Making Participant Digital Transformation, Data Analytics and AI Ready for his Work
res630-4
4 Week Professional Certification Training
AI and Data Analytics Integration in Renewable Energy Storage Systems Specialist
www.eurotraining.com/bro/res630-4.php
4 Week Professional Certification Workshops
Seattle, USA
| Istanbul
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New York
| Dubai
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Kualalumpur
| London
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AI and Data Analytics Skills for Renewable Energy Storage Systems
AI and Data Analytics Skills for Renewable Energy Storage Systems
Building Multi-discipline Understanding, Knowledge, Process Understanding, Skills, and Competencies to Perform and Improve each of the Work Performance included in the Program Content Below
Program Overview
The AI and Data Analytics Skills for Renewable Energy Storage Systems program is an advanced training initiative designed to provide participants with specialized knowledge and skills in using artificial intelligence (AI) and data analytics to optimize the performance and efficiency of renewable energy storage systems. This program aims to empower engineers, data scientists, and renewable energy professionals with expertise in leveraging AI-driven technologies to enhance energy storage management, prediction, and decision-making. Program topics cover the key aspects of utilizing AI and data analytics for energy storage systems in renewable energy applications.
This Program provides participants with the knowledge and skills to leverage these advanced technologies for optimizing energy storage operations, enhancing renewable energy integration, and maximizing the benefits of energy storage systems in a sustainable energy transition.
Program will This two week program provides further insight, deeper understanding of the advanced applications and techniques that leverage AI and data analytics for energy storage systems in renewable energy.
Program addresses emerging trends, interdisciplinary considerations, and practical aspects of implementing and optimizing energy storage systems for sustainable energy solutions.
Course Objectives
- Introduction to AI and Data Analytics in Renewable Energy Storage: Participants will gain an understanding of the role of AI and data analytics in optimizing the operation and management of renewable energy storage systems.
- Data Collection and Preprocessing for Storage Systems: The program will cover data collection methods, sensor technologies, and data preprocessing techniques for renewable energy storage systems.
- Machine Learning Algorithms for Energy Storage Optimization: Participants will learn about various machine learning algorithms used for optimizing energy storage operations, including supervised and unsupervised learning techniques.
- AI-Based State-of-Charge (SoC) and State-of-Health (SoH) Estimation: The program will focus on AI-driven approaches for accurate estimation of the state of charge and state of health of energy storage systems.
- Predictive Maintenance and Failure Detection: Participants will explore how AI and data analytics can be applied to predict maintenance needs and detect potential failures in renewable energy storage systems.
- Energy Forecasting for Energy Storage Planning: The program will cover energy forecasting models that use AI to predict energy demand and optimize energy storage system planning.
- Optimal Energy Storage Scheduling and Dispatch: Participants will learn how to use AI algorithms to optimize energy storage scheduling and dispatch for grid support and demand response.
- AI for Battery Management Systems (BMS): The program will address AI applications in battery management systems to enhance battery performance, longevity, and safety.
- Smart Charging and Discharging Strategies: Participants will explore AI-driven smart charging and discharging strategies for energy storage systems, including load shifting and peak shaving.
- Data-Driven Decision Making in Energy Storage: The program will focus on using data-driven insights from AI and analytics to make informed decisions in energy storage operations.
- AI-Enabled Grid Integration: Participants will understand how AI can support renewable energy storage integration into the grid for enhanced stability and reliability.
- Real-Time Monitoring and Remote Control: The program will cover real-time monitoring and remote control of renewable energy storage systems using AI-driven technologies.
Program Content
AI and Data Analytics Skills for Renewable Energy Storage Systems
Day 1
- Introduction to Energy Storage Systems in Renewable Energy
- AI-Driven Energy Storage Sizing and Optimization
Day 2
- Predictive Analytics for Energy Storage Operation and Control
- AI-Based Energy Management Systems for Energy Storage
- Data Analytics for Battery Health Monitoring and Predictive Maintenance
Day 3
- Optimization of Energy Storage System Integration in Grids
- Reinforcement Learning for Energy Storage System Control
Day 4
- AI-Enabled Energy Arbitrage and Market Participation
- Data-Driven Grid Services and Ancillary Services
- Integration of AI and Internet of Things (IoT) for Energy Storage Systems
Day 5
- Cybersecurity and Data Privacy for AI-Driven Energy Storage
- Case Studies and Real-World Applications
Day 6
- AI-Driven Optimization of Hybrid Energy Storage Systems
- Data Analytics for Energy Storage System Performance Evaluation
- AI-Based Forecasting for Renewable Energy and Load Profiles
Day 7
- Intelligent Energy Storage System Scheduling and Dispatch
- AI for Battery State-of-Health Estimation and Lifetime Prediction
- Data Analytics for Grid Congestion Management with Energy Storage
- AI-Driven Control of Community Energy Storage Systems
Day 8
- Advanced Data Visualization and Decision Support for Energy Storage Systems
- AI and Machine Learning for Energy Storage System Failure Prediction
- Integration of Energy Storage Systems in Microgrids
Day 9
- AI-Enabled Energy Storage System Asset Management
- Optimization of Energy Storage System Siting and Sizing
Day 10
- Policy and Regulatory Considerations for AI-Driven Energy Storage
Who Should Attend
The program is designed for engineers, data scientists, renewable energy professionals, energy storage specialists, and individuals interested in advancing their skills in AI and data analytics for renewable energy storage systems.
