93039 - Smart Grids for Renewables Integration M

Learning outcomes

At the end of the course students are provided with the basic criteria for the planning, operation, control, and protection of medium / low voltage power distribution networks with high penetration of dispersed generation - mainly from renewable sources – and storage units, based on the use of ICT (smart grid) technologies. The course focuses on stability, on voltage and frequency control, on demand side management of the mentioned distribution networks. The course also contains a laboratory module at the end of which students have the basic knowledge for the design and use of a DMS (distribution management system) for active distribution networks.

Course contents

The course addresses some of the main issues relevant to the power distribution network operation in presence of distributed generation and of the power apparatuses and systems that allow for its smart management.

In particular, the course deals with the steady state and transient response of power grids by using suitable models of the main components of the electrical power systems, to be implemented in simulation environments.

During the carrying out of the Laboratory activities, some of the methods supporting the smart management of active distribution networks, such as load flow calculation and state estimation, are applied to case studies that take into consideration the recent technical standards for the connection of distributed generation resources to the power grid. Matlab and EMTP are the professional software environments used for the purpose.

The course also briefly introduces the use of artificial intelligence and machine-learning techniques as support tools for load/generation forecasting, monitoring, pseudo-measurement generation, and state estimation in active distribution networks.

In the laboratory sessions, an introduction to FPGA and Real-Time Labview programming is provided for the development of signal acquisition systems, processing and control on reconfigurable platforms as a support for DMS.

Theory

• The smart grid. Impact of distributed generation and renewables.
• Recall of power flow calculations.
• Calculation of the hosting capacity of a distribution feeder.
• Interconnection of renewable and distributed generation and relevant protections.
• Introduction to power system state estimation.
• Introduction to artificial intelligence and machine learning applications for active distribution networks: forecasting, monitoring, state-estimation support, and decision support for DMS.
• Introduction to phasor measurements units and their applications.

• Grid-codes present and future requirements in presence of converter-connected resources.

Laboratory

• Introduction to EMTP calculations.
• Transient response of a distribution feeder.
• Frequency control in presence of islanded generators and frequency taker converter-connected generators.
• Development of a voltage-unlock protection in EMTP.
• State estimation of power systems in Matpower.
• Machine-learning-based load/generation forecasting and use of pseudo-measurements for distribution-system state estimation in Matpower.
• Introduction to FPGA and Real-Time Labview programming.
• Coding phasors and estimation of the positive, negative and zero sequence in a real time application.
• Development of a Fault Ride Through protection for a Wind Turbine Generator in LabView real-time environment.

Readings/Bibliography

Lecture notes.

Teaching methods

Theory lectures and laboratory exercises.

In consideration of the type of activity and the teaching methods adopted, the attendance of this training activity requires the prior participation of all students in the training modules 1 and 2 on safety in the study places, in e-learning mode.

Assessment methods

The end-of-course examination, conducted via EOL, will assess both theoretical and laboratory topics, including EMTP and LabVIEW programming. Exam schedules will be available at almaesami.unibo.it.

Office hours

See the website of Fabio Tossani