Alireza Rezvani ¹, Maziar Izadbakhsh ¹, Majid Gandomkar ², Saeed Vafaei ²

Affiliations
1 Young Researchers and Elites Club, Saveh Branch, Islamic Azad University, Saveh, IR
2 Department of Electrical Engineering, Saveh Branch, Islamic Azad University, Saveh, IR

Abstract

The output characteristics of Photovoltaic (PV) arrays are nonlinear and change with the cell's temperature and solar radiation. Maximum Power Point Tracking (MPPT) methods are used to maximize the PV array output power by tracking continuously the maximum power point (MPP). This paper presents an integrated offline Genetic Algorithm (GA) and artificial neural network (ANN) to track the solar power optimally based on various operation conditions due to the uncertain climate change. Data are optimized by GA and then these optimum values are used in neural network training. The obtained results show minimal error of MPP, optimal voltage (Vmpp) and superior capability of the suggested method in the MPPT. The simulation results are presented by using Matlab/Simulink and show that ANN-GA controller of grid-connected mode can meet the need of load easily and have fewer fluctuations around the maximum power point; also, this method has well regulated PV output power and it produces extra power rather than Modified Perturb&Observe (MP&O) method for different conditions. Moreover, to control both line voltage and current, a grid side P-Q controller has been applied.

Keywords

Genetic Algorithm, Neural Network, Photovoltaic, P-Q Control.

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Alireza Rezvani ¹, Maziar Izadbakhsh ¹, Majid Gandomkar ², Saeed Vafaei ²

Affiliations
1 Young Researchers and Elite Club, Saveh Branch, Islamic Azad University, Saveh, IR
2 Department of Electrical Engineering, Saveh Branch, Islamic Azad University, Saveh, IR

Abstract

Nowadays, it has been a developing consideration towards utilization of photovoltaic (PV) system. This paper proposes the Adaptive Neuro-Fuzzy Inference System (ANFIS) and an integrated offline Genetic Algorithm (GA) to track the PV power based on different circumstances due to the various climate changes. Training data in ANFIS are optimized by GA. The proposed controller is accomplished and studied applying Matlab/Simulink software. The results show minimal error of Maximum Power Point (MPP), Optimal Voltage (V_mpp) and superior capability of the suggested method in MPP tracking.

Keywords

ANFIS, GA, MPPT, Photovoltaic System.

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Maziar Izadbakhsh ¹, Alireza Rezvani ¹, Majid Gandomkar ², Sohrab Mirsaeidi ¹

Affiliations
1 Young Researchers and Elite Club, Saveh Branch, Islamic Azad University, Saveh, IR
2 Department of Electrical Engineering, Saveh Branch, Islamic Azad University, Saveh, IR

Abstract

Dynamic performance investigation of Wind Turbine (WT) implementing Permanent Magnet Synchronous Generator (PMSG) under variable wind speeds and load circumstances are investigated in this paper. The injected active and reactive power respectively regulate by d-axis current and q-axis current using active and reactive power (P-Q) control method. The P-Q controller can adjust DC link voltage, active and reactive power. The generated reactive power via the WT is adjusted at zero so that the Power Factor (PF) is retained unity. The proposed system is containing of WT, PMSG, rectifier, a DC bus by capacitor and voltage source inverter. The simulation results depict the accuracy and credibility of the WT and the strategy of inverter controller. The thorough Wind Power Generation System (WPGS) and power electronic converters interfaces are proposed by using Matlab/Simulink.

Keywords

Dynamic Analysis, Load Circumstances, PMSG, P-Q Controller, Wind Turbine (WT)

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