Information updated until 30/06/2026 CODE 86667 ACADEMIC YEAR 2026/2027 CREDITS 5 cfu anno 2 ENERGY ENGINEERING 11917 (LM-30 R) - SAVONA SCIENTIFIC DISCIPLINARY SECTOR ING-IND/33 LANGUAGE English TEACHING LOCATION SAVONA SEMESTER 1° Semester OVERVIEW The teaching unit provides knowledge for the development of simulation and optimisation models of complex energy and electrical systems: distributed generation plants, battery storage systems, multi-energy microgrids and nanogrids, power distribution networks, electric vehicle charging hubs, energy communities, prosumer buildings. Mathematical models are developed in the classroom and implemented using computer tools. AIMS AND CONTENT LEARNING OUTCOMES The teaching unit is designed to provide the students the theoretical and methodological skills necessary for the development of power system simulation and optimization models. The unit aims to provide the students the capabilities to model different power system technologies in off-design and transient operating conditions, through the use of dedicated software, and to develop optimization mathematical models for the design and the operation of energy communities, microgrids, nanogrids, and smart charging infrastructures for electric vehicles. AIMS AND LEARNING OUTCOMES The main purpose of the teaching unit is to provide students competences on the development of power system optimization and simulation models, with a particular focus on distributed generation, smart grids/microgrids/nanogrids, power distribution networks, energy communities and smart electric mobility systems. Students will acquire skills to develop mathematical models for the simulation of the behaviour of both power plants, in off-design/transient conditions, and electric power networks. Moreover, students will be able to develop optimization models to design and daily operate prosumer buildings, energy communities, smart grids and smart microgrids/nanogrids (Optimal Design models and Energy Management Systems). Competences on the modelling of electric storage systems and electric mobility charging infrastructures (vehicle-to-grid V2G, vehicle-to-building V2B and vehicle-to-home V2H technologies, Smart Charging of electric vehicles) will be also acquired. PREREQUISITES Knowledge of power plants. Knowledge of power and energy systems. Knowledge of mathematical analysis and systems theory. TEACHING METHODS The teaching unit is organized in interactive lectures on theoretical topics, solution of case studies and computer aided exercises (using Matlab, Matpower, Simulink, Simscape, Yalmip, Homer Pro, Recon, DIgSILENT). SYLLABUS/CONTENT - Development of mathematical models to simulate the behaviour of power plants in off-design (partial loads) and transient operating conditions - Smart grids and smart microgrids/nanogrids: technical and economic aspects, the Smart Polygeneration Microgrid of the Savona Campus - Modelling of electrical storage systems, high performance cogeneration and trigeneration units, renewable power plants - Modelling of electrical circuits and power distribution networks - Electric mobility systems (electric vehicles and charging infrastructures, vehicle-to-grid V2G, vehicle-to-building V2B and vehicle-to-home V2H technologies, Smart Charging of electric vehicles) - Development of optimization tools to design and daily operate distributed energy facilities, energy communities, smart grids/microgrids/nanogrids, charging hubs for electric vehicles - Development of Energy Management Systems for smart grids/microgrids/nanogrids, prosumer buildings with demand response, energy communities and charging hubs for electric vehicles. RECOMMENDED READING/BIBLIOGRAPHY Lecture notes. Books and papers suggested by the lecturer. TEACHERS AND EXAM BOARD STEFANO BRACCO Ricevimento: Students are received by appointment directly with the teacher via email or phone. Contact details: Stefano Bracco, DITEN, Via Opera Pia 11a, first floor, office no. I.20, 16145 Genova Savona Campus, Via Magliotto 2, Delfino building, office no. 3, 17100 Savona tel. +39-01921945123, mob. +39-3357917372, e-mail: stefano.bracco@unige.it LESSONS LESSONS START https://corsi.unige.it/en/corsi/11917/studenti-orario Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS EXAM DESCRIPTION Each student has to prepare a written report (possibly also in a group with other students) on a developed optimization/simulation model. A positive evaluation of the written report permits to have access to the oral exam which consists of answers to theoretical questions and the solution of numerical exercises. Students with a certified learning disability (DSA), a disability, or other special educational needs are invited to contact the instructor at the beginning of the course to discuss teaching and examination arrangements that, while respecting the learning objectives of the course, take individual learning needs into account and provide appropriate accommodations. Please also note that requests for exam accommodations or exemptions must be submitted using the form available at this link https://modulionline.unige.it/richiesta-adattamenti#no-back , to the course professor, the DIME contact person (federico.scarpa@unige.it), and the relevant office ( inclusione.studenti@info.unige.it) at least seven working days before the examination, in accordance with the guidelines available at this link https://unige.it/disabilita-dsa/richiesta-servizi ASSESSMENT METHODS Evaluation of the acquisition of practical and theoretical competencies in developing optimization and simulation models of power plants, energy distribution and storage systems, power distribution networks, prosumer buildings, energy communities, microgrids/nanogrids and electric mobility systems. FURTHER INFORMATION Students have to install Matlab/Simulink/Simscape software on their computer in order to follow lessons. Agenda 2030 - Sustainable Development Goals Quality education Affordable and clean energy Industry, innovation and infrastructure Sustainable cities and communities Responbile consumption and production Climate action