YoVDO

Modelling and measuring the Energy Transition

Offered By: Politecnico di Milano via Coursera

Tags

Energy Systems Courses Linear Programming Courses

Course Description

Overview

This MOOC provides attendants with fundamental knowledge about the main challenges in modelling the energy transition at both global and regional levels, as well as the industrial ecology instruments to measure the associated impacts. The course begins by covering national energy accounting and the definition of a reference energy system, followed by an introduction to modelling for energy planning through linear programming. Participants will be engaged in hands-on practice using Excel. Additionally, scenario analysis principles are provided to help participants wisely discuss the results of practical case studies. Next, the course covers national economic accounting and the use of monetary input-output tables for national and multiregional applications, such as computing carbon footprints. Participants will also learn about Leontief’s production and impact model, which is demonstrated through another Excel-based hands-on session. Lastly, students will be introduced to the use of MARIO, an in-house, Python-based open-source tool for regional and multi-regional impact assessment studies based on Input-Output Analysis. By the end of the MOOC, participants will acquire a strong foundational knowledge for scientifically approaching the global energy transition; they will be able to understand and interpretate national economic and energy accounting tables, as well as to apply specific tools freely available to plan energy interventions and to assess their impacts.

Syllabus

  • Modelling Energy Transition
  • Measuring the impact of Energy Transition

Taught by

Matteo Vincenzo Rocco and Emanuela Colombo

Tags

Related Courses

Linear and Discrete Optimization
École Polytechnique Fédérale de Lausanne via Coursera
Linear and Integer Programming
University of Colorado Boulder via Coursera
Graph Partitioning and Expanders
Stanford University via NovoEd
Discrete Inference and Learning in Artificial Vision
École Centrale Paris via Coursera
Convex Optimization
Stanford University via edX