MicroGrids, SmartGrids and Supergrids - 5EUS5SMA

Goal(s)

The development of renewable energy, electric vehicles and various storage facilities linked to a desire to preserve the environment brought new challenges to traditional power systems but also embedded and island systems. These networks must follow this policy while remaining economical and reliable. The purpose of this unit is to understand all the new challenges that make the concept of Micro Grids, Smart Grids and Super Grids emerge. Students will be trained to methods and tools, in the research phase, experimentation phase or already used, in order to be as close as possible to current industrial issues.

Content(s)

The development of renewable energy, electric vehicles and various storage facilities linked to a desire to preserve the environment brought new challenges to traditional power systems but also embedded and island systems. These networks must follow this policy while remaining economical and reliable. The purpose of this unit is to understand all the new challenges that make the concept of Micro Networks, Smart Grids and Super Grids emerge. Students will be trained to methods and tools, in the research phase, experimentation phase or already used, in order to be as close as possible to current industrial issues.
The unit consists of four courses:

• Smart Grids and Super Grids
  In this course, the new challenges and actors of electrical networks are presented as well as the new resulting constraints. The goal is to show the need for structural evolutions (new architectures, DC networks ...) and operational evolutions (reconfiguration in normal condition, self-healing, state estimation and coordinated voltage control) of power systems for the transition to the Smart grids and Super grids.
• Advanced functions for the integration of RES
  In this lab, the PREDIS real distribution network is firstly modeled in Matlab. Then simulations are used to highlight the various technical constraints that appear due to the insertion of distributed generation. Two major advanced functions are explored: the reconfiguration of the network and the producer participation to voltage regulation. These solutions are then applied to the PREDIS distribution network.
• Optimization method for networks
  The numerical optimization for the electrical networks course begins with a general presentation of the optimization (objectives, theoretical concepts). Then it describes the classes of optimization problems which are now well understood and accessible to numerical calculation and the computer tools useful for engineers to effectively solve them. Then this course broaches modeling, ie the art of "well" representing real problems as mathematical optimization problems, and illustrates it by setting the equations of two key application problems coming from the electrical industry: the problem of managing power generation and the problem of power flow allocation in a transmission network. These equations are then implemented by students during labs and used for typical case studies encountered in practice in power systems.
• Sizing of multi-source systems
  The objective of this course is to study the technical aspects involved in the design of a dynamic electrical system in general: energy flow management, optimal sizing of sources (storage included), dynamic stability and dynamic interactions, advanced monitoring and control. All these concepts are applied on case studied (embedded systems, island networks, microgrids). By the way, students will make the connection between the modes of dynamic management and the sizing of the various components of the system. This course is divided into 4 parts:
  • Technical debate on the steps to be considered in the complete sizing of an electrical system and the constraints to considered. Presentation of the expectation of the course.
  • Energy management of an embedded system: frequency source management, analysis and links related to the sizing of the system. Quick overview of other management strategies (optimal control by rules, fuzzy logic).
  • Dynamic analysis of an electrical system: state modeling, stability analysis, participation factors and sensitivity matrices, formulation of the control objectives, formulation of the problem of robust control.
  • Mini-Project:
    • sizing of an embedded storage system (batteries and / or supercapacitors)
    • sizing of the control and monitoring architecture of an isolated DC network: state modeling, stability analysis, synthesis of correctors based on the sensitivity function, timing validation.

• 1st year 1 – common courses
  • Unit Electric Power devices
  • Unit Modeling and Control of Systems
  • Unit Modeling and Numerical Computation
• Numerical methods (EdP simulation and optimization) Common to ASI / IEE / SEM 2A
• Course Modeling and networks computation (IEE PS Unit Sizing and operation of electrical networks) or Modeling and grid management (SEM S3 Module Power System),