Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/215853 
Erscheinungsjahr: 
2020
Schriftenreihe/Nr.: 
Working Paper Series in Production and Energy No. 42
Verlag: 
Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP), Karlsruhe
Zusammenfassung: 
A paradigm shift has to be realized in future energy systems with high shares of renewable energy sources. The electrical demand has to react to the fluctuating electricity generation of renewable energy sources. To this end, flexible electrical loads like electric heating devices coupled with thermal storage or electric vehicles are necessary in combination with optimization approaches. In this paper, we develop a novel privacy-preserving approach for decentralized optimization to exploit load flexibility. This approach, which is based on a set of schedules, is referred to as SEPACO-IDA. The results show that our developed algorithm outperforms the other approaches for scheduling based decentralized optimization found in the literature. Furthermore, this paper clearly illustrates the suboptimal results for uncoordinated decentralized optimization and thus the strong need for coordination approaches. Another contribution of this paper is the development and evaluation of two methods for distributing a central wind power profile to the local optimization problem of distributed agents (Equal Distribution and Score-Rank-Proportional Distribution). These wind profile assignment methods are combined with different decentralized optimization approaches. The results reveal the dependency of the best wind profile assignment method on the used decentralized optimization approach.
Schlagwörter: 
Demand response
Decentralized optimization
Smart grid
Wind and PV integration
Electric heating
Electric vehicles
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