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

URN to cite this document: urn:nbn:de:bvb:703-epub-2078-4

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.
Department of Mathematics, University of Bayreuth, School of Electrical Engineering and Computer Science, University of Newcastle, Australia, Technische Universität Ilmenau
Bayreuth , 2015 . - 4 S.

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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

Abstract

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: Preprint, postprint
Keywords: noncooperative distributed optimization; smart grid; model predictive control
DDC Subjects: 500 Science > 510 Mathematics
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
Language: English
Originates at UBT: Yes
URN: urn:nbn:de:bvb:703-epub-2078-4
Date Deposited: 23 Jun 2015 07:40
Last Modified: 28 Mar 2019 15:16
URI: https://epub.uni-bayreuth.de/id/eprint/2078

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