Increasing the efficiency of local energy markets through residential demand response

被引:0
|
作者
Mengelkamp E. [1 ]
Bose S. [1 ,2 ]
Kremers E. [2 ]
Eberbach J. [2 ]
Hoffmann B. [2 ]
Weinhardt C. [1 ]
机构
[1] Karlsruhe Institute of Technology, Fritz-Erler-Str. 23, Karlsruhe
[2] European Institute for Energy Research, Emmy-Noether-Str. 11, Karlsruhe
关键词
Agent-based simulation; Demand response; Local energy market; Peer-to-peer trading; Reinforcement learning;
D O I
10.1186/s42162-018-0017-3
中图分类号
学科分类号
摘要
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 10c€/kWh and 40%. © 2018, The Author(s).
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