Solar Control Research Articles

Review of thin film deposition and techniques

The main aim of this paper is to review different thin film deposition techniques and their significance in photovoltaic applications. Chemical methods for preparing thin films are currently attracting due to their relative affordability, simplicity, and suitability for large-area deposition. Since these are low temperature techniques, they prevent substrate oxidation and corrosion and can be employed with a range of substrates, including insulators, semiconductors, and metals. These are gradual processes that enable crystallites to have improved grain structure and better orientation. All deposition techniques entail building a layer on an existing substrate with a thickness that can range from tens of Å to a millimetre depending on various working circumstances. Film growth may occur through ion-by-ion condensation of the materials on the substrates, depending on the deposition circumstances. Thin film deposition can be influenced by various parameters such as PH, temperature, deposition time etc are also described in the present article. Solar selective coatings, solar control, photoconductors, solid state and photoelectrochemical solar cells, optical imaging, hologram recording, optical mass memories etc. are some of the applications of metal chalcogenide films.

Renewable Energy Heat Source Desing and Modelling

Rising fossil fuel prices and growing environmental awareness are leading to a search for alternative energy sources for heating. This paper deals with the design of a heat source based on the use of renewable energy sources. The aim is to propose an efficient, sustainable, and environmentally sustainable solution that minimizes the negative impact on the environment and contributes to the reduction of greenhouse gas emissions. In the introductory part of this paper, the status and importance of using renewable energy sources for heat generation compared to traditional fossil fuels is assessed. The next section focuses on the detailed design and modelling of such a system, analysing various parameters and factors such as available solar energy, control and regulation system, energy conversion efficiency, heat storage and distribution of the heating system.

Design and Development of a Solar- Powered UAV Using IoT and Machine Learning

The proposed solar-powered UAV utilizes photovoltaic panels to convert solar energy into electrical power to supply the onboard electronic systems, including the propulsion system and sensors. To enhance the UAV's performance, loT technology is employed to enable the communication and coordination of the UAV with other connected devices, such as ground stations and sensors. This allows for real-time data collection and analysis, as well as improved situational awareness for the UAV. To optimize the performance of the UAV, SVM is used as a machine learning algorithm for object detection and classification. SVM has been widely used in UAVs to detect and classify objects in aerial images, and has been proven to be effective in a variety of applications. The proposed design utilizes SVM to detect and classify objects of interest, such as crops, buildings, and infrastructure, and to assist in the navigation and control of the UAV. The design and development of the proposed solar-powered UAV involves several key components, including the solar panels, propulsion system, control system, and communication system.

A novel low-cost solution for mitigating the loss of power supply probability in grid-tied Solar PV systems during daytime grid-outage scenario

In this paper, a novel method has been proposed and implemented to mitigate the loss of power from grid-connected solar PV systems during the grid outage condition. This loss during daytime grid outages usually occurs because of the built-in islanding feature of the commercially available grid-tied inverters. Unlike other existing grid outage mitigation methods such as; using the expensive hybrid inverters and other battery backup inverters, the proposed method introduces a battery-less topology which can avoid the significant cost of battery pack itself and associated auxiliary control circuits, its operation and maintenance. An optimized low capacity (around 5% of grid-tied inverter rating) DC-AC interface system in the form of a stand-alone inverter has been introduced to provide the reference AC bus for keeping the grid-tied solar inverter operational even during the daytime grid outage. The interface system is energized from a solar PV-powered DC bus instead of the commonly used high-capacity battery backup. The method also ensures the maximum available energy extraction from a grid-connected solar PV Plant without renovating the existing grid-tied solar inverters. The experimental validation has been done by a practical 2kW p grid-tied inverter and a 200VA stand-alone inverter interfaced solar PV system operation and control under sunny and cloudy day scenario. The proposed low-cost grid outage mitigation method is a generalized one and hence can be very useful for scalable grid-connected solar PV power plants also.

An Innovative Converterless Solar PV Control Strategy for a Grid Connected Hybrid PV/Wind/Fuel-Cell System Coupled With Battery Energy Storage

