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.
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.
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:
Fundamentals on mathematics and statistics
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
Part I: Introduction to Optmization models
Part 2: Network Optimization
Part 3: uncertainty and scenarios analysis
Part 4: Project management.
Bibliography will be indicated during lessons and published on AULAWEB
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)
Ricevimento: Please, write an email to have an appointment (ambrosin@economia.unige.it)
Septembre 2024 (first semester)
Written examination and presentation of case studies.
In same cases a lab activity should be required.
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.
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.