Semester 1 : (Uso)

TU111:  Sensors

On successful completion of this course, the students will be able to:

  • Know and describe the physics of sensor mechanisms.
  • Select and use sensors for laboratory experiments and industrial plants. 
  • Describe and define performance criteria for sensors.
  • Analyze and rate the performance of different transducers and sensors.
  • Predict and identify the parameters that might affect the sensor performance.

TU112:  Wind turbines

On successful completion of this course, the students will be able to:

  • Identify the different elements  and technologies of the wind turbines. 
  • Calculate the wind speed using log law and power laws and predict the  aerodynamic loads on a wind turbine rotor. 
  • Design the wind turbine’s rotor
  • Calculate power and thrust as a function of wind speed.
  • Evaluate the impact of surface roughness and orography on wind speed profiles.
  • Use and apply the maximum power extraction techniques. 
  • Calculate power curve and analyze the impact of various control systems in a wind turbine.
  • Analyze and simulate the aerodynamics profile for a wind turbine.

TU113:  Electromechanical Energy Converters

On successful completion of this course, the students will be able to:

  • Describe the basic process of electromechanical energy conversion.  
  • Describe the creation procedure of a rotating magnetic field in three-phase AC machines.
  • Describe the operation principle and use synchronous machines in both operation modes:  motors and generators.
  • Describe the operation principle and use squirrel and double-fed induction machines  in both operation modes: motors and generators.
  • Détermine the steady state equivalent model and power balance of synchronous and induction machines.
  • Determine the dynamic model of synchronous and induction machines in a rotating frame and their vector control.

TU121: Electric circuits and transformers 

On successful completion of this course, the students will be able to:

  • Know the basics of electrical networks and transformers.
  • Determine and calculate the different currents, voltages and powers in different structures and types of electric circuits (single-phase or three-phase).
  • Understand the equivalent model and calculate the power balance of electric transformers.
  • Use transformers in distribution and transmission grids.

TU122: Photovoltaic energy

On successful completion of this course, the students will be able to:

  • Identify the different types of photovoltaic installations. 
  • Introduce the design and sizing solar photovoltaic power systems (on-grid/off-grid) using analytical techniques, dedicated softwares and the required datasets.
  • Identify the different components of a PV systems (PV panels, PV inverters, safety components, etc). 
  • Know and evaluate the performance and efficiency of PV cells and PV inverters technologies.
  • Know the main factors that impact the amount of peak sun hours reaching the PV array.
  • Identify the optimal angle and orientation that provides maximum energy production.
  • Understand the required steps for solar system installation.

TU123: Static Power Converters

On successful completion of this course, the students will be able to:

  • Know the basics of energy conversion using static power converters.
  • Design and analyze power converter circuits.
  • Select suitable power converters to control électrical motors and other energy applications (charge controller, solar inverter, etc.).
  • Calculate and analyze the output parameters of power converters (average value, RMS value, harmonic spectrum, active and reactive powers, power factor, etc.)

TU131: Microcontroller for power converters and electrical machine

On successful completion of this course, the students will be able to:

  • Understand the interaction between the different components of the microcontroller architecture.
  • Know the software and hardware operation of a microcontroller.
  • Select an appropriate data type and use the memory of a microcontroller.
  • Program a microcontroller from different levels of language so that it performs a succession of logical and complex steps.
  • Integrate a microcontroller in specific applications.

TU132: FPGA with VHDL

On successful completion of this course, the students will be able to:

  • Know the principles of advanced digital circuit design. 
  • Know the state-of-the-art ASIC/FPGA design methodologies.
  • Build FPGA designs using the hardware description language VHDL.
  • Operate, debug and analyze IP core designs in modern VHDL software tool-chains.

TU133: Embedded systems for PV energy applications

On successful completion of this course, the students will be able to:

  • Configure the different hardware modules used for the real-time control of a PV system such as the PWM modules, analog to digital converters, etc.
  • Manage the operation of different timers and interrupts used in the control algorithm for a PV energy applications
  • Make the measurement of all electric signals requested for the control of PV energy applications
  • Generate in real-time the PWM signals feeding the gates of the PV energy converters.
  • Implement in real-time an MPPT algorithm for PV energy applications.

TU141: Microcontroller for power converters and electrical machine

Similar to the content of TU131

TU142: FPGA with VHDL

Similar to the content of TU132

TU143: Embedded systems for wind energy applications

On successful completion of this course, the students will be able to:

  • Configure the different hardware modules used for the real-time control of a wind energy system such as the PWM modules, analog to digital converters, etc.
  • Manage the operation of different timers and interrupts used in the control algorithm for a wind energy applications .
  • Make the measurement of all electric signals requested for the control of a wind energy applications.
  • Generate in real-time the PWM signals feeding the gates of the wind energy converters. 
  • Implement in real-time an MPPT algorithm for wind energy systems.

