Introduction of photovoltaic automatic weather station FT-FGF9

In the western region of China, which is rich in solar energy resources, in order to ensure its energy supply, a large number of distributed photovoltaic power stations are needed to realize the efficient use of renewable energy. Although photovoltaic power generation is a new energy, clean and pollution-free, and still a steady stream, it has a fatal shortcoming, just like agriculture, it is very dependent on the "weather" conditions. The emergence of extreme weather often threatens power generation equipment and power generation, so the photovoltaic industry is in urgent need of accurate weather forecasting services. The photovoltaic automatic weather station is an instrument that provides meteorological data, and its main responsibility is to record every minute and every second of meteorological data in real time to assist in making accurate meteorological predictions.

In the process of research and development and production for many years, Fengtu Technology has accumulated a complete and practical photovoltaic intelligent automatic weather station program. The scheme consists of three parts: 1) acquisition module; 2) Data processing and storage module; 3) Alarm module.

FT-FGF9 is a weather station launched by Fengtu Technology, a weather station suitable for the photovoltaic field, which is based on Internet of Things sensors and wireless transmission technology. Real-time monitoring of ambient temperature, ambient humidity, maximum temperature, minimum temperature, dew point temperature, wind speed, 2-minute wind speed, 10-minute wind speed, wind direction, air pressure, component temperature, horizontal total radiation (day, month, year cumulative), etc. The product wirelessly transmits the monitored data to the server for analysis and processing and then outputs it to the user. When the temperature or water vapor in the air in a certain area is monitored to reach a certain value, the system will send an early warning signal to the user according to the historical weather conditions and local meteorological conditions, and remind the relevant personnel to take corresponding measures in the first time, thus improving the work efficiency.