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|Booktitle=Proceedings of the main European events on Evolutionary Computation | |Booktitle=Proceedings of the main European events on Evolutionary Computation | ||
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|Address=Malaga, Spain | |Address=Malaga, Spain | ||
|Editor=Jin-Kao Hao and Martin Middendorf | |Editor=Jin-Kao Hao and Martin Middendorf | ||
| + | |Series=LNCS | ||
| + | |Number=7245 | ||
|Note=to appear. | |Note=to appear. | ||
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{{Publikation Details | {{Publikation Details | ||
|Abstract=In this paper, we focus on a real world scenario of energy management of a smart home. External variable signals, reflecting the low voltage grid's state, are used to address the challenge of balancing energy demand and supply. The problem is formulated as a nonlinear integer programming problem and a load management system, based on a customized evolutionary algorithm with local search, is proposed to control intelligent appliances, decentralized power plants and electrical storages in an optimized way with respect to the given external signals. The nonlinearities present in the integer programming problem makes it difficult for exact solvers. The results of this paper show the efficacy of evolutionary algorithms for solving such combinatorial problems. | |Abstract=In this paper, we focus on a real world scenario of energy management of a smart home. External variable signals, reflecting the low voltage grid's state, are used to address the challenge of balancing energy demand and supply. The problem is formulated as a nonlinear integer programming problem and a load management system, based on a customized evolutionary algorithm with local search, is proposed to control intelligent appliances, decentralized power plants and electrical storages in an optimized way with respect to the given external signals. The nonlinearities present in the integer programming problem makes it difficult for exact solvers. The results of this paper show the efficacy of evolutionary algorithms for solving such combinatorial problems. | ||
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|Projekt=MEREGIOmobil | |Projekt=MEREGIOmobil | ||
|Forschungsgruppe=Effiziente Algorithmen | |Forschungsgruppe=Effiziente Algorithmen | ||
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| + | |Forschungsgebiet=Evolutionäre Algorithmen | ||
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Version vom 13. Februar 2012, 08:43 Uhr
Electrical Load Management in Smart Homes Using Evolutionary Algorithms
Electrical Load Management in Smart Homes Using Evolutionary Algorithms
Published: 2012
April
Herausgeber: Jin-Kao Hao and Martin Middendorf
Buchtitel: Proceedings of the main European events on Evolutionary Computation
Nummer: 7245
Reihe: LNCS
Verlag: Springer
Erscheinungsort: Malaga, Spain
Referierte Veröffentlichung
Note: to appear.
BibTeX
Kurzfassung
In this paper, we focus on a real world scenario of energy management of a smart home. External variable signals, reflecting the low voltage grid's state, are used to address the challenge of balancing energy demand and supply. The problem is formulated as a nonlinear integer programming problem and a load management system, based on a customized evolutionary algorithm with local search, is proposed to control intelligent appliances, decentralized power plants and electrical storages in an optimized way with respect to the given external signals. The nonlinearities present in the integer programming problem makes it difficult for exact solvers. The results of this paper show the efficacy of evolutionary algorithms for solving such combinatorial problems.
Evolutionäre Algorithmen, Energieinformatik