In this paper, we present a low-cost, stand-alone sensory platform developed for in situ monitoring of environmental parameters, for use in the Amazon region in the north of Brazil. The mission of the platform is to perform monitoring and identification of overirradiance (solar irradiance > 1000 W/m²) and extreme overirradiance events (solar irradiance > 1300 W/m²) using a photovoltaic based irradiance sensor. The sensory platform was built using the ESP8266 microcontroller, an open embedded computer capable of Wi-Fi communication using the IEEE 802.11 standard, and small photovoltaic modules, air temperature, atmospheric pressure, voltage, and current sensors, enabling the development of a low-cost system (€70/R$350.00 BRL). Calibration and tests were conducted at the Federal University of Pará (UFPA), Belém campus, Pará, where the platform measured an extreme overirradiance of 1321 W/m² at a low-latitude (1 °S) and low altitude (7 m above sea level).

Nowadays, the market for natural gas production and its use as a source of energy supply has been growing substantially in Brazil. However, the use of tools that assist the industry in the management of production can be essential for the strategic decision-making process. In this intuit, this work aims to evaluate the formulation of Holt Winter's additive and multiplicative time series to forecast Brazilian natural gas production. A comparison between the models and their forecast play a vital role for policymakers in the strategic plan, and the models estimated production values ​​for the year 2018 based on the information contained in the interval between 2010 and 2017. Therefore, It was verified that the multiplicative method had a good performance so that we can conclude this formulation is ideal for such an application since all the predicted results by this model showed greater accuracy within the 95% confidence interval.

This research shows the methodology results for outdoor characterization by the I-V curves of the PV power generators at the biggest Brazilian rooftop PV power plant mounted at the Mineirão Football Stadium. The experimental results of the methodology were obtained by a measurement campaign using two capacitive loads. This work identified a significant difference when these measurements were extrapolated to standard test conditions (STC) and compared to the rated power data shown on the PV modules’ label at strings: between 24.12% to 26.19% lower. Results showed a contribution of soiling in a power reduction of about 6.7% on average. Additionally, it was considered an uncertain method, and AC electrical parameters were monitored. The reference PV module’s calibration was carried out with great attention—the measurements were made with the PV device under test (DUT), guaranteeing the same real operating conditions for the reference PV module and the PV string as DUT. This measurement method has allowed a better characterization of the uncertainty associated with the measurement process. Finally, this study demonstrates the importance of investigating the actual power of the installed PV generators and how these measurements are essential to guaranteeing energy production following the owner’s expectations.

This paper applies different methodologies through measurement and simulation for the partial shading analysis of solar photovoltaic (SPV) arrays. A two-diode photovoltaic solar cell model evaluates SPV arrays under shading conditions. Experimental data from two identical 1.5 kWp PV generators were used as a study case. One is subjected to shading caused by the branches of a tree, resulting in its electricity production being affected for several days, and the other is shadow-free. The authors use a methodology based on short circuit of the solar cells to determine the different irradiance levels. It was considered because it avoids using several irradiance sensors to map the shaded and unshaded regions in a shadow SPV array. The two-diode photovoltaic solar cell model used was developed in matlab/simulink. The applied model and the map irradiance methodology can be used to represent current–voltage (IV) curves in complex shading. For example, what could help identify if a given SPV array is working on a global maximum power point or a local maximum power point. Furthermore, the experimental results demonstrated that the model and methodology are useful in understanding what happens with SPV arrays in very complex shadow situations.

The purpose of this article is to present an architecture of a reduced-size greenhouse, monitored and controled via Internet of Things (IoT). As an experiment, seeds of Apuleia leiocarpa (Vog.) Macbr were used and at 25oC, 75% germination was obtained. In order to apply the automation on seed germination process, sensors are required and a prototype has been built with support of a computational system installed in its interior by including the control in conserving temperature, humidity and the degree of brightness inside the structure. In this sense, sensors are used for monitoring and control of the variables that most influence in the development of a vegetal species. The proposed system has a cloud-based storage and the effective contributions of the computer system are started from the web platform, transfer the set-points to the controllers, and upload data read from sensors to the same web page.