Challenge & Case-Based Modules

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 what exactly is 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.

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 long-term energy demand forecasting and the methods applied for this purpose. Also, the principles, methods and conditions limiting the development of the whole energy sector. 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 presented in detail. The module covers environmental and social aspects as well.

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 that allows to achieve higher efficiency and sustainability while using multi-energy sources, 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.