Sizing Control and Hardware Implementation of a Hybrid Wind-Solar Power System, Based on an ANN Approach, for Pumping Water

Table 7

Performance comparison.

References	Algorithms		Tracking efficiency (%)	Frequency max (Hz)
Proposed algorithm	ANN structures for the wind turbine	20 neurons and sigmoid transfer function for the first layer; 1 neuron as well as linear transfer function for the second layer	99.61	62.8
Izadbakhsh et al. [16]	Fuzzy logic for the wind turbine	5 membership trapezoidal transfer function for each input or output	97.10	96.2
Prakash and Sankar [17]	ANN for the wind turbine	Modified Elman neural network algorithm	95.39	80
Priyadarshi et al. [19]	ANN-fuzzy logic for the PV system	5 Gaussian membership functions for the fuzzy controller and 5 layers for the ANN controller	90.2	94.3
Cheng et al. [20]	Fuzzy logic for the PV system	2 trapezoidal and 3 triangular membership functions using PSO technique to optimize input membership function	96.65%	76