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Peter Palensky,
Simon Tindemans,
Pedro P. Vergara,
Kees Vuik,
Marieke Kootte,
Jochen Lorenz Cremer,
and
Alexandru Stefanov
This course will teach you how to digitalize the 'conventional' grid and which digital technologies you can use for this, including but not limited to, AI, machine learning, blockchain and computer simulations.
Read more
This course will teach you how to digitalize the 'conventional' grid and which digital technologies you can use for this, including but not limited to, AI, machine learning, blockchain and computer simulations.
Read more
This course will teach you how to digitalize the 'conventional' grid and which digital technologies you can use for this, including but not limited to, AI, machine learning, blockchain and computer simulations.
Even though the power grid has been the main driver of the rapid advancement of technology in the past decades, the engineering of the grid is outdated by today's standards. Equipment is still hardwired and analogue, there is limited data acquisition, and many control actions are performed manually. Subsequently, it becomes harder to ensure similar system quality and efficient operations when more renewables are added to the grid. The next big leap, therefore, is to revamp and digitalize the energy system. We invited five prominent industry leaders to share industry perspectives, case studies and applications of digitalization in the fields of Grid Operations, Electric Power Systems, Power Distribution, Electrical Systems, Control Systems and Cybersecurity, but also in Consultancy and Software Development. Our guest speakers are: Philip Gladek (CEO of Spectral), Bas Kruimer (Business Director Digital Grid Operations at DNV), Martin Wevers (Grid Planner at TenneT), Evelyn Heylen (Head of research at Centrica) and Antoine Marot (Lead AI Scientist at RTE). You will also get hands-on experience through solving an optimal scheduling problem, noting the differences between different numerical simulation methods and applying machine learning to predict system overloads.
This course is aimed at professionals in the energy industry who want to broaden their perspective and discover alternative approaches to energy integration in an intelligent way such as:- grid operators, electrical systems managers, control systems managers, power engineers- cybersecurity consultants, software developers, artificial intelligence managers/ scientists, energy consultants- project managers, planners, policy makers etc.Any other enthusiasts with the desire to learn more about current practices of the power grid, novel digital technologies and trends to deploy them can also enrol in this course.
"At DNV, our vision is to be a trusted voice to tackle global transformations. The energy transition is vital to decelerate climate change. Integrating energy systems in an intelligent way is a critical skill for the engineers, project managers, planners, policymakers, and scientists of the future.The course “Digitalization of intelligent and integrated energy systems” comes at the right time to tackle the challenges and complexity of today’s energy systems. It provides you with a powerful framework to digitalize energy systems by using AI, machine learning, simulations, digital twins and sheds light on cyber security matters. It helps you to integrate electric cars, heat, gas and electricity into the energy system. I would highly recommend this innovative course to everyone who is interested in the digital transformation of the energy system."
Bas Kruimer, Business Director Digital Grid Operations, Energy Systems, DNV
Register for this course and see more details by visiting:
OpenCourser.com/course/fquwkj/digitalization
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What's inside
Learning objectives
- To recognize the digital transformation in the energy sector, identify challenges and solutions, and evaluate its impact on both the power system and society itself.
- To analyse the it-ot infrastructure and protocols of the digitalized power system, identify vulnerabilities and learn how to mitigate and recover from these cyber threats.
- To compare the different model types used for numerical simulations of energy systems and evaluate the influence of individual parameters and system models on the simulation performance.
- To explain the different objectives of decision-making in energy systems, and the influence of different units and their properties on the decision making.
- To apply and evaluate machine learning methods for prediction and control in energy systems
- To recognize the digital transformation in the energy sector, identify challenges and solutions, and evaluate its impact on both the power system and society itself.
- To analyse the it-ot infrastructure and protocols of the digitalized power system, identify vulnerabilities and learn how to mitigate and recover from these cyber threats.
- To compare the different model types used for numerical simulations of energy systems and evaluate the influence of individual parameters and system models on the simulation performance.
- To explain the different objectives of decision-making in energy systems, and the influence of different units and their properties on the decision making.
- To apply and evaluate machine learning methods for prediction and control in energy systems
Syllabus
Module 0: Introduction
Module 1: The Digital Transformation of the Energy System
This week, you will learn how digitalization and the digital transformation is penetrating the electricity grid and reinventing the way we operate our power system. We will discuss the following elements:
Read more
Syllabus
Module 0: Introduction
Module 1: The Digital Transformation of the Energy System
This week, you will learn how digitalization and the digital transformation is penetrating the electricity grid and reinventing the way we operate our power system. We will discuss the following elements:
Read more
Digitalization and digital transformation
Smart cities
Digital twins
Transactive energy
Blockchain
Data ownership in the digital power system
The CEO of Spectral will tell you how they are leveraging the digital transformation to create new business opportunities.
