Battery energy management to minimize the grid fluctuation in residential microgrids
Author(s)
Islam, M
Yang, F
Hossain, J
Ekanayeke, C
Tayab, UB
Griffith University Author(s)
Year published
2018
Metadata
Show full item recordAbstract
The stochastic nature of renewable resources and loads leads to a large fluctuation of grid power in a grid-tied microgrid (MG) operation. Integrate battery energy storage system in MG is popular way to handle the stochastic nature of renewable resources to feed the stochastic load. In this paper, a battery management strategy is proposed using golden section search algorithm to minimize the grid power fluctuation by securing the battery constraints. The algorithm is applied in energy management system (EMS) of MG to minimize the grid peak power and grid power variation within a 24 hours duration by considering the random ...
View more >The stochastic nature of renewable resources and loads leads to a large fluctuation of grid power in a grid-tied microgrid (MG) operation. Integrate battery energy storage system in MG is popular way to handle the stochastic nature of renewable resources to feed the stochastic load. In this paper, a battery management strategy is proposed using golden section search algorithm to minimize the grid power fluctuation by securing the battery constraints. The algorithm is applied in energy management system (EMS) of MG to minimize the grid peak power and grid power variation within a 24 hours duration by considering the random nature of renewable generations. The proposed battery management strategy is verified through the simulation experiment in a residential AC MG.
View less >
View more >The stochastic nature of renewable resources and loads leads to a large fluctuation of grid power in a grid-tied microgrid (MG) operation. Integrate battery energy storage system in MG is popular way to handle the stochastic nature of renewable resources to feed the stochastic load. In this paper, a battery management strategy is proposed using golden section search algorithm to minimize the grid power fluctuation by securing the battery constraints. The algorithm is applied in energy management system (EMS) of MG to minimize the grid peak power and grid power variation within a 24 hours duration by considering the random nature of renewable generations. The proposed battery management strategy is verified through the simulation experiment in a residential AC MG.
View less >
Conference Title
Australasian Universities Power Engineering Conference, AUPEC 2018
Subject
Nanoelectronics