2015
DOI: 10.1080/15325008.2015.1018457
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A Control Strategy for Hybrid Autonomous Power System with a Battery Management Scheme

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Cited by 6 publications
(2 citation statements)
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References 31 publications
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“…In [6], [20] and [21] the control action for the next time step is obtained by solving an online finite horizon open-loop optimal control problem, using the current state of the plant as the initial state, known as Model Predictive Control (MPC). In [22], [23], [24], [25] and [26] the EMS is carried out from a dynamic control model of the elements in the microgrid, which calculates the optimal operation taking into account stability and frequency constraints.…”
Section: )mentioning
confidence: 99%
“…In [6], [20] and [21] the control action for the next time step is obtained by solving an online finite horizon open-loop optimal control problem, using the current state of the plant as the initial state, known as Model Predictive Control (MPC). In [22], [23], [24], [25] and [26] the EMS is carried out from a dynamic control model of the elements in the microgrid, which calculates the optimal operation taking into account stability and frequency constraints.…”
Section: )mentioning
confidence: 99%
“…Also, Aravind et al [14] devised a control strategy for a hybrid power system to attain a smoother power transition between diesel generators and battery energy storage systems under temporary conditions. Aravind et al [14] formulated a battery management scheme to maintain the battery state of charge at high levels of 70% and 80% under transient conditions and hold the diesel generator power above its nominal value. The simulation results showed the smooth sharing of power between the diesel generator and battery energy storage system with a maintained system frequency.…”
Section: Genset Efficiencymentioning
confidence: 99%