Finally, you will investigate how digitalization is penetrating and impacting your working environment.
Your instructors of this week are:
Peter Palensky
Philip Gladek (Spectral)
Module 2: Computational Methods for Energy Networks
This week will present numerical simulators, computer programs that allow simulations of power system behavior. You will learn the following:
What is numerical simulation, and why do we need it?
What methods are there for simulating the electrical power system?
How can we couple different energy domains?
How do different modeling approaches impact simulation performance?
An industry expert from TenneT, the Dutch transmission system operator, will explain the role of numerical simulations on one of their key activities, grid planning.
There are multiple simulation exercises where you will be able to see for yourself how different simulation types and methods, solver settings, and network models impact the performance and result of the numerical simulation.
Cornelis Vuik
Marieke Kootte
Martin Wevers (TenneT)
Module 3: Decision Support in Integrated Energy Systems
The power system has different types of units, and operators have distinct goals when operating their system. Traditionally, this was low cost, but nowadays, a greater emphasis is placed on emissions and reliability. However, these are at a trade-off with each other, meaning that no golden combination exist. This week, you will be taught:
What trade-offs there are in energy systems.
What influence different units and their properties have on decision objectives.
How capacity planning and other methods can be used in decision making.
How to use the optimal scheduling problem to meet your decision objectives.
You will also get to see how Centrica, a British multinational energy and services company, is modelling battery systems to support the grid.
At the end of the week, you will get hands-on experience with the optimal scheduling problem. You will see how the optimal schedule of a small system changes with different model parameters and investigate how to achieve some objectives.
Simon Tindemans
Pedro P. Vergara
Evelyn Heylen (Centrica)
Module 4: AI-Based Data and Machine Learning Approaches
This week, you will learn how machine learning can be applied in the energy system, allowing for more accurate predictions and automatic control of the power system. We will discuss the following topics:
Machine learning basics
Forecasting with regression models, ensemble methods and neural networks
Dynamic security assessment with classification and decision trees
Identification of customer types using k-means clustering
Anomaly detection using auto-encoders
Surrogate modeling
Learning control actions with reinforcement learning
Moreover, we will see two perspectives on the future of machine learning in the power grid, one academic and one from an employee of RTE, the French transmission system operator. The industry speaker will also discuss how artificial intelligence is already being deployed in and around the grid.
At the end of the week, you will get to see how this all works. You will predict the overloading of a cable using the power measurements of several households.
Jochen Lorenz Cremer
Antoine Marot (RTE)
Module 5: Cybersecurity of Digital Energy Systems
Although the digital transformation creates many opportunities, it also makes the grid more vulnerable to cyber attacks. This week, you will learn about the cybersecurity of digital energy systems. The following aspects will be highlighted:
What is cybersecurity?
How is the IT-OT network of the power grid organized?
How does a digital substation work?
What communication protocols are used, and how can these be exploited?
How can we analyze the impact of cyber attacks on the power grid?
What can we do to mitigate these cyber threats?
How can blockchain help to mitigate Internet-of-Things based cyber attacks?
The business director of digital grid operations at DNV will explain how the grid is evolving into a Data Machine because of digitalization. Moreover, he will highlight how you can prepare for the future by improving your cybersecurity.
To conclude this week, you will be tasked with analyzing several cybersecurity elements of a case study.
Alexandru Stefanov
Raifa Akkaoui
Bas Kruimer (DNV)
Module 6: Next Steps
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches the fundamentals of digital transformation in the energy system which is paramount in industry today
Instructed by five prominent industry leaders who share real-world perspectives and applications in digitalization
Provides hands-on experience through problem-solving and application of machine learning in energy systems
Covers the technical infrastructure, cybersecurity, and data analysis methods used in the digitalized power system
Suitable for professionals in the energy industry, consultants, software developers, and policy makers seeking to broaden their understanding of digitalization in energy systems
Save this course
Save Digitalization of Intelligent and Integrated Energy Systems to your list so you can find it easily later:
Save
Save
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Digitalization of Intelligent and Integrated Energy Systems with these
activities:
Review of Power System Analysis
Show steps
Review a classic textbook on power system analysis to refresh your understanding of fundamental concepts and gain insights into advanced topics.
View
Power System Analysis and Design, SI Edition
on Amazon
Show steps
-
Read selected chapters covering topics relevant to the course content.
