ANFIS Based MPPT For PVWPS Using BLDC Motor | ||||
| The Egyptian International Journal of Engineering Sciences and Technology | ||||
| Articles in Press, Accepted Manuscript, Available Online from 25 May 2025 | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/eijest.2025.379924.1334 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
hany Mohamed Deeb  1; Mohamed Abdel Fattah Enany2; sameh ibrahim selem3
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| 1faculty of engineering Zagazig university | ||||
| 2Electrical Power & Machines Department, Faculty of Engineering, Zagazig University. | ||||
| 3Faculty of Engineering, Zagazig University, Zagazig, Egypt | ||||
| Abstract | ||||
| In recent years, researches on photovoltaic (PV) systems have focused on reducing costs and maximizing conversion efficiency. To achieve maximum efficiency, PV arrays must operate at their maximum power points (MPP), where they generate energy with minimal losses. However, since solar cells exhibit variable current and voltage characteristics depending on irradiation and temperature, an effective maximum power point tracking (MPPT) control strategy is required. This study presents a technical evaluation of a PV system integrated with a brushless DC (BLDC) motor for a water pumping application. The system is modeled in MATLAB/Simulink, incorporating a DC-DC converter and an adaptive neuro-fuzzy inference system (ANFIS) for MPPT control. The ANFIS controller is trained offline to optimize PV output power and regulate water flow rate. A mathematical iteration technique is also introduced for comparative analysis. The proposed system enhances performance by adapting to varying solar insolation and temperature conditions, ensuring maximum power extraction and optimal water flow. Results demonstrate the accuracy, robustness, and effectiveness of the ANFIS-based approach in improving system efficiency, economic feasibility, and fault detection. | ||||
| Keywords | ||||
| Carbon dioxide; Sulfur dioxide; power-voltage and current-voltage | ||||
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