CODE 108172 ACADEMIC YEAR 2024/2025 CREDITS 6 cfu anno 2 MANAGEMENT FOR ENERGY AND ENVIRONMENTAL TRANSITION (MEET) 11427 (LM-77) - GENOVA SCIENTIFIC DISCIPLINARY SECTOR MAT/09 LANGUAGE English TEACHING LOCATION GENOVA SEMESTER 1° Semester MODULES Questo insegnamento è un modulo di: QUANTITATIVE ANALYSIS FOR DECISION MAKING TEACHING MATERIALS AULAWEB OVERVIEW The course aims at exploring tools to support networks and system management, and project management in the energy field, including environmental and green transition issues. Methods to perform networka and systems scenarios analysis are presented, together with some Key performance indexes. Models to plan and control the project activities are proposed and time-cost trade-off analysis will be realized. AIMS AND CONTENT LEARNING OUTCOMES The course aims to explore tools to support systems, networks management, and project management. It focuses on strategic decisions related to network design with predefined connectivity, reliability, and sustainability levels. From the concept of the network to the system one. Queue theory tools will be used to perform system analysis and dimension evaluation thanks to Key performance indexes. Some scenarios analysis will be performed and methods to deal with uncertainty will be introduced. In the project management field, useful models will be studied to plan and control the project activities. Time-cost trade-off analysis will be realized. AIMS AND LEARNING OUTCOMES The course aims at providing decision support methods to face problems in the energy field, including enviromental and green transition issues. The course will provide the knowledge of different management and optimization techniques such as math programming, decision theory, simulation, scenario analysis.. The consolidation of the proposed methodologies is supported by the development of case studies; methods and models will be implemented and solved thanks to specific software. The case studies analysed will allow the development of awareness of personal learning level, of ability to apply the studied techniques, understanding one's own needs for skills development. Furthermore, the solution of the problems contextualized in real systems allows the development of imagination, creativity, critical reflection, and problem-solving. With reference to learning outcomes, at the end of the course the students must have acquired competences that allow them to understand, describe and solve different types of real problems, develop models and methods and use dedicated software environments with a certain mastery of reference. Specifically, at the end of the course, the students will be able to: analyse a decision problem and understand the best way to face it formulate a decision problem and define a solution approach solve some of the typical problems in the energy field critically analyse the solutions obtained by assessing their correctness and feasibility and discuss on their efficiency, reliability and sustainability. carry out scenario analyses and compare the alternatives PREREQUISITES Fundamentals on mathematics and statistics TEACHING METHODS Traditional lectures are integrated with lab lessons, seminars and individual/group works. During lesson are proposed activities based on active, interactive and constructive teaching techniques; these activities will contribute to the acquisition of transversal skills (see the training objectives section) and related Open Badges. Thanks to participation in proposed activities, it is possible to obtain the following Open Badge: Ability in learning to learn - advanced level Project creation proficiency - basic or advanced level SYLLABUS/CONTENT Part I: Introduction to Optmization models Introduction to Operations Research and problem solving: from real problems to optimization models. Classification of optimization models and methods, and brief introduction. Software for optimization: excel and/or Lingo Part 2: Network Optimization Graphs and Optimization problems on graphs Network design problems, sustainable and reliable networks Part 3: uncertainty and scenarios analysis Decision trees and decision theory Simulation and Scenarios analysis System performance evaluation: Key performance indexes, trade offs Part 4: Project management. Graphs for representing and evaluating time and costs of projects Time-cost trade-off analysis Methods to deal with uncertainty RECOMMENDED READING/BIBLIOGRAPHY Bibliography will be indicated during lessons and published on AULAWEB TEACHERS AND EXAM BOARD DANIELA AMBROSINO Ricevimento: Please, write an email to have an appointment (ambrosin@economia.unige.it) ELENA TANFANI Ricevimento: Wednesday h.13.00 - Department of Economics - I floor (contact the teacher some days before via email). Remote reception on Team on request: contact the teacher via email (etanfani@economia.unige.it) LESSONS LESSONS START Septembre 2024 (first semester) Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS EXAM DESCRIPTION Written examination and presentation of case studies. In same cases a lab activity should be required. ASSESSMENT METHODS The knowledge on the topics covered in class will be assessed through the written examination The ability to apply knowledge and communication skills and other personal competencies (learning to learn and project creation) will be assessed through the projects work and thier presentation. FURTHER INFORMATION Working students and students with certified SLD (Specific Learning Disorders), disability or other special educational needs are advised to contact the teacher at the beginning of the course to agree on teaching and examination arrangements so to take into account individual learning patterns, while respecting the teaching objectives. Agenda 2030 - Sustainable Development Goals Affordable and clean energy Sustainable cities and communities Climate action OpenBadge PRO3 - Soft skills - Creazione progettuale avanzato 1 - A PRO3 - Soft skills - Creazione progettuale base 1 - A PRO3 - Soft skills - Imparare a imparare avanzato 1 - A