Mobile phone detection photovoltaic inverter

Can smartphones be used in solar photovoltaic (PV) energy field?

Author to whom correspondence should be addressed. Smartphones and tablets can be effectively used in the solar photovoltaic (PV) energy field for different purposes because of their versatile capabilities incorporating hardware and software functionalities.

Can IoT-based embedded monitoring system be used for solar PV power conditioning unit?

Arduino, Mega 2560, ESP01. A low–cost IoT-based embedded monitoring system for solar PV systems is discussed in Ref. , where a GPRS module and a low–cost microcontroller were used. The authors present a procedure for remote monitoring for solar PV power conditioning unit, but experimental verification is not presented.

How is IoT affecting PV system monitoring & remote sensing?

The internet of things (IoT) enables communication and data sharing among a wide variety of devices, systems, and services. Over the last few years, IoT approaches have also been investigated in PV system monitoring and remote sensing in response to an industry need to effect better fault diagnostics and prognostics [10, 11].

Which monitoring systems are suitable for small-scale PV plants?

However, few of the monitoring systems comply with the international standard (IEC61724) reported in Ref. , including class B and class C that are the most appropriate for small-scale PV plants, which decrease significantly the quality of the designed monitoring system.

Can intelligent FDD be used for remote sensing of PV plants?

Fig. 21 shows a suggestion of a smart configuration based on IoT with embedded intelligent FDD into a low-cost device for remote sensing of PV plants. It consists of sensors for measuring currents, voltages, and cell temperature in each PV string, and an irradiance sensor. Fig. 21.

Can Ai be used in solar PV farms?

The application of AI techniques in solar PV farms has been available for the last two decades in order to improve modelling, control optimization, and output power forecasting efficacy of the sizeable datasets [3, 4].