Titlebar

Export bibliographic data
Literature by the same author
plus on the publication server
plus at Google Scholar

 

A real-time pricing scheme for residential energy systems using a market maker

Title data

Braun, Philipp ; Grüne, Lars ; Kellett, Christopher M. ; Weller, Steven R. ; Worthmann, Karl:
A real-time pricing scheme for residential energy systems using a market maker.
In: The Institution of Engineers Australia (ed.): Proceedings of 2015 Australian Control Conference (AUCC). - Barton, Australia , 2015 . - pp. 259-262
ISBN 978-1-4673-9552-6

This is the latest version of this item.

Official URL: Volltext

Project information

Project title:
Project's official titleProject's id
DFG Priority Program 1305 "Control theory for digitally networked dynamical systems", Project "Performance Analysis for Distributed and Multiobjective Model Predictive Control"GR1569/13-1
ARC Future FellowshipFT1101000746

Project financing: Deutsche Forschungsgemeinschaft
ARC

Abstract in another language

Voltage rise is an undesirable side-effect of solar photovoltaic (PV) generation, arising from the flow of surplus electrical power back into the grid when PV generation exceeds local demand. Customers deploying residential-scale battery storage are likely to further exacerbate voltage rise problems for electrical utilities unless the charge/discharge schedules of batteries is appropriately coordinated. In this paper, we present a real-time pricing mechanism for use in a network of distributed residential energy systems (RESs), each employing solar PV generation and battery storage. The pricing mechanism proposed in this paper is based on a Market Maker algorithm in which predicted power profiles and real-time pricing information is iteratively exchanged between a central entity and each of the RESs. The Market Maker formulation presented in this paper is shown via simulation studies to converge to a fixed price vector, thereby reducing the price volatility observed in an earlier formulation, while achieving the same reduction in power usage variability as a centralised model predictive control (MPC) scheme presented previously.

Further data

Item Type: Article in a book
Related institutions (e.g. sponsor, organisator): Institute of Electrical and Electronics Engineers : IEEE
Refereed: Yes
Keywords: noncooperative distributed optimization; smart grid; model predictive control
Institutions of the University: Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics)
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics) > Chair Mathematics V (Applied Mathematics) - Univ.-Prof. Dr. Lars Grüne)
Profile Fields
Profile Fields > Advanced Fields
Profile Fields > Advanced Fields > Nonlinear Dynamics
Result of work at the UBT: Yes
DDC Subjects: 500 Science > 510 Mathematics
Date Deposited: 14 Jan 2016 11:40
Last Modified: 01 Oct 2018 10:25
URI: https://eref.uni-bayreuth.de/id/eprint/29682

Available Versions of this Item