec 12, 2025	5 Days	Onsite	€5,700
Cape town	Week 50, 2025 Dec 14, 2025 - Dec 18, 2025	5 Days	Onsite	€6,000
Istanbul	Week 51, 2025 Dec 15, 2025 - Dec 19, 2025	5 Days	Onsite	€4,500
Kuala Lumpur	Week 52, 2025 Dec 22, 2025 - Dec 26, 2025	5 Days	Onsite	€5,200
Manama	Week 01, 2025 Dec 29, 2025 - Jan 2, 2026	5 Days	Onsite	€4,700
Dubai	Week 01, 2025 Dec 30, 2025 - Jan 3, 2026	5 Days	Onsite	€4,500
Milan	Week 02, 2026 Jan 6, 2026 - Jan 10, 2026	5 Days	Onsite	€5,700
Tokyo	Week 02, 2026 Jan 6, 2026 - Jan 10, 2026	5 Days	Onsite	€10,000
Rome	Week 03, 2026 Jan 13, 2026 - Jan 17, 2026	5 Days	Onsite	€5,700
Istanbul	Week 04, 2026 Jan 20, 2026 - Jan 24, 2026	5 Days	Onsite	€4,500