An IOT Based Solar Power Robotic Tracking & Monitoring System

2019 ◽  
Author(s):  
Pragati Gunjal ◽  
Aniket Gore ◽  
Indrajeet Khot ◽  
Kalyani Zanak
Author(s):  
Maisagalla Gopal ◽  
T Chandra Prakash ◽  
N Venkata Ramakrishna ◽  
Bonthala Prabhanjan Yadav

2021 ◽  
Vol 9 (2) ◽  
pp. 27-36
Author(s):  
Sheikh Hasib Cheragee ◽  
Nazmul Hassan ◽  
Sakil Ahammed ◽  
Abu Zafor Md. Touhidul Islam

We have Developed an IoT-based real-time solar power monitoring system in this paper. It seeks an opensource IoT solution that can collect real-time data and continuously monitor the power output and environmental conditions of a photovoltaic panel.The Objective of this work is to continuously monitor the status of various parameters associated with solar systems through sensors without visiting manually, saving time and ensures efficient power output from PV panels while monitoring for faulty solar panels, weather conditionsand other such issues that affect solar effectiveness.Manually, the user must use a multimeter to determine what value of measurement of the system is appropriate for appliance consumers, which is difficult for the larger System. But the Solar Energy Monitoring system is designed to make it easier for users to use the solar system.This system is comprised of a microcontroller (Node MCU), a PV panel, sensors (INA219 Current Module, Digital Temperature Sensor, LDR), a Battery Charger Module, and a battery. The data from the PV panels and other appliances are sent to the cloud (Thingspeak) via the internet using IoT technology and a Wi-Fi module (NodeMCU). It also allows users in remote areas to monitor the parameters of the solar power plant using connected devices. The user can view the current, previous, and average parameters of the solar PV system, such as voltage, current, temperature, and light intensity using a Graphical User Interface. This will facilitate fault detection and maintenance of the solar power plant easier and saves time.


2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Hong-Chan Chang ◽  
Shang-Chih Lin ◽  
Cheng-Chien Kuo ◽  
Hao-Ping Yu

This study endeavors to develop a cloud monitoring system for solar plants. This system incorporates numerous subsystems, such as a geographic information system, an instantaneous power-consumption information system, a reporting system, and a failure diagnosis system. Visual C# was integrated with ASP.NET and SQL technologies for the proposed monitoring system. A user interface for database management system was developed to enable users to access solar power information and management systems. In addition, by using peer-to-peer (P2P) streaming technology and audio/video encoding/decoding technology, real-time video data can be transmitted to the client end, providing instantaneous and direct information. Regarding smart failure diagnosis, the proposed system employs the support vector machine (SVM) theory to train failure mathematical models. The solar power data are provided to the SVM for analysis in order to determine the failure types and subsequently eliminate failures at an early stage. The cloud energy-management platform developed in this study not only enhances the management and maintenance efficiency of solar power plants but also increases the market competitiveness of solar power generation and renewable energy.


2019 ◽  
Vol 10 (2) ◽  
Author(s):  
Dragoljub Mirjanić ◽  
Tomislav Pavlović ◽  
Ivana Radonjić ◽  
Darko Divnić

The paper provides basic information on fixed (stationary), one-axis tracking and dual-axis tracking PV solar power plants. In this regard, a schematic overview of the PV solar power plant and basic information on its components (solar modules, inverters, monitoring system, etc.) are given. The following is a description of the fixed, one-tracking and dual-tracking PV solar power plant and their energy efficiency. Finally, measured results of power and temperature of fixed and dual-axis tracking solar modules of 50 W are presented.


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