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7166686 
Journal Article 
A new prediction model of battery and wind-solar output in hybrid power system 
Mirzapour, F; Lakzaei, M; Varamini, G; Teimourian, M; Ghadimi, N; , 
2019 
Yes 
Journal of Ambient Intelligence and Humanized Computing
ISSN: 1868-5137 
SPRINGER HEIDELBERG 
HEIDELBERG 
77-87 
WOS:000456951400006 
In this paper short term power forecast of wind and solar power is proposed to evaluate the available output power of each production component. In this model, lead acid batteries used in proposed hybrid power system based on wind-solar power system. So, before the predicting of power output, a simple mathematical approach to simulate the lead-acid battery behaviors in stand-alone hybrid wind-solar power generation systems will be introduced. Then, the proposed forecast problem will be evaluated which is taken as constraint status through state of charge (SOC) of the batteries. The proposed forecast model includes a feature selection filter and hybrid forecast engine based on neural network (NN) and an intelligent evolutionary algorithm. This method not only could maintain the SOC of batteries in suitable range, but also could decrease the on-or-off switching number of wind turbines and PV modules. Effectiveness of the proposed method has been applied over real world engineering data. Obtained numerical analysis, demonstrate the validity of proposed method.