Monitoring and data acquisition are essential to recognize the renewable resources available on-site, evaluate electrical conversion efficiency, detect failures, and optimize electrical production. Commercial monitoring systems for the photovoltaic system are generally expensive and closed for modifications. This work proposes a low-cost real-time internet of things system for micro and mini photovoltaic generation systems that can monitor continuous voltage, continuous current, alternating power, and seven meteorological variables. The proposed system measures all relevant meteorological variables and directly acquires photovoltaic generation data from the plant (not from the inverter). The system is implemented using open software, connects to the internet without cables, stores data locally and in the cloud, and uses the network time protocol to synchronize the devices’ clocks. To the best of our knowledge, no work reported in the literature presents these features altogether. Furthermore, experiments carried out with the proposed system showed good effectiveness and reliability. This system enables fog and cloud computing in a photovoltaic system, creating a time series measurements data set, enabling the future use of machine learning to create smart photovoltaic systems.
The photonic band gap (PBG) crystals have been used as a perfectly reflecting substrate for many millimeter wave applications. In this work the fin line directional coupler with PBG substrate is analyzed using the TTL-Transverse Transmission Line method. Compared to odder full wave methods the TTL is an efficient tool to determine the coupler characteristics, making possible a significant algebraic simplification of the equations involved in the process. In order to analyze the structure the effective dielectric constant, the attenuation constant and the coupling were determined. News results obtained for this application and the conclusions are presented.
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