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Verlagsausgabe
DOI: 10.5445/IR/1000085522
Veröffentlicht am 27.08.2018
Originalveröffentlichung
DOI: 10.1186/s42162-018-0017-3

Increasing the efficiency of local energy markets through residential demand response

Mengelkamp, Esther; Bose, Samrat; Kremers, Enrique; Eberbach, Jan; Hoffmann, Bastian; Weinhardt, Christof

Abstract:
Local energy markets (LEMs) aim at building up local balances of generation and
demand close to real time. A bottom-up energy system made up of several LEMs could
reduce energy transmission, renewable curtailment and redispatch measures in the
long-term, if managed properly. However, relying on limited local resources, LEMs
require flexibility to achieve a high level of self-sufficiency. We introduce demand
response (DR) into LEMs as a means of flexibility in residential demand that can be used
to increase local self-sufficiency, decrease residual demand power peaks, facilitate local
energy balances and reduce the cost of energy supply. We present a simulation study
on a 100 household LEM and show how local sufficiency can be increased up to 16%
with local trading and DR. We study three German regulatory scenarios and derive that
the electricity price and the annual residual peak demand can be reduced by up to
10ce/kWh and 40%


Zugehörige Institution(en) am KIT European Institute for Energy Research (EIFER)
Institut für Informationswirtschaft und Marketing (IISM)
Publikationstyp Zeitschriftenaufsatz
Jahr 2018
Sprache Englisch
Identifikator ISSN: 2520-8942
URN: urn:nbn:de:swb:90-855229
KITopen ID: 1000085522
HGF-Programm 37.06.01; LK 01
Erschienen in Energy Informatics
Band 1
Heft 1
Seiten 1:11
Vorab online veröffentlicht am 22.08.2018
Schlagworte Demand response, Local energy market, Reinforcement learning, Agent-based simulation, Peer-to-peer trading
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