-
Summarize key concepts and equations in your own words.
-
Solve practice problems to test your comprehension.
-
Discuss the book's content with classmates or colleagues.
Power Systems Simulators Practice
Show steps
Practice using power systems simulators to gain hands-on experience in simulating power system behavior and evaluating the impact of different parameters and models.
Show steps
-
Familiarize yourself with a power systems simulator software, such as PSS/E or PowerFactory.
-
Load a simple power system model into the simulator.
-
Run simulations to observe the system's behavior under different operating conditions.
-
Analyze the simulation results and identify key performance indicators.
Cybersecurity Training Tutorials
Show steps
Complete online tutorials and training courses to enhance your knowledge of cybersecurity threats and mitigation strategies.
Browse courses on
Cybersecurity
Show steps
-
Identify relevant tutorials or courses from reputable sources.
-
Follow the instructions and complete the tutorials or courses.
-
Apply the learned concepts and techniques to analyze cybersecurity vulnerabilities in the power grid.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Discussion Forum Participation
Show steps
Engage in discussions with peers to exchange insights, clarify concepts, and deepen your understanding of course material.
Show steps
-
Regularly participate in the course discussion forums.
-
Post thoughtful questions and responses.
-
Engage with other students' contributions.
Energy System Optimization Project
Show steps
Develop a project to optimize the operation of an energy system, considering factors such as cost, emissions, and reliability.
Show steps
-
Define the scope and objectives of your optimization project.
-
Gather data and develop a model of the energy system.
-
Formulate an optimization problem to minimize or maximize desired objectives.
-
Solve the optimization problem using suitable algorithms or software.
-
Analyze and interpret the optimization results.
Energy Grid Cybersecurity Assessment Report
Show steps
Conduct a cybersecurity assessment of an energy grid and create a report documenting the findings and recommendations.
Browse courses on
Cyber Threat Analysis
Show steps
-
Gather information about the energy grid and its components.
-
Identify potential cybersecurity threats and vulnerabilities.
-
Analyze the impact of identified threats and vulnerabilities.
-
Develop recommendations for mitigating cybersecurity risks.
-
Write a comprehensive cybersecurity assessment report.
Energy Industry Conference Attendance
Show steps
Attend industry conferences and workshops to stay updated on the latest trends and developments in energy systems digitalization.
Show steps
-
Identify relevant energy industry conferences and workshops.
-
Register and attend selected events.
-
Take notes and gather insights from presentations and discussions.
-
Engage with industry experts and potential collaborators.
Review of Power System Analysis
Show steps
Review a classic textbook on power system analysis to refresh your understanding of fundamental concepts and gain insights into advanced topics.
View
Power System Analysis and Design, SI Edition
on Amazon
Show steps
Show steps
Show steps
- Read selected chapters covering topics relevant to the course content.
- Summarize key concepts and equations in your own words.
- Solve practice problems to test your comprehension.
- Discuss the book's content with classmates or colleagues.
Power Systems Simulators Practice
Show steps
Practice using power systems simulators to gain hands-on experience in simulating power system behavior and evaluating the impact of different parameters and models.
Show steps
Show steps
Show steps
- Familiarize yourself with a power systems simulator software, such as PSS/E or PowerFactory.
- Load a simple power system model into the simulator.
- Run simulations to observe the system's behavior under different operating conditions.
- Analyze the simulation results and identify key performance indicators.
Cybersecurity Training Tutorials
Show steps
Complete online tutorials and training courses to enhance your knowledge of cybersecurity threats and mitigation strategies.
Browse courses on
Cybersecurity
Show steps
Show steps
Show steps
- Identify relevant tutorials or courses from reputable sources.
- Follow the instructions and complete the tutorials or courses.
- Apply the learned concepts and techniques to analyze cybersecurity vulnerabilities in the power grid.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Discussion Forum Participation
Show steps
Engage in discussions with peers to exchange insights, clarify concepts, and deepen your understanding of course material.
Show steps
Show steps
Show steps
- Regularly participate in the course discussion forums.
- Post thoughtful questions and responses.
- Engage with other students' contributions.
Energy System Optimization Project
Show steps
Develop a project to optimize the operation of an energy system, considering factors such as cost, emissions, and reliability.
Show steps
Show steps
Show steps
- Define the scope and objectives of your optimization project.
- Gather data and develop a model of the energy system.
- Formulate an optimization problem to minimize or maximize desired objectives.
- Solve the optimization problem using suitable algorithms or software.
- Analyze and interpret the optimization results.
