Single Phase Water Pumping System using Adaptive Neuro Fuzzy Inference MPPT for PV system

M. Kabilan, V. Gopalakrishnan
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Abstract

The demand for water in India steadily increases as the population grows. Due to its numerous advantages, research in AC motor-based Water Pumping Systems (WPS) has recently got a lot of attention. Because of its natural abundance and ecologically beneficial properties, renewable energy-based solar photovoltaic (PV) generation is the ideal substitute for conventional energy sources. Maximum power extraction from the PV system is critical for increasing solar power generation efficiency. This proposed work presents a solar power system using Adaptive Neuro-Fuzzy Inference System (ANFIS) Maximum Power Point Tracking (MPPT) for pumping system. A MPPT controller based on ANFIS has been introduced in this research. This approach has the advantage of having a higher tracking accuracy. This tracker captures irradiance and temperature from the solar panel as inputs. This system uses a battery backup for energy storage purpose. The battery is recharged using the solar supply. In this system, Pulse Width Modulated (PWM) inverter is used, where it converts the battery voltage (DC), into AC voltage for running the pumping system. For validation, the proposed model is analysed using MATLAB/Simulink.
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基于自适应神经模糊推理的光伏系统单相抽水系统
随着人口的增长,印度对水的需求也在稳步增长。基于交流电机的水泵系统(WPS)由于其诸多优点,近年来受到了广泛的关注。基于可再生能源的太阳能光伏发电由于其丰富的自然资源和生态效益,是传统能源的理想替代品。光伏发电系统的最大功率提取是提高太阳能发电效率的关键。本文提出了一种采用自适应神经模糊推理系统(ANFIS)最大功率点跟踪(MPPT)的太阳能发电系统。本文介绍了一种基于ANFIS的MPPT控制器。该方法具有跟踪精度较高的优点。这个跟踪器从太阳能电池板获取辐照度和温度作为输入。该系统使用备用电池进行能量存储。电池使用太阳能电源充电。该系统采用脉宽调制(PWM)逆变器,将电池电压(直流)转换为交流电压,用于泵送系统的运行。为了验证所提出的模型,使用MATLAB/Simulink对其进行了分析。
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