Description
Objectives
Understand the concepts to develop new solutions for energy services Collect, store, process and analyse energy systems data; Implement algorithms to extract new knowledge from energy data (statistical analysis,machine learning) Develop new solutions, like forecast energy consumption, segment energy users, fault identification, data representation.
Syllabus
1 – Introdution to energy systems. Review of concepts and definitions. Definitions of energy services 2 - Introdution to data science concepts (Big Data, IOT, Machine Learning, etc) 3 – Energy data and related variables acquisition and processing. 4 – Introduction to data bases. Development of an energy data base. 5 – Data pre-processing and exploratory data analysis. 6 - Algorithms for knowledge extraction 6 – Algorithms for energy consumption forecast 7 – Energy data representation 8 – Development of new tools for energy services (different applications)
Prerequisites
Thermodynamics, Electromagnetism, Computational Mathematics, Programming
Cross Competence Component
Critical and Innovative Thinking (e.g. criativity, strategic thinking, problem solving approaches) Interpersonal skills (e.g. oral presentations, organizational and communication skills, team work, etc.)
Laboratorial Component
No laboratorial component
Programming And Computing Component
Using an IDE (Integrated Development Environment), Algorithms, Programs, Analyse of the algorithm computational complexity
Ethical Principles
All members of a group are responsible for the group’s work In any assessment, every student shall honestly disclose any help received and sources used. In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.