Energy Grid Cybersecurity Assessment Report
Show steps
Conduct a cybersecurity assessment of an energy grid and create a report documenting the findings and recommendations.
Browse courses on
Cyber Threat Analysis
Show steps
Show steps
Show steps
- Gather information about the energy grid and its components.
- Identify potential cybersecurity threats and vulnerabilities.
- Analyze the impact of identified threats and vulnerabilities.
- Develop recommendations for mitigating cybersecurity risks.
- Write a comprehensive cybersecurity assessment report.
Energy Industry Conference Attendance
Show steps
Attend industry conferences and workshops to stay updated on the latest trends and developments in energy systems digitalization.
Show steps
Show steps
Show steps
- Identify relevant energy industry conferences and workshops.
- Register and attend selected events.
- Take notes and gather insights from presentations and discussions.
- Engage with industry experts and potential collaborators.
Career center
Learners who complete Digitalization of Intelligent and Integrated Energy Systems will develop knowledge and skills
that may be useful to these careers:
Grid Operator
Grid Operator
Grid Operators are responsible for the safe and reliable operation of the power grid. This course may be useful for Grid Operators as it provides an overview of the digital transformation of the energy system, including the challenges and opportunities it presents. The course also discusses the use of numerical simulations, decision support tools, and machine learning methods in energy systems.
Power Systems Analyst
Power Systems Analyst
Power Systems Analysts study the behavior of power systems and develop solutions to improve their performance. This course may be useful for Power Systems Analysts as it provides an overview of the digital transformation of the energy system, including the challenges and opportunities it presents. The course also discusses the use of numerical simulations, decision support tools, and machine learning methods in energy systems.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. This course may be useful for Machine Learning Engineers as it provides an overview of machine learning and artificial intelligence, which are important tools for data analysis. The course also discusses how to apply machine learning methods to energy systems, such as forecasting, dynamic security assessment, and anomaly detection.
Electrical Engineer
Electrical Engineer
Electrical Engineers design, develop, test, and supervise the installation of electrical systems and components. This course may be useful for Electrical Engineers as it provides an overview of the digital transformation of the energy system, including the challenges and opportunities it presents. The course also discusses the use of numerical simulations, decision support tools, and machine learning methods in energy systems.
Research Scientist
Research Scientist
Research Scientists conduct research and develop new technologies. This course may be useful for Research Scientists as it provides an overview of the digital transformation of the energy system, including the challenges and opportunities it presents. The course also discusses the use of numerical simulations, decision support tools, and machine learning methods in energy systems.
Systems Engineer
Systems Engineer
Systems Engineers design, develop, and maintain complex systems. This course may be useful for Systems Engineers as it provides an overview of the digital transformation of the energy system, including the challenges and opportunities it presents. The course also discusses the use of numerical simulations, decision support tools, and machine learning methods in energy systems.
IT Architect
IT Architect
IT Architects design, develop, and maintain the IT infrastructure of organizations. This course may be useful for IT Architects as it provides an overview of the digital transformation of the energy system, including the challenges and opportunities it presents. The course also discusses the IT-OT network, communication protocols, and cybersecurity threats in energy systems.
Energy Consultant
Energy Consultant
Energy Consultants provide advice and guidance to businesses and organizations on how to manage their energy consumption and costs. This course may be useful for Energy Consultants as it provides an overview of the digital transformation of the energy system, including the challenges and opportunities it presents. The course also discusses the use of numerical simulations, decision support tools, and machine learning methods in energy systems.
Renewable Energy Engineer
Renewable Energy Engineer
Renewable Energy Engineers design, develop, and install renewable energy systems. This course may be useful for Renewable Energy Engineers as it provides an overview of the digital transformation of the energy system, including the challenges and opportunities it presents. The course also discusses the use of numerical simulations, decision support tools, and machine learning methods in energy systems.
Software Developer
Software Developer
Software Developers design, develop, and maintain software applications. This course may be useful for Software Developers as it provides an overview of the digital transformation of the energy system, including the challenges and opportunities it presents. The course also discusses the IT-OT network, communication protocols, and cybersecurity threats in energy systems.
Project Manager
Project Manager
Project Managers plan, organize, and execute projects. This course may be useful for Project Managers as it provides an overview of the digital transformation of the energy system, including the challenges and opportunities it presents. The course also discusses the use of numerical simulations, decision support tools, and machine learning methods in energy systems.
Data Scientist
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course may be useful for Data Scientists as it provides an overview of machine learning and artificial intelligence, which are important tools for data analysis. The course also discusses how to apply machine learning methods to energy systems, such as forecasting, dynamic security assessment, and anomaly detection.
