DENSYS Curriculum

Foreword

How the program is structured

Year 1

Year 2

Partners

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Elective courses #3

Wind and ocean energy plants

Teaching Unit (for year 2): Elective #3

Face-to-face time

⁠
`60`
⁠
hours

Student workload

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`180`
⁠
hours

ECTS

⁠
`6`
⁠
⁠

Responsible Teacher

Giovanni BRACCO

Politecnico di Torino

⁠

Pedagogic Team

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Aims of the teaching

Complete and updated course description available

here⁠

The course focuses on the modeling of the dynamics of energy systems and markets at different spatial scales and on medium-long terms under a complex set of constraints. This modeling is crucial today for the planning of sustainable energy strategies at regional, national and international level. The objective of the course is to provide the students the capability to discriminate between different models and scenarios for energy planning, as well as to develop their own simplified models, and to analyze and compare the results of complex energy models and different development scenarios. The course is inter-disciplinary in nature, being culturally located at the crossroads between economics and engineering. The main topics addressed in the course are:

The context of climate changes, the UN sustainability goals, the Paris Agreement, the needs for energy modeling and the different classifications of the existing models (top-down vs. bottom-up, partial vs. global equilibrium models; optimization vs. simulation, ...)

Micro-scale energy models - deterministic / statistical models, machine learning and stochastic models

Meso-scale energy models, with particular reference to Multi-Criteria Decision Algorithms and data classification learning processes.

Macro-scale energy models: assumptions in input, interconnections between energy demand, energy supply and technologies, mathematical methods adopted for the solutions, assessment of the propagation of uncertainties from input to output.

eMergy analysis and indices.

In parallel with these theoretical developments, the students have the opportunity to develop their own macro-scale model with a hands-on approach and to apply it to the analysis of a case study (a country or a region), divided in small groups.

Intended Learning outcomes (measured by the assessment)

After this course, the students will understand the rationale behind energy models at local/regional/world level, they will know the structure of the different models existing in the literature and will be able to distinguish and classify them. They will know the input needed for the different energy models (e.g. the MARKAL – TIMES models), with special attention to the main scenarios (business-as-usual, normative, explorative), and they will be able to properly comment and compare the relative outputs, and in particular the outlook of the main energy markets for the next few decades. The student will also know the main algorithms adopted for the solution of the constrained optimization problems hidden in the models, and be able to apply them in order to develop the model of a regional energy balance in small teams, empowering their capabilities to work in a group and improving their communication skills.

Learning activities and approach

E-learning (online)

Could be the whole course

Lectures (onsite)

45h

Tutorials (onsite)

Tutorial on the Reference Energy System

Useful information

Location

Practical work equipment

The final grade is obtained combining two different assessments:

1. A written exam, contributing up to 18/30 to the final grade, including 3-4 questions on different theoretical topics addressed during the lectures, for a duration of 2h. The written exam aims at verifying the student’s capability to personally summarize and discuss the main features and issues of the energy modeling at the different spatial scales, presented in the course. 2. The preparation of a short report, and its presentation in oral or poster form, on the analysis of a regional balance of a selected country, and on the simulation of alternative scenarios for its energy mix evolution up to 2050, to be submitted by the end of the course. The individual project, contributing up to 12/30 to the final grade, aims at assessing the student’s capability to select and use the most suitable numerical models and tools, among those presented during the course, for the energy modeling at the macroscale.

Other information

Assessment method

Homework (mini case based), final exam.

Prerequisites

A background on the fundamentals of all major energy technologies (oil, coal, gas, renewables, nuclear, etc.) is taken for granted.

Related literature

Selected up-to-date papers published in International Journals on the topic subject of the course.

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