Adaptive photovoltaic solar module based on internet of things and web-based monitoring system

<span>This paper presents an intelligent of single axis automatic adaptive photovoltaic solar module. A static solar panel has an issue of efficiency on shading effects, irradiance of sunlight absorbed, and less power generates. This aims to design an effective algorithm tracking system and a prototype automatic adaptive solar photovoltaic (PV) module connected through </span><span>internet of things (IoT). The system has successfully designated on solving efficiency optimization. A tracking system by using active method orientation and allows more power and energy are captured. The solar rotation angle facing aligned to the light-dependent resistor (LDR) voltage captured and high solar panel voltage measured by using Arduino microcontroller. Real-time data is collected from the dynamic solar panel, published on Node-Red webpage, and running interactive via android device. The system has significantly reduced time. Data captured by the solar panel then analyzed based on irradiance, voltage, current, power generated and efficiency. Successful results present a live data analytic platform with active tracking system that achieved larger power generated and efficiency of solar panel compared to a fixed mounted array. This research is significant that can help the user to monitor parameters collected by the solar panel thus able to increase 51.82% efficiency of the PV module.</span>

Benchmarking study between capacitive and electronic load technic to track I-V and P-V of a solar panel

<p>To detect defects of solar panel and understand the effect of external parameters such as fluctuations in illumination, temperature, and the effect of a type of dust on a photovoltaic (PV) panel, it is essential to plot the Ipv=f(Vpv) characteristic of the PV panel, and the simplest way to plot this I-V characteristic is to use a variable resistor. This paper presents a study of comparison and combination between two methods: capacitive and electronic loading to track I-V characteristic. The comparison was performed in terms of accuracy, response time and instrumentation cost used in each circuit, under standard temperature and illumination conditions by using polycrystalline solar panel type SX330J and monocrystalline solar panels type ET-M53630. The whole system is based on simple components, less expensive and especially widely used in laboratories. The results will be between the datasheet of the manufacturer with the experimental data, refinements and improvements concerning the number of points and the trace time have been made by combining these two methods.</p>

A Review on Monitoring Solar System Parameters Using IoT

The most significant system for monitoring solar systems is the solar parameters monitoring system. Solar energy is a renewable energy source produced by solar panels. Solar energy is a renewable energy source produced by solar panels. Voltage, light intensity, and temperature are the parameters that the system measures. An Arduino Uno microcontroller board is used in the suggested monitoring system. Solar panel, LDR Sensor, LM 35, Arduino microcontroller, and resistors are used in the system. Light. LDR sensor is used to detect light intensity, L35 is used to measure temperature, and a voltage divider circuit is used to monitor voltage in this system. Keywords: Solar Panel, Monitoring, Renewable Energy, Solar Panel, Arduino Uno.

Bayesian Updating of Solar Panel Fragility Curves and Implications of Higher Panel Strength for Solar Generation Resilience

Solar generation can become a major and global source of clean energy by 2050. Nevertheless, few studies have assessed its resilience to extreme events, and none have used empirical data to characterize the fragility of solar panels. This paper develops fragility functions for rooftop and ground-mounted solar panels calibrated with solar panel structural performance data in the Caribbean for Hurricanes Irma and Maria in 2017 and Hurricane Dorian in 2019. After estimating hurricane wind fields, we follow a Bayesian approach to estimate fragility functions for rooftop and ground-mounted panels based on observations supplemented with existing numerical studies on solar panel vulnerability. Next, we apply the developed fragility functions to assess failure rates due to hurricane hazards in Miami-Dade, Florida, highlighting that panels perform below the code requirements, especially rooftop panels. We also illustrate that strength increases can improve the panels' structural performance effectively. However, strength increases by a factor of two still cannot meet the reliability stated in the code. Our results advocate reducing existing panel vulnerabilities to enhance resilience but also acknowledge that other strategies, e.g., using storage or deploying other generation sources, will likely be needed for energy security during storms.

Design and test of wirelessly powered IPMC artificial muscle for aquatic ecosystem health applications

Aquatic environments and water resources face a variety of risks from numerous sources of pollution. In this paper, we propose a preliminary mechanism for realizing robotic technology practically and cost-effectively for monitoring these pollutions. The presented system is a small robotic fish propelled by a beam of ionic polymer-metal composite (IPMC) artificial muscle that imitates the motion of a small Scorpis Georgiana fish. One of the superiorities of the proposed model is the IPMC actuation mechanism powered by a battery that is charged wirelessly from a solar panel source. This approach enables us to produce a robotic fish that works ceaselessly without being forced to carry the solar panel load. Moreover, we present a method to control the flapping motion of a robotic fish by taking advantage of a tiny Wi-Fi module that yields more working range, bulky data sending, low power consumption, simple programing, and convenient communication for creating a network with other similar robots. All these beneficial characteristics make the proposed structure a promising candidate for detecting pollution on the surface of aquatic environments and sending/recording necessary data in collaboration with desirable sensors. Theoretical considerations support experimental results reported in the paper.

Group decision-making with Fermatean fuzzy soft expert knowledge

With the rapid growth of population, the global impact of solar technology is increasing by the day due to its advantages over other power production technologies. Demand for solar panel systems is soaring, thus provoking the arrival of many new manufacturers. Sale dealers or suppliers face an uncertain problem to choose the most adequate technological solution. To effectively address such kind of issues, in this paper we propose the Fermatean fuzzy soft expert set model by combining Fermatean fuzzy sets and soft expert sets. We describe this hybrid model with numerical examples. From a theoretical standpoint, we demonstrate some essential properties and define operations for this setting. They comprise the definitions of complement, union and intersection, the OR operation and the AND operation. Concerning practice in this new environment, we provide an algorithm for multi-criteria group decision making whose productiveness and authenticity is dutifully tested. We explore a practical application of this approach (that is, the selection of a suitable brand of solar panel system). Lastly, we give a comparison of our model with certain related mathematical tools, including fuzzy and intuitionistic fuzzy soft expert set models.

Effects of Humidity on Dust Particle Removal during Solar Panel Cleaning

Solar panel cleaning is important to maintain the efficiency of energy production. In this research, we investigated the effects of relative humidity and condensation on the effectiveness of cleaning. The dust particles are subjected to various forces once they are deposited on the surface of a solar panel. When the dust particles continue to build up, they are also subjected to the adhesion forces from the neighboring dust particles. The adhesion forces from the substrates and the neighboring particles are dependent on the ambient conditions. Fundamentally, the interaction between the adhesion force of particle-particle and particle-substrate under various conditions was discussed in this manuscript.

Evaluation of the Effect of the Difference between the Real Attachment Unit and the Sealing in the Study of the Stress-Strain State of the Solar Panel of a Small Spacecraft as a Result of a Temperature Shock

The author of this scientific paper studies the stress-strain state of the solar panel of a small spacecraft after a temperature shock. The temperature shock is caused by the entry or exit of a small spacecraft into or out the Earth's shadow. In this work is considered a one-dimensional model of thermal conductivity. It is assumed that the solar radiation flux falls properly on the solar panel. Violation of normality due to deformations is neglected. A special feature of this work is to take into account the actual fixing of the solar panel. The boundary conditions in the form of a seal are preserved. However, the mobility of the smallest spacecraft is taken into account as a result of the occurrence of a longitudinal force in the solar panel during a temperature shock. The results are compared with the simulation data without taking into account the mobility of the small spacecraft. The results of this work can be used in the design of small spacecraft for technological purposes to meet the requirements for microaccelerations.