Energy Policy Analyst
Energy Policy Analyst
Energy Policy Analysts develop and analyze policies that affect the production, distribution, and consumption of energy. This course may be useful for Energy Policy Analysts as it provides an overview of the digital transformation of the energy system, including the challenges and opportunities it presents. The course also discusses the use of numerical simulations, decision support tools, and machine learning methods in energy systems.
Cybersecurity Analyst
Cybersecurity Analyst
Cybersecurity Analysts are responsible for protecting computer networks and systems from unauthorized access, use, disclosure, disruption, modification, or destruction. This course may be useful for Cybersecurity Analysts as it provides an overview of the cybersecurity of digital energy systems, including the IT-OT network, communication protocols, and potential vulnerabilities. The course also discusses how to analyze the impact of cyber attacks on the power grid and how to mitigate these threats.
Environmental Engineer
Environmental Engineer
Environmental Engineers develop solutions to environmental problems, such as air and water pollution, hazardous waste management, and climate change. This course may be useful for Environmental Engineers as it provides an overview of the digital transformation of the energy system, including the challenges and opportunities it presents. The course also discusses the use of numerical simulations, decision support tools, and machine learning methods in energy systems.
For more career information including salaries, visit:
OpenCourser.com/course/fquwkj/digitalization
Reading list
We've selected 11 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Digitalization of Intelligent and Integrated Energy Systems.
This textbook classic in the field of power systems analysis and design. It provides comprehensive coverage of the fundamental concepts and principles of power systems, as well as detailed treatment of advanced topics such as power system stability, control, and protection.
Provides a comprehensive overview of the digitalization of energy systems. It discusses the challenges and opportunities of digitalization, as well as the technologies and applications that are being used to digitalize energy systems.
Save
Provides a comprehensive overview of the various aspects of power quality, including voltage sags and swells, harmonics, and transients. It valuable resource for engineers and students who want to learn more about power quality issues and mitigation.
Provides a comprehensive overview of data analytics for energy systems. It discusses the challenges and opportunities of data analytics, as well as the technologies and applications that are being used to analyze energy data.
This handbook provides comprehensive coverage of the design, operation, and maintenance of electric power distribution systems. It valuable resource for engineers and students who want to learn more about electric power distribution.
This textbook provides comprehensive coverage of the fundamental concepts and principles of power systems analysis and design. It valuable resource for engineers and students who want to learn more about power systems.
Provides a comprehensive overview of optimization of energy systems. It discusses the challenges and opportunities of optimization, as well as the technologies and applications that are being used to optimize energy systems.
Provides a comprehensive overview of energy systems modeling and optimization. It discusses the challenges and opportunities of modeling and optimization, as well as the technologies and applications that are being used to model and optimize energy systems.
Provides a comprehensive overview of control of energy systems. It discusses the challenges and opportunities of control, as well as the technologies and applications that are being used to control energy systems.
Provides a comprehensive overview of simulation of energy systems. It discusses the challenges and opportunities of simulation, as well as the technologies and applications that are being used to simulate energy systems.
This handbook provides comprehensive coverage of all aspects of electric power engineering. It valuable resource for engineers and students who want to learn more about electric power engineering.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/fquwkj/digitalization
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Effort
3 to 6 hours per week for 6 weeks
Level
Introductory
Via
edX
Institution
Delft University of Technology
Instructors
Peter Palensky
Simon Tindemans
Pedro P. Vergara
Kees Vuik
Marieke Kootte
Jochen Lorenz Cremer
Alexandru Stefanov
Session
July 30, 2024
- July 1, 2025
Language
English
Transcripts
English
Español
Français
Português
Deutsch
中文
العربية
हिंदी
Türkçe
తెలుగు
Bahasa Indonesia
Kiswahili
This course belongs to a
collection
called
Intelligent and Integrated Energy Systems. It's comprised of four courses:
- Digitalization of Intelligent and Integrated Energy Systems (viewing)
- Policy and Management of Modern Energy Systems
- Technology of Intelligent and Integrated Energy Systems
- Business Implications of Intelligent and Integrated Energy Systems
Good to know
Teaches the fundamentals of digital transformation in the energy system which is paramount in industry today
Instructed by five prominent industry leaders who share real-world perspectives and applications in digitalization
Provides hands-on experience through problem-solving and application of machine learning in energy systems
Covers the technical infrastructure, cybersecurity, and data analysis methods used in the digitalized power system
Suitable for professionals in the energy industry, consultants, software developers, and policy makers seeking to broaden their understanding of digitalization in energy systems
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