DocumentCode :
1721716
Title :
Application genetic algorithms for load management in refrigerated warehouses with wind power penetration
Author :
Zong, Yi ; Cronin, Tom ; Gehrke, Oliver ; Bindner, Henrik ; Hansen, Jens Carsten ; Latour, Mikel Iribas ; Arcauz, Oihane Usunariz
Author_Institution :
Nat. Lab. for Sustainable Energy, Riso DTU, Roskilde, Denmark
fYear :
2009
Firstpage :
1
Lastpage :
6
Abstract :
Wind energy is produced at random times, whereas the energy consumption pattern shows distinct demand peaks during day-time and low levels during the night. The use of a refrigerated warehouse as a giant battery for wind energy is a new possibility that is being studied for wind energy integration as well as a way to store electricity produced during night-time by wind turbines. The controller for load management in a refrigerated warehouse with wind power penetration by GA-based is introduced in this paper. The objective function is to minimize the energy consumption for operating the refrigerated warehouse. It can be seen that the GA-based control strategy achieves feasible results for operating the temperature in refrigerated warehouse. Balancing the wind power production with refrigerated warehouse load management promises to be a clean and cost effective method. For refrigerated warehouse owners, it has the potential to lower operational costs.
Keywords :
energy consumption; genetic algorithms; load management; refrigeration; wind power; energy consumption pattern; genetic algorithms; load management; refrigerated warehouses; wind energy; wind power penetration; wind turbines; Batteries; Costs; Energy consumption; Genetic algorithms; Load management; Production; Refrigeration; Temperature control; Wind energy; Wind turbines; Genetic algorithm; load management; optimization; wind energy;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
PowerTech, 2009 IEEE Bucharest
Conference_Location :
Bucharest
Print_ISBN :
978-1-4244-2234-0
Electronic_ISBN :
978-1-4244-2235-7
Type :
conf
DOI :
10.1109/PTC.2009.5282071
Filename :
5282071
Link To Document :
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