Challenge & Case-Based Modules
The three challenge and case-based modules have been developed, focusing on artificial intelligence in power systems, economic operation and the planning aspect of smart grids. All six universities from the SMAGRINET Consortium integrated one of the following three modules into their curriculum and implemented it during the project's lifetime. Learn more about each one of them below:”
The module consists of a short introduction into artificial intelligence (AI) and why it is taking off now, data representation, its mapping from high to low-dimensional spaces, and visualization. Linear and nonlinear models focus on classification and regression tasks, as well as assumptions, polynomial models and decision trees. The module also provides insight on deep learning (DL) and unsupervised learning, defining learning hierarchical representations, the topology of deep convolutional neural networks, clustering and deep auto-encoders. Generalization, model assessment and selection expand on cross-validation, K-fold cross-validation, model comparison and selection, model bias and model variance. Several lectures are focused on various applications, such as demand management, consumer insights, participation in energy markets and cyber security.
The first pilot at both participating universities was conducted in Jan 2020 and Nov-Dec 2020. After an evaluation, the second one was implemented in Oct-Dec 2020 and Oct-Nov 2021. Further, KTU decided to continue offering the module in Sep-Dec 2021.
Artificial Intelligence in a Smart Grid with Prosumers
A cross-curricular module combining economics, technology and law. This module provides an overview of current energy policy principles, goals and objectives. Energy sector planning is based on long-term energy demand forecasting, so the module first analyzes the specifics of this topic and the methods applied for this purpose. Further, the principles, methods and conditions limiting the development of the whole energy sector are in focus. Cost-benefit analysis and risk identification and evaluation are also presented. Energy sector regulation, applied methods and other aspects of regulation, electricity market pricing, electricity financial markets and risk management are discussed in detail. The module covers environmental and social aspects as well.
The first pilot at both participating universities was conducted in Feb-Apr 2020. After an evaluation, the second was implemented in Sep-Dec 2020 and Feb-Mar 2021. Further, TalTech decided to continue offering the module in Sep-Dec 2021.
Economic Operation and Societal Challenges
The module combines essentials subjects on modern and smart electrical system operation and control. It introduces general characteristics of a distributed network with distributed renewable generation, virtual power plants and optimization problems. Analysis of the load and distributed generation forecasting problem is based on time series forecasting techniques and ARIMA models. Allocation of distributed generation focuses on traditional and coordinated voltage control in a distribution network as well as the state estimation techniques and issues The module’s lectures include topics on energy storage technologies and multi-energy sources, which allows achieving higher efficiency and sustainability. Moreover, electric vehicles’ impact on network operation, power quality problems and their solutions, methods of testing and diagnostics of electrical equipment, planning of distributed network expansion, power flow calculation methods, as well as security aspects in distribution systems are covered.
The first pilot at both participating universities was conducted in Jan 2020 and Sep 2020. After an evaluation, the second one was implemented in Jan 2021 and Feb 2021. Further, TUB decided to continue offering the module in Jan and Feb 2022.
Connection Planning in Smart Grids