TU151: Conventional Optimization methods

At the end of this course, the student will be able to:

  • Analyze the advantages and disadvantages associated with the large-scale optimization techniques when applied to problems from electrical or energy engineering applications.
  • Formulate a problem situation in the form of an optimization model.
  • Analyze an optimization model, in particular determine if it is linear or if it is convex.
  • Characterize the optimal solutions of an optimization model and, when possible, calculate them analytically, analyze their sensitivity using duality in the linear case.
  • Propose in a reasoned way the use of a resolution algorithm, based on the type of problem, its size and the expected convergence properties.
  • Implement a resolution algorithm.

TU152: Advanced optimization methods

  • The student will be able to analyze the complexity of the different methods and critically analyze the different methodological options available for solving optimization problems in the management of complex systems.

Semester 2 : (ULe & UCA)

TU21.1: Modern Power Systems and Smart Grids

  • The student knows the main parts of an electrical power system, how they interconnect, and their functions.

TU21.2: Power Systems Operation and Analysis

  • The student can model, simulate and analyze electrical power systems in a steady-state regime.
  • The student can model, simulate and analyze electrical power systems in a transient regime.
  • The student can evaluate faulted electrical systems.
  • The student can evaluate the stability of electrical systems.

TU21.3: Power Systems Protection

  • The student knows the fundamentals of designing and coordinating protection schemes in electrical systems.

TU21.4: Practical Work: Laboratory on Smart Grids

  • The student can apply theoretical concepts to engineering problems and case studies.

TU22.1: Distributed Energy Resources

  • The student sizes self-consumption facilities and simulates their operation.
  • The student designs a wind energy plant connected to a distribution network.
  • The student knows the main energy storage technologies and simulates and tests detailed models for electrical batteries. 
  • The student knows the main preventive, predictive, and corrective maintenance techniques for distributed resources.

TU22.2: Energy Management for Buildings

  • The student models the energy demand of a building.
  • The student models both the thermal and electrical demands in a building.
  • The student acquires the basic theoretical concepts related to building energy analysis and management.
  • The student knows the appropriate procedures for carrying out energy-saving studies and the methods for verifying the energy demand limitation in buildings.
  • The student knows the thermal and electrical market rules and tariff systems and can simulate the electric bill of a building.
  • The student applies the main concepts of home automation management to improve the energy efficiency of a building.
  • The student designs a simple energy management system for a building based on a deterministic or stochastic approach.

TU22.3: Fundamentals of Energy Economics 

  • The student knows the relationship between energy and economic growth and how the availability of energy affects the balance of markets, economic development, and the ability of economies to compete in a global environment, especially in the European context. 
  • The student identifies the main macroeconomic energy indicators.
  • The student designs an economical energy map.

TU22.4: Fundamentals of Energy Policy  

  • The student knows the impact of geopolitical and security factors in the energy sector and their effects on regulation. 
  • The student understands the concept of energy security broadly and the geopolitical factors that determine its future, especially in the case of the EU.

TU22.5: Practical Work: Laboratory in DER and Energy Management

  • The student can apply theoretical concepts to engineering problems and case studies.
  • Students should be able to integrate knowledge and face the complexity of making judgments based on information that, being incomplete or limited, includes reflections on the social and ethical responsibilities linked to the application of their knowledge and judgments.
  • Understand the legal, moral, and ethical implications regarding the use of artificial intelligence.
  • Students understand the fundamentals of data engineering (modeling, ingestion, storage, processing, analysis, and visualization), crawling, processing, indexing, and information retrieval techniques.
  • Apply methodologies for the design, implementation, and testing of learning frameworks.
  • Know the different stages in the management of a machine learning project and the most common tools to perform this task successfully.
  • Control advanced techniques in the field of deep learning and optimization.
  • Manage the implementation and life cycle of predictive models in the production phase.

Students should be able to:

  • Apply natural language processing techniques in problem-solving.
  • Apply computer vision techniques to solve problems.
  • Develop deep learning algorithms in different tasks of natural language processing and computer vision.
  • Students should know the technical regulations and legal provisions applicable to cybersecurity, their implications in the design of systems, and the application of security tools.
  • Students should be able to plan, manage, organize, and implement security measures in the operation and management of systems.
  • Students should be able to design mechanisms to prevent security threats, as well as to detect and respond to security incidents in critical systems. 
  • Students should know to analyze the particularities of the critical systems and their authentication and access authentication and access schemes according to the scope of the application.

Students should be able to:

 

  • Conceive, design, implement, and maintain a comprehensive cybersecurity system in a defined context.
  • Develop concise, clear and reasoned documents, plans and work projects in the field of cybersecurity.
  • Design and implement secure distributed architectures, platforms, and systems.

