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

URN zum Zitieren dieses Dokuments: urn:nbn:de:bvb:703-epub-2078-4

Titelangaben

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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Braun_Gruene_et_al_real_time_pricing_scheme_for_res_2015.pdf - Preprint
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Angaben zu Projekten

Projekttitel:
Offizieller ProjekttitelProjekt-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

Projektfinanzierung: 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.

Weitere Angaben

Publikationsform: Preprint, Postprint, Working paper, Diskussionspapier
Keywords: noncooperative distributed optimization; smart grid; model predictive control
Themengebiete aus DDC: 500 Naturwissenschaften und Mathematik > 510 Mathematik
Institutionen der Universität: Fakultäten
Fakultäten > Fakultät für Mathematik, Physik und Informatik
Fakultäten > Fakultät für Mathematik, Physik und Informatik > Mathematisches Institut
Fakultäten > Fakultät für Mathematik, Physik und Informatik > Mathematisches Institut > Lehrstuhl Mathematik V (Angewandte Mathematik)
Fakultäten > Fakultät für Mathematik, Physik und Informatik > Mathematisches Institut > Lehrstuhl Mathematik V (Angewandte Mathematik) > Lehrstuhl Mathematik V (Angewandte Mathematik) - Univ.-Prof. Dr. Lars Grüne
Profilfelder
Profilfelder > Advanced Fields
Profilfelder > Advanced Fields > Nichtlineare Dynamik
Sprache: Englisch
Titel an der UBT entstanden: Ja
URN: urn:nbn:de:bvb:703-epub-2078-4
Eingestellt am: 23 Jun 2015 07:40
Letzte Änderung: 23 Jun 2015 07:40
URI: https://epub.uni-bayreuth.de/id/eprint/2078