The course aims to provide basic knowledge for the modelling, simulation and control of dynamic systems, with particular reference to sustainable energy systems (polygeneration microgrids, intelligent buildings, electric vehicles, renewable energy). Flexible software tools (including MATLAB) will be used in relation to specific application examples.
The course covers the basic methodological tools for modeling, simulation and control of sustainable energy systems related to the following application areas: smart grid, renewable energy, water resources, sustainable production systems, energy communities and sustainable districts.
The course aims to provide basic knowledge about the methods for the definition and use of mathematical models and software tools (MATLAB-Simulink, LINGO) for the purpose of the representation, simulation and control of sustainable energy systems. The course will cover the basic methods for the representation of dynamic systems also on the basis of experimental data, with the aim of developing techniques to improve performance and to allow real-time control. The methods will be described in close connection with specific application case studies: modeling and control of renewable energy plants (use of agro-forest biomass for energy production, hydroelectric, wind, photovoltaic plants), modeling, automation and control of polygenerative networks and energy communities.
The transversal skills on which we intend to focus are:
- personal competence
- social competence
- ability to learn to learn proficiency in project creation
- expertise in project management
Basic knowledge related to systems’ analysis and modelling.
The course includes lectures, seminars and computer exercises. In particular, as regards transversal skills, exercises (on and off the computer) will be carried out in the classroom, encouraging work in different groups in order to promote personal and social skills and project development.
Working students and students with DSA, disability or other special educational needs certification are advised to contact the teacher at the beginning of the course to agree on teaching and exam methods which, in compliance with the teaching objectives, take into account individual ways of learning
Information architectures
Introduction to problems concerning the analysis, control, and simulation of sustainable energy systems.
Integration of mathematical models into computer architectures for real-time control.
Application examples: smart grids, renewable energies, water resources, control and automation of industrial systems and energy communities.
Simulation and identification of models.
Discrete-time control techniques.
PID controllers
Predictive control.
Application to control problems of sustainable energy systems.
Software tools: introduction to the MATLAB, SIMULINK and LINGO environment tools of interest for the course.
Activities "in field" and seminars useful for the application of the studied methods and for collaboration with companies.
Course material by Michela Robba that includes also the link to bibliographic material
Analisi e controllo di sistemi dinamici, un laboratorio informatico, Finzi, Visioli, Volta, 1996
Applied Data Analysis and Modeling for Energy Engineers and Scientists-Springer (2011), T. Agami Reddy-
Multivariable System Identification-From Observations to Models, R. Guidorzi ,2003
Ricevimento: It is possible to book an appointment writing an email to: michela.robba@unige.it
LOREDANA MAGISTRI (President)
ALBERTO TRAVERSO
ARISTIDE FAUSTO MASSARDO (President Substitute)
MICHELA ROBBA (President Substitute)
GIULIO FERRO (Substitute)
https://corsi.unige.it/en/corsi/11438
Oral Examination and discussion of computer exercises done during the course. Students with SLD, disability or other regularly certified special educational needs are advised to contact the instructor to agree on teaching and examination methods that, in compliance with the course objectives, take into account the individual learning requirements.
The verification methods concern: 1. During the oral exam, the teacher will define a system that the student will have to characterize from the point of view of simulation and optimization either on the blackboard or on another IT support or otherwise. 2. During the oral exam, general questions will be asked to verify knowledge of point 1, and to evaluate reasoning ability 3. During the oral exam, a project carried out in groups and delivered before the exam will be evaluated. The evaluation criteria concern: - correctness of the project report and written and oral responses - appropriate vocabulary and safety in exposition
