Smart Grid Digitalization and Integration
This course is part of Intelligent and Integrated Energy Systems.
Master the digital transformation of energy systems in this comprehensive course. Explore cutting-edge technologies including AI, machine learning, blockchain, and digital twins for modern power grids. Learn to analyze IT-OT infrastructure, implement cybersecurity measures, and apply numerical simulations for energy systems. Gain practical experience with optimal scheduling, machine learning applications, and system security assessment. Industry experts share real-world case studies and applications in grid operations, power distribution, and control systems.
4.2
(9 ratings)
Instructors:
English
Arabic, German, English, 9 more
Powered by
What you'll learn
Understand digital transformation in energy systems and evaluate its societal impact
Analyze IT-OT infrastructure and implement cybersecurity measures for power systems
Apply numerical simulation methods for energy system modeling and analysis
Implement decision-making strategies for integrated energy systems
Master machine learning applications for prediction and control
Develop expertise in cybersecurity threat assessment and mitigation
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
Closed caption
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
Created by
Provided by
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 7 modules in this course
This course provides comprehensive coverage of energy system digitalization, focusing on the integration of modern digital technologies into power grids. Students learn about digital transformation in the energy sector, cybersecurity for power systems, computational methods for energy networks, and AI-based approaches. The curriculum includes practical applications of machine learning, optimal scheduling, and security assessment. Topics range from smart cities and digital twins to blockchain implementation and cyber threat mitigation.
Introduction
Module 1
The Digital Transformation of the Energy System
Module 2
Computational Methods for Energy Networks
Module 3
Decision Support in Integrated Energy Systems
Module 4
AI-Based Data and Machine Learning Approaches
Module 5
Cybersecurity of Digital Energy Systems
Module 6
Next Steps
Module 7
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Intelligent and Integrated Energy Systems
Instructors
6 Courses
Distinguished Expert in Numerical Analysis and High Performance Computing
Kees Vuik serves as a Professor of Numerical Analysis at Delft University of Technology since 2007, where he has established himself as a leading authority in computational mathematics. After completing his MSc from TU Delft and a brief stint at Philips Research Laboratories, he earned his PhD from Utrecht University in 1988, focusing on Moving Boundary (Stefan) Problems. His research spans discretization of partial differential equations, iterative methods, and high performance computing, with over 200 publications to his credit. As coordinator of the international Master Computer Simulations for Science and Engineering (COSSE) double degree program, he has significantly influenced computational science education. His academic impact is reflected in his impressive citation metrics, with over 10,893 citations and an h-index of 51. He teaches various courses, including the foundational Modelling course for first-year Applied Mathematics Bachelor students, where he incorporates real-world examples from his extensive industry collaborations. His recent work includes co-authoring a comprehensive textbook on "Numerical Methods for Ordinary Differential Equations" and leading research in numerical analysis applications for modern computational challenges. His expertise in iterative solution methods combined with high performance computing has made him a sought-after collaborator for both academic and industrial projects.
9 Courses
Professor at Delft University of Technology
Professor Peter Palensky serves as head of the Electric Sustainable Energy department and chair of Intelligent Electrical Power Grids (IEPG) section at TU Delft, while also leading the Delft Energy Initiative and serving as scientific director of the PowerWeb Institute. His illustrious career spans multiple prestigious institutions, including positions as Principal Scientist at the Austrian Institute of Technology, associate Professor at the University of Pretoria, and researcher at Lawrence Berkeley National Laboratory. His research focuses on complex and integrated energy systems, particularly developing methods for intelligent power grids using hybrid numerical models and digital twins. He currently leads groundbreaking work in smart electricity systems, cyber-physical energy systems, and grid dynamics, while teaching courses in Energy Efficiency and Intelligent Electrical Power Grids. As Editor in Chief of the IEEE Industrial Electronics Magazine and associate editor for several IEEE publications, he maintains a significant influence in the field. His expertise encompasses smart grids, demand response systems, and cyber security in power systems, with his publications garnering over 10,000 citations, demonstrating his substantial impact on the field of intelligent electrical power systems and sustainable energy solutions.
Testimonials
Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.
Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.