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Mean Field Games and Smart Grids - Distributed Control Solutions for the Future Power Network

Alan Turing Institute via YouTube

Overview

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Explore the application of Mean Field Games (MFG) in distributed control solutions for future power networks in this 41-minute workshop video from the Alan Turing Institute. Delve into the basic theory of MFG and its applications to optimization problems in the energy industry and environmental sciences. Learn about energy arbitrage with storage, electricity market modeling, and numerical resolution techniques. Examine case studies on cyclic constraints and model extensions for Thermostatically Controlled Loads (TCLs). Investigate transmission expansion planning, including network representation, centralized network expansion, and merchant planning solutions. Gain insights from leading experts in the field and discover how MFG can be applied to high-dimensional distributed optimization problems in various domains, from energy production and storage optimization to climate change negotiations modeling.

Syllabus

Intro
Motivations
Outline
Energy arbitrage with storage
Modelling: electricity market
Mean Field Game Formulation
Numerical resolution
Cyclic constraints
Implementation
Case study (2)
Model extensions
Thermostatically Controlled Loads
Main Features
Modelling: Individual TCL
Modelling: TCL population
Modelling: Unit Commitment
Summary
Transmission Expansion
Network Representation
Centralized Network Expansion
Game with continuum of players
Objective function
Merchant planning solution
Conclusions

Taught by

Alan Turing Institute

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