Hierarchical distributed optimization and predictive control of a smart grid

29 August 2018
August 29, 2018
Contatti: 
DII - Dipartimento di Ingegneria Industriale
via Sommarive, 9 - 38123 Povo, Trento
Tel. 
+39 0461 282500 - 2503
Fax 
fax +39 0461 281977

Venue: Seminar Room, h. 14:00 – 15:00, Polo scientifico-tecnologico Fabio Ferrari – via Sommarive 9 - Trento

  • Philipp Braun -  University of Newcastle, Australia

Abstract:

The energy transition, from a centralized to a decentralized and sustainable power supply using small scale power plants, presents new challenges to the distribution grid provider who is responsible for maintaining the stability of the electricity network. New procedures to ensure the overall network stability need to be developed, which are flexible with respect to the underlying network and scalable, to be able to handle the amount of data of a fast growing network of renewable energy producers. To this end, we examine model predictive control (MPC) and hierarchical distributed optimization algorithms. In particular, we use a network of residential energy systems (RESs), connected to a grid provider through a point of common coupling, where every resident is equipped with solar photovoltaic panels and local storage devices to examine three different hierarchical distributed optimization algorithms. The flexibility of the algorithms allows for a plug and play manner of implementation. Scalability is obtained by solving the optimization problems on the level of the RESs and not on the level of the grid provider. Furthermore, with respect to a specific centralized optimization problem, convergence of the distributed optimization algorithms to the central optimum can be proven. The performance of the distributed optimization algorithms and the corresponding MPC schemes are illustrated using a dataset on power generation and power consumption of residential customers of the company Ausgrid.

Biosketch:

Philipp Braun received the Diploma degree in mathematics from the Technical University Kaiserslautern, Kaiserslautern, Germany, in 2012 and the Ph.D. degree in mathematics from the University of Bayreuth, Bayreuth, Germany, in 2016. Since 2016, he has been an Assistant Professor at the Chair of Applied Mathematics at the University of Bayreuth (currently on leave), and a Senior Research Associate at the University of Newcastle, Newcastle, Australia. His research interests include predictive control algorithms, in particular, distributed control algorithms in the context of smart grids. Additionally, he is working on stability and stabilization of constrained dynamical systems using Lyapunov methods.