AI & Optimization in Renewable Energy Systems Course
At a glance
- Duration
- 1 Week
- Format
- Classroom
- Cities
- Baku, Langkawi, Doha, Barcelona, Bali, Singapore and more
- Next session
- 19 – 23 October 2026, Baku
- Average fee
- 7,500 €
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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Events for this Course
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Baku 19 – 23 October 2026
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Langkawi 25 – 29 October 2026
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Doha 1 – 5 November 2026
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Barcelona 2 – 6 November 2026
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Bali 8 – 12 November 2026
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Singapore 9 – 13 November 2026
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Sharm El-Sheikh 16 – 20 November 2026
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Abu Dhabi 23 – 27 November 2026
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Seoul 30 November – 4 December 2026
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Bangkok 6 – 10 December 2026
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Kuala Lumpur 14 – 18 December 2026
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Istanbul 21 – 25 December 2026
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Dubai 28 December 2026 – 1 January 2027
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Barcelona 4 – 8 January 2027
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Munich 11 – 15 January 2027
-
Kuwait 17 – 21 January 2027
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Tbilisi 25 – 29 January 2027
-
Tokyo 1 – 5 February 2027
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Frankfurt 1 – 5 February 2027
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Muscat 21 – 25 February 2027
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Casablanca 22 – 26 February 2027
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Dubai 1 – 5 March 2027
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Zanzibar 7 – 11 March 2027
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Marbella 14 – 18 March 2027
-
Manama 21 – 25 March 2027
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London 29 March – 2 April 2027
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Chicago 4 – 8 April 2027
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Toronto 11 – 15 April 2027
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Paris 12 – 16 April 2027
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Geneva 18 – 22 April 2027
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Lisbon 19 – 23 April 2027
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Amman 2 – 6 May 2027
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Phuket 9 – 13 May 2027
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Trabzon 16 – 20 May 2027
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New York 24 – 28 May 2027
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Nice 31 May – 4 June 2027
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Madrid 7 – 11 June 2027
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Johannesburg 13 – 17 June 2027
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San Diego 21 – 25 June 2027
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Nairobi 27 June – 1 July 2027
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Rome 5 – 9 July 2027
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Cape town 11 – 15 July 2027
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Jakarta 19 – 23 July 2027
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Montreux 26 – 30 July 2027
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Accra 1 – 5 August 2027
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Amsterdam 9 – 13 August 2027
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Porto 16 – 20 August 2027
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Barcelona 23 – 27 August 2027
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Prague 30 August – 3 September 2027
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Berlin 30 August – 3 September 2027
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Zoom 6 – 10 September 2027
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Tashkent 12 – 16 September 2027
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London 20 – 24 September 2027
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Athens 27 September – 1 October 2027
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Abu Dhabi 4 – 8 October 2027
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Milan 4 – 8 October 2027
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Cairo 11 – 15 October 2027
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Vienna 18 – 22 October 2027
| Image | Location | Dates | Duration | Mode | Price | Actions |
|---|---|---|---|---|---|---|
|
|
Baku |
Week 43, 2026 19 – 23 October 2026 |
1 Week | Onsite | €8,000 | |
|
|
Langkawi |
Week 43, 2026 25 – 29 October 2026 |
1 Week | Onsite | €8,000 | |
|
|
Doha |
Week 44, 2026 1 – 5 November 2026 |
1 Week | Onsite | €7,000 | |
|
|
Barcelona |
Week 45, 2026 2 – 6 November 2026 |
1 Week | Onsite | €6,500 | |
|
|
Bali |
Week 45, 2026 8 – 12 November 2026 |
1 Week | Onsite | €6,500 | |
|
|
Singapore |
Week 46, 2026 9 – 13 November 2026 |
1 Week | Onsite | €6,500 | |
|
|
Sharm El-Sheikh |
Week 47, 2026 16 – 20 November 2026 |
1 Week | Onsite | €5,200 | |
|
|
Abu Dhabi |
Week 48, 2026 23 – 27 November 2026 |
1 Week | Onsite | €6,500 | |
|
|
Seoul |
Week 49, 2026 30 November – 4 December 2026 |
1 Week | Onsite | €12,000 | |
|
|
Bangkok |
Week 49, 2026 6 – 10 December 2026 |
1 Week | Onsite | €8,000 | |
|
|
Kuala Lumpur |
Week 51, 2026 14 – 18 December 2026 |
1 Week | Onsite | €6,500 | |
|
|
Istanbul |
Week 52, 2026 21 – 25 December 2026 |
1 Week | Onsite | €6,000 | |
|
|
Dubai |
Week 53, 2026 28 December 2026 – 1 January 2027 |
1 Week | Onsite | €6,500 | |
|
|
Barcelona |
Week 01, 2027 4 – 8 January 2027 |
1 Week | Onsite | €6,500 | |
|
|
Munich |
Week 02, 2027 11 – 15 January 2027 |
1 Week | Onsite | €6,500 | |
|
|
Kuwait |
Week 02, 2027 17 – 21 January 2027 |
1 Week | Onsite | €7,000 | |
|
|
Tbilisi |
Week 04, 2027 25 – 29 January 2027 |
1 Week | Onsite | €5,700 | |
|
|
Tokyo |
Week 05, 2027 1 – 5 February 2027 |
1 Week | Onsite | €12,000 | |
|
|
Frankfurt |
Week 05, 2027 1 – 5 February 2027 |
1 Week | Onsite | €6,500 | |
|
|
Muscat |
Week 07, 2027 21 – 25 February 2027 |
1 Week | Onsite | €6,500 |
Frequently asked questions
Are training dates available?
Yes. Available dates and destinations are listed in the course dates section on this page.
How can I register?
Choose an available date on this page and complete the registration form, or send a programme enquiry.
Can I download the course brochure?
Yes. Use the brochure download link provided on this page.
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