Super-linear speedup for real-time condition monitoring using image processing and drones

Real-time inspections for the large-scale solar system may take a long time to get the hazard situations for any failures that may take place in the solar panels normal operations, where prior hazards detection is important. Reducing the execution time and improving the system’s performance are the ultimate goals of multiprocessing or multicore systems. Real-time video processing and analysis from two camcorders, thermal and charge-coupling devices (CCD), mounted on a drone compose the embedded system being proposed for solar panels inspection. The inspection method needs more time for capturing and processing the frames and detecting the faulty panels. The system can determine the longitude and latitude of the defect position information in real-time. In this work, we investigate parallel processing for the image processing operations which reduces the processing time for the inspection systems. The results show a super-linear speedup for real-time condition monitoring in large-scale solar systems. Using the multiprocessing module in Python, we execute fault detection algorithms using streamed frames from both video cameras. The experimental results show a super-linear speedup for thermal and CCD video processing, the execution time is efficiently reduced with an average of 3.1 times and 6.3 times using 2 processes and 4 processes respectively.

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.

Non-Isolated Interleaved Hybrid Boost Converter for Renewable Energy Applications

DC-DC boost converters are necessary to extract power from solar panels. The output voltage from these panels is far lower than the utility voltage levels. One of the main functions of the boost converter is to provide a considerable step-up gain to interface the panel to the utility lines. There are several techniques used to boost the low panel voltage. Some of the issues faced by these topologies are a high duty ratio operation, complex design with multiple active switches and discontinuous input current that affects the power drawn from the panel. This paper presents a boost converter topology that combines the advantages of an interleaved structure, a voltage lift capacitor and a passive voltage multiplier network. A mathematical analysis of the proposed converter during its various modes of operation is presented. A 100 W prototype of the proposed converter is designed and tested. The prototype is controlled by a PIC16F18455 microcontroller. The converter is capable of achieving a gain of 10 without operating at extremely high duty ratios. The voltage stress of the switch is far lower than the maximum output voltage.

Agent-Based Modelling of Urban District Energy System Decarbonisation—A Systematic Literature Review

There is an increased interest in the district-scale energy transition within interdisciplinary research community. Agent-based modelling presents a suitable approach to address variety of questions related to policies, technologies, processes, and the different stakeholder roles that can foster such transition. However, it is a largely complex and versatile methodology which hinders its broader uptake by researchers as well as improved results. This state-of-the-art review focuses on the application of agent-based modelling for exploring policy interventions that facilitate the decarbonisation (i.e., energy transition) of districts and neighbourhoods while considering stakeholders’ social characteristics and interactions. We systematically select and analyse peer-reviewed literature and discuss the key modelling aspects, such as model purpose, agents and decision-making logic, spatial and temporal aspects, and empirical grounding. The analysis reveals that the most established agent-based models’ focus on innovation diffusion (e.g., adoption of solar panels) and dissemination of energy-saving behaviour among a group of buildings in urban areas. We see a considerable gap in exploring the decisions and interactions of agents other than residential households, such as commercial and even industrial energy consumers (and prosumers). Moreover, measures such as building retrofits and conversion to district energy systems involve many stakeholders and complex interactions between them that up to now have hardly been represented in the agent-based modelling environment. Hence, this work contributes to better understanding and further improving the research on transition towards decarbonised society.

Functioning Fuzzy Logic in Optimizing the Solar Systems Work

Fuzzy logic has been used in many fields, either to control a specific movement, improve the productivity of a machine, or monitor the work of an electrical or mechanical system or the like. In this chapter, we will discuss what are the basic factors that must be taken to use the fuzzy logic in the aforementioned matters in general, and then focus on its employment in the field of renewable energy. Three main axes for renewable energy are solar panels, a wind turbine and finally, solar collectors. The key to working and the basis of the static system is the mechanism for selecting the inputs that directly affect the output in addition to the methods and activation functions of the fuzzy logic.

PARAMETERS MONITORING ORGANIZATION OF THE SOLAR PANELS EXPERIMENTAL STAND

Актуальность разработки обусловлена необходимостью создания устройства для сбора и обработки информации с экспериментального стенда солнечных панелей. Назначением стенда является получение достоверных данных для верификации моделей оценки показателей гелиопотенциала, использующихся при обосновании эффективности применения солнечных электростанций на территории восточных регионов России. Дано описание основного и вспомогательного оборудования экспериментального стенда. Солнечные панели стенда разноориентированы для определения наиболее эффективного угля наклона и обоснования необходимости применения следящей за солнцем системы. Для снятия и записи мгновенной мощности солнечных панелей разработано устройство на основе микроконтроллера Arduino. Для мониторинга показаний силы тока используется шунтовый амперметр, подключаемый в разрыв цепи питания. Приведена схема счётчика тока и описана его работа. Приведены первичные результаты собранных данных. Намечены основные этапы дальнейшей обработки данных. The relevance of the presented development is due to the need to create a device to read and process information from an experimental array of solar panels. The purpose of the array is to obtain reliable data for the verification of models for estimating photovoltaic power potential indicators used in justifying the feasibility of the adoption of solar power plants in the eastern regions of Russia. We present a description of the main and auxiliary equipment of the experimental array. The array's solar panels are arranged in different ways so as to determine the most efficient tilt angle and justify the need to use a sun tracking system. The proprietary device based on the Arduino microcontroller was designed to read and write the value of instantaneous power of solar panels. To monitor the readings of the amperage, a shunt ammeter is used, which is connected to the gap of the power circuit. The study provides a diagram of the current meter and describe its operation. We outlined the main stages of subsequent data processing.

ESTIMATION OF PHOTOVOLTAIC POTENTIAL AT THE URBAN LEVEL FROM 3D CITY MODEL (SOLAR CADASTER): CASE OF CASABLANCA CITY, MOROCCO

Nowadays, the use of solar energy in buildings, especially photovoltaic energy, has undergone a great evolution in the world, thanks to various technological advances and to incentive programs. Related to this topic, the solar cadaster is an important interactive tool to predict the solar potential in an urban environment. The main objective of this research work is to estimate the photovoltaic energy potential of roofs based on aerial photogrammetry and GIS processing. The location chosen for the study is the Maarif district located in the city of Casablanca in order to raise awareness of the public and decision makers to this energy potential through a geoportal that will be developed for this purpose. The tool proposed in this research work makes it possible to evaluate the solar irradiation on a part of the territory of Casablanca with a sufficiently satisfactory precision and reliability, this thanks to the precise reconstruction of the territory in 3D urban model called digital surface model (DSM) at 50 cm resolution by techniques known as photogrammetry which makes it possible to carry out measurements extracted from a stereoscopic pairs, by using the parallax and the correlation between the digital images taken from various points of view. The analysis was used on the basis of specific algorithms and several factors including geographical location, shade, tilt, orientation, roof accessibility and topography which are the main factors influencing the productivity of solar panels.