- AI and Data Analytics for Energy Storage Systems in Renewable Energy Professionals
- Energy Storage System Operators and Managers: Professionals responsible for the operation and management of energy storage systems, such as battery storage or pumped hydro storage, can learn about the application of AI and data analytics for optimizing storage system performance, improving energy efficiency, and enhancing system reliability.
- Renewable Energy Project Developers: Renewable energy project developers interested in incorporating energy storage technologies into their projects can gain insights into the benefits, economic viability, and technical considerations of integrating AI and data analytics with energy storage systems.
- Energy Analysts and Researchers: Energy analysts and researchers focusing on energy storage technologies and renewable energy integration can explore the application of AI and data analytics in analyzing energy storage data, optimizing storage operation, and developing predictive models for storage performance.
- Grid Operators and Utility Professionals: Grid operators and utility professionals involved in managing the electrical grid can learn about the use of AI and data analytics in integrating energy storage systems into the grid infrastructure, optimizing grid stability, and maximizing the benefits of renewable energy resources.
- Data Scientists and AI Specialists: Data scientists and AI specialists interested in the energy sector can explore the application of AI algorithms, machine learning techniques, and data analytics tools for energy storage optimization, predictive maintenance, and anomaly detection in renewable energy systems.
- Engineers and Technologists: Engineers and technologists working in the renewable energy and energy storage industries can enhance their knowledge of AI and data analytics for energy storage systems. This includes understanding optimization algorithms, data-driven modeling, and control strategies for improving storage performance and efficiency.
- Policy Makers and Government Officials: Policy makers and government officials involved in energy policies, regulations, and incentives for renewable energy and energy storage can gain insights into the role of AI and data analytics in supporting the deployment and integration of energy storage systems in the grid.
- Consultants and Advisors: Consultants and advisors specializing in renewable energy, energy storage, or data analytics can enhance their understanding of AI and data analytics techniques for energy storage systems. This knowledge can enable them to provide guidance and support to clients in optimizing energy storage solutions and leveraging data-driven insights.
- Researchers and Academics: Researchers and academics in fields such as renewable energy, data science, electrical engineering, and AI can explore the latest advancements and research trends in AI and data analytics for energy storage systems. They can contribute to the development of innovative approaches and methodologies in this field.
- Students and Future Professionals: Students pursuing degrees in energy, data science, electrical engineering, or related fields can gain a foundational understanding of AI and data analytics for energy storage systems. This knowledge can prepare them for careers in energy storage research, system optimization, data analysis, or policy-making.
Registration Form
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Registration Information
4 Week Professional Certification Training Program
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To register: Please send us an official letter confirming registration (on organizational letterhead). Also send us a completed registration form ?electronically fill-able is at- available at http://www.eurotraining.com/etl-reg-4w.doc You can request or registration form by Emailing regn@eurotraining.com and eurotraining@gmail.com
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For Program Fee Information Email: fees@eurotraining.com . Fees are Payable by Bank Transfer or Bank Draft. Fee information is also available at: http://www.eurotraining.com/fees.php .
Program Fee is
4 week (120 hrs)
At Dubai, Kuwait, New Delhi, Qatar £13,990 (USD $17,800) per participant.
At London, US Locations, Europe, Malaysia, Singapore £15,389 (USD $19,580) per participant.
Online eTraining Fee £6,000 (USD $7,500) per participant.
Accommodation is not included in Program fee. Special rates will be available at venue hotel for the class room training program participants.
Special discount of 10% is offered for participants who pay their fees at least 45 days before start of the program.
Refund will not be considered where the participants cancels his registration less than 3 weeks before start of the program. Alternate nominations will be allowed anytime before program start. In case of exceptional hardship or emergency participant may be allowed to attend at another location.
All participants are required to fill in Participant Information form - on first day of the program. Each program Undergoes Customization to Better Meet Participant Present and Future Career Needs. Please be prepared to let the Instructor/s know about your organization's Special Needs, Interests or Initiatives.
It is always useful for participants to bring their existing problems or case studies, work-process flow charts or job related problems for discussion - consideration will be at sole discretion of the program director/s.
Provisional Registration : You can make a provisional registration request by sending us an email with an official provisionsl registration request this will ensure we will reserve a seat for you for 14 days. After this you have 2 weeks to send us an official registration request. Provisional registration is automatically cancelled at the earlier of (1) 2 weeks after Provisional Confirmation if registration is not confirmed from your side (2) Two weeks before start of the program. We do request you to inform us ASAP you have decided either way. Please note All provisional registrations automatically cancel 2 weeks before program start unless confirmed.
Information required for Provisional Registration: Program Title, Location, Dates, Your Organization Name, Your Email Address, Your FAX No and your Mobile Number.