Semester 3: (UNIVAQ & UT)

  • Students will be able to understand the structure of power converters, electric machines and drives for renewable energy systems, how single elements interact each other, the main requirements and problems in their operations.
  • Students will learn the main topologies of power converters DC/DC, AC/DC, and DC/AC and how they can be connected with the sources and the loads and/or the grid.
  • Students will learn how to use electric machines for the electromechanical energy conversion, their operation as generators and as motors.
  • Students will learn how to simulate systems using power converters and electric machines.
  • Students will learn how to select and use components to design DC/DC, AC/DC and DC/AC power converters for the conversion of renewable energy systems.
  • Students will develop simple projects by simulations and laboratory design and verification.

Upon successful completion of this module, the student should:

  • have advanced knowledge, with technical insights, of formal definitions, algorithms and methodologies of advanced techniques of ML and optimal control.
  • be able to choose the best ML technique for building a predictive model of an automation system, and use it to solve an optimal control problem with respect to certain specifications and constraints.
  • be able to formally set up a control problem related to energy systems, and to compare and adequately choose different techniques consistently with the specific problem.
  • be able to extract and process data from the “Laboratory of Monitoring and Control of Building Automation Systems” of the University of L’Aquila, which consists of a collection of SCADA systems of HVAC and energy plants of 3 buildings of the Campus of the University of L’Aquila.
  • On successful completion of this module, the student will be able to design controllers for systems in the field of automatic control for energy. To characterize this offer, which is aimed at both industrial and information engineering, is its distinctly scientific character, with a good knowledge base borrowed from physics and mathematics. Students will be able to direct their interests along three paths: Machine Learning, Industrial Automation, and Complex Systems. Thanks to the design skills acquired in the most innovative technological fields and the use of the most modern tools, students will be able to deal with innovation and development of production, design, programming, and management of systems in manufacturing or services companies and in public administrations.

Upon completing a program on Health Impact Assessment (HIA) for the Energy, learners should be able to:

  • Understand the principles and concepts of HIA:

      1. Define what HIA is and its purpose.
      2. Explain the key principles and core concepts underlying HIA.

  • Identify the components of HIA:

      1. Recognize the different stages of HIA, including scoping, assessment, mitigation, and monitoring.
      2. Describe the various stakeholders involved in the HIA process and their roles.

  • Conduct a comprehensive HIA:

      1. Collect and analyze relevant data to assess potential health impacts of a project, policy, or program.
      2. Apply appropriate methodologies and tools to evaluate health-related consequences.

  • Assess and evaluate potential health impacts:

      1. Identify potential positive and negative health effects on different population groups.
      2. Analyse and interpret the results of the HIA to inform decision-making.

  • Integrate health considerations into planning and decision-making:

      1. Articulate the importance of considering health in various sectors, such as urban planning, transportation, and environmental policies.
      2. Propose strategies to incorporate health concerns into decision-making processes.

  • Engage stakeholders and promote collaboration:

      1. Demonstrate effective communication skills to engage diverse stakeholders in the HIA process.
      2. Facilitate collaborative efforts between health professionals, policymakers, and community representatives.

  • Develop and recommend evidence-based mitigation measures:

      1. Formulate feasible and evidence-based recommendations to enhance positive health impacts and minimize negative effects.
      2. Advocate for the adoption of HIA findings and proposals.

  • Understand the legal and ethical aspects of HIA:

      1. Identify legal frameworks and regulations relevant to HIA implementation.
      2. Address ethical considerations and challenges related to HIA, such as privacy and confidentiality.

  • Apply HIA to real-world scenarios:

      1. Practice conducting HIA for actual projects or policies, using case studies or simulations.
      2. Reflect on lessons learned and improvements for future HIA endeavors.
  • Promote the integration of HIA into policy and decision-making processes:
      1. Advocate for the use of HIA in planning and policymaking in the energy sector at various levels (local, regional, national).
      2. Influence decision-makers to prioritize health outcomes in their initiatives.
  • Evaluate and communicate the results of HIA:
    1. Develop effective strategies to communicate HIA findings to diverse audiences.
    2. Assess the effectiveness of HIA and identify areas for improvement.

Semester 4 (Uso, UNIVAQ, ULe, UCA, UT)

In Semester 4, the student can choose one of the following options:

  1. Apply for one of the proposals validated and published by the Joint Programme Board (JPB)
  2. Provide a proposal for an external project drawn up by a company. An external project form must be duly completed and signed by the qualified person in charge at the company. The proposal must be approved by the JPB

 The Master’s Thesis is evaluated following the procedures agreed by the University Academic Committee (UAC) of the party where the thesis is presented. It is written and defended in English in front of a jury consisting of representatives nominated by the UAC of the party where the student presents his/her thesis and also an external reviewer.