Development of a Fault Diagnosis System for Photovoltaic Module Array Based on Internet of Things

• Main Authors: TSAI,JEN-HSIANG, 蔡仁翔
• Other Authors: CHAO,KUEI-HSIANG
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/dx6b8x

碩士 === 國立勤益科技大學 === 電機工程系 === 107 === The main purpose of this thesis is to develop a photovoltaic module array fault diagnosis system with IOT function. First, the modules are connected into a four series three paralles configuration with total-cross-tied construction to increase the power generation of the overall photovoltaic system, and to consider the P-V characteristic curve produces multi peaks when partial modules of PV array are shaded. Therefore, this paper proposes a weight optimized particle swarm optimization algorithm for global maximum power tracking to ensure that the PV module array can output maximum power. Then, in the photovoltaic module array, a current sensor is connected across the connecting line segment, so that when the photovoltaic module array is shaded or faulty, the current of the line segment across the module can be sensed. Through the direction of the line segment, the correct position of the shading or faulty module can be detected. Then, the information is uploaded to the cloud server through the LoRa wireless transmission module, and forward it with the professional communication interface for maintenance personnel to troubleshoot. In order to make the algorithm of this system have a good computing speed, the weight optimization particle swarm optimization algorithm is implemented with digital signal processor. Finally, the feasibility of the photovoltaic module array fault diagnosis system with IOT function is verified by the measured results.