Copious and accessible sun radiation creates an attractive system for converting solar energy into electrical energy. The solar power plants are installed in remote locations and hence needs monitoring and controlling system from remotely. A computerized remote solar plant monitoring system with an enormous range of solar Photovoltaic (PV) exploitation needs well-developed systems with Web-based interfaces. This research work focuses an inter-disciplinary field of renewable solar power plants located in the southern region of India, integrating with recent digital technology of Internet of Things (IoT) which supports to monitor real-time data of solar irradiation (G), temperature (T), clearness index (K_t), panel voltage (V_pv), current (I_pv), peak power (P_mp), and tilt angle of solar panel (β°) and also to control the optimum inclination angle (β°_opt) of the solar panel for maximizing of PV power using Genetic Algorithm (GA). An integrated solar power plant with IoT is developed with hardware setup and virtually tested for enhancing the tracking behavior of the proposed system. The IoT-based control of solar power plant significantly improves the performance of monitoring and maintenance of the power plant parameters with cost-effectiveness.

丰富且容易获得的太阳辐射为将太阳能转化为电能创造了一个有吸引力的系统。太阳能发电厂安装在偏远地区，因此需要远程监控和控制系统。具有大量太阳能光伏 (PV) 开发的计算机化远程太阳能电站监控系统需要具有基于 Web 界面的开发良好的系统。这项研究工作的重点是位于印度南部地区的可再生太阳能发电厂的跨学科领域，与最新的物联网 (IoT) 数字技术相结合，支持监测太阳辐照 (G)、温度的实时数据( T )、净度指数(Kt )、面板电压( _{Vpv )})、电流 ( I _pv )、峰值功率 ( P _mp ) 和太阳能电池板的倾斜角 ( β °) 以及使用遗传算法控制太阳能电池板的最佳倾斜角 ( β ° _opt ) 以最大化 PV 功率(GA)。使用硬件设置开发了具有物联网的集成太阳能发电厂，并进行了虚拟测试，以增强拟议系统的跟踪行为。基于物联网的太阳能发电厂控制显着提高了发电厂参数的监控和维护性能，具有成本效益。