OVERVIEW

Sustainable energy and environmental systems are in general complex systems, characterized by a lot of data to be elaborated and dynamic systems to model for the aim of decision support. The course has the objective of providing the basis for simulation, optimization and control of energy and environmental systems, with specific reference to the following topics: smart grids, renewable energy, water resources management.

AIMS AND CONTENT

LEARNING OUTCOMES

The course has the objective to give basic knowledge of the methods for the definition and use of mathematical models and software tools for the planning, management and control of environmental and energy systems. The course will include methods related to: control, simulation, model predictive control, which will be described in a strict connection with applicative real case studies (renewable energy mix and polygenerative microgrids, material and energy recovery, natural resources management, etc.).

AIMS AND LEARNING OUTCOMES

The course provides basic knowledge related to simulation, optimization and control of energy and environmental systems, by the use of MATLAB-Simulink and LINGO software tools. The specific application areas are: optimal use of forest biomass for energy production, operational management of microgrids, water management and hydroelectric power plants.

Specifically, at the end of the course, students will be able to:

- acquire competences on specific application areas in the field of energy and environment;

- formalize (through mathematical equationa) decision problems;

- simulate, by the use of software tools, energy and environmental systems;

- use software tools for simulation and optimization purposes.

PREREQUISITES

The course includes an introduction to the main competences useful for the understanding of the lectures. Specifically, knowledge on the meaning of dynamic systems and minimization/maximization of a mathematical function is very important.

TEACHING METHODS

The course is characterized by lectures, examples and exercises in the computer room. Moreover, in field visits will be organized during the course, in order to undersant the practical significance of the methods studied during lectures. Applicative examples will be given in relation to methods and implemented by the use of softwre tools (Matlab/Simulink, Lingo). During the course, it will be given the possibility to prepare a report on a specific case study to present during the oral exam.

SYLLABUS/CONTENT

1. Information architectures, systems analysis, control, optimization for environmental and energy systems.
2. Introduction to mathematical models: simulation, optimization, control.
3. Applicative examples: renewable and sustainable energy mix at different spatial scales (building, microgrid, District, etc.), water resources, agro-forest biomass.
4. Techniques for discrete time control. Model Predictive Control. 
5. Application to control problems in the environmental and energy field.
6. Software tools: introduction to MATLAB tools that are of interest for the course.
7. Introduction to available tools for the planning and control of sustainable energy systems and polygenerative microgrids

RECOMMENDED READING/BIBLIOGRAPHY

Dispense e slides del corso a cura di Michela Robba e Riccardo Minciardi

Harold Klee, Randal Allen-Simulation of Dynamic Systems with MATLAB and Simulink, 2011

C. Vercellis: Modelli e decisioni, Progetto Leonardo, 1997

Jorgesen, Bendoricchio. Fundamentals of Ecological Modelling

TEACHERS AND EXAM BOARD

Exam Board

MICHELA ROBBA (President)

RICCARDO MINCIARDI

ROBERTO SACILE

LESSONS

Class schedule

SIMULATION OF ENERGY AND ENVIRONMENTAL SYSTEMS

EXAMS

EXAM DESCRIPTION

The exam is characterized by an oral examination with three questions. In the case the student has prepared a small project (report on a specific applicative case), one question is about the project.

ASSESSMENT METHODS

The details on the methods of preparation of the exam will be provided during lectures. The oral examination will be related to the models, methods and tools presented during the course with the aim of evaluating the student's knowledge and capacity of formalizing and implementing simulation and optimization models. As regards, the report, the student should be able to discuss obtained results.

Exam schedule

FURTHER INFORMATION

Pre-requisites :

None