The proposed work addresses the modeling, control, energy management and operation of hybrid grid connected system with wind-PV-Battery Energy Storage System (BESS) integrated with Fuel Cell (FC) and Electrolyzer. A hybrid PV-Wind-FC with electrolyzer consisting of BESS with the least number of control loops and converters has been proposed. The proposed hybrid system presents a cost efficient solution for integrating PV into a hybrid system by eliminating the PV converter. This includes the design of controllers for grid-connected hybrid systems with a renewable distributed generator (Wind and PV) as a primary source, BESS as a secondary source and FC with Electrolyzer as a tertiary source. In addition, the lead compensator along with integrator is used for obtaining enough phase margin and removing steady state error completely. It increases the stability of the controller and adds phase shift φ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>s</i></sub> at a cross gain frequency (ω <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>cut</i></sub> ). The Grid Side Controller (GSC) is capable of providing frequency support to the utility grid, when it is linked to the grid. In the proposed configuration, PV power is maximized and injected into grid through GSC. Rotor Side Converter (RSC) and GSC ensure the support for sharing the burden of the grid station. Moreover, the proposed controller of BESS with coordination of FC eliminates the effect of intermittency of power generated from wind and PV. Excess power production by renewable distribution generation is used by Electrolyzer to generate hydrogen. This hydrogen is further used by FC when there is not enough power generation due to unfavorable weather conditions. The energy management has been presented to fulfill the load profile, avoid BESS overcharging and to minimize the intermittency and fluctuation of Wind and PV sources. This method guarantees steady power flow and service continuity. The Simulink model of the proposed system results validate the efficiency of the proposed hybrid system as compared to the conventional hybrid system reported in the literature. The modeling of the proposed system and analysis has been demonstrated using the MATLAB Simulink model. Lastly, the energy management of the system has also been examined and compared with the conventional power system.

Modeling and simulation of the kinematic behavior of the deployment mechanism of solar array for a 1‐U CubeSat

AbstractKinematics of deployable solar array mechanisms in CubeSat satellites have considerable influence on the stability and attitude control of a satellite, especially in low mass systems as CubeSats. One of the issues with the conventional solar panel deployment mechanisms in CubeSats is the speed of its deployment, especially when position‐lock to hold the panels back from oscillation is lacking. The generated oscillation becomes more pronounced in a system equipped with solar tracking unit and thus, reduces available projected area of the panels and causing fatigue at the yoke and panel hinges. This work aims at modeling and simulation of the 1‐U CubeSat solar panel deployment mechanism vibration control using fisher wire. Two‐fold panel deployment mechanism with a rolling sun‐tracking tilt mechanism was developed. The system performance from viewpoint of vibration analysis was evaluated using mass‐spring‐damper method and bond graph techniques. Numerical simulations and experiments were performed to validate the proposed method. The modeling and computational analysis were done with SOLIDWORKS software. The system was tested for vibration and stability using the seismic mass‐spring‐and‐damper arrangement to validate the model. A 3‐D printing was generated and tested to evaluate its vibration performance and its effects during deployment. The result was such that the two panels attached to a wing hinged at Y – and – Y directions deployed slowly and smoothly at approximately 2 s, giving room for the vibration to decay exponentially towards zero. This agrees with reported works where a DC motor was used to control speed of deployment by increasing time to 6.8 s. The simulated and experimental results of the printed model showed close agreement with the theoretical values with an error of 0.03% in energy supply reliability and up to 400% power generation potential when compared to body mounted solar panels with the same satellite specification without a significant impact on system strength and stability.

Design of solar cell using mirror, cooling, double axis, and solar tracking

Fossil energy sources are dwindling. It is necessary to develop alternative energy sources for future energy. The solar cell is an alternative energy that can be used in Indonesia. The current challenge is utilizing solar panels for the best possible power production. This research gives the solution to design an increase in solar cell output power by using mirrors, cooling, and a double-axis solar tracking control system. The results show that using a mirror, cooling, and double-axis solar tracking produces optimal output power with a current and power are 2.43 amperes and 40.3 watts, respectively. Meanwhile, several factors can affect this solar panel's efficiency. Specifically, the amount of solar radiation that the solar panel can receive depends on the climate on the day and location of the research and the solar panel's dimensions.

A comparative study between deterministic and two meta-heuristic algorithms for solar PV MPPT control under partial shading conditions

• Under partial shading conditions, adequate tuning of firefly and particle swarm optimization maximum power point tracking algorithms converge to the global maximum power point irrespectively of the starting voltage value. • Under partial shading conditions, there is no guarantee that perturb and observe algorithm will converge to the global maximum power point even for different starting voltage values. • The sensitivities of the parameters of firefly algorithm in improving the performance of the algorithm are investigated to find the best possible control parameters. • Firefly algorithm based maximum power point tracking performed slightly well than particle swarm optimization based maximum power point tracking for most irradiance patterns investigated in this paper. During partial shading conditions (PSC), the PV modules in a solar PV array become reverse biased and act as a load, resulting in hotspot issues. This can significantly decrease the efficiency of the solar PV. The general way to deal with PSC is to connect bypass diodes across the non-shaded PV module. However, this will alter the uniform characteristics of the PV array, resulting in multiple power peaks i.e., a multi modal landscape. The conventional gradient-based Perturb and Observe (PnO) algorithm generally used for maximum power point tracking (MPPT) in solar PV is ineffective in finding the maximum power during PSC because it is prone to converge to local optimum due to its nature of searching in a multimodal landscape. However, in this article an attempt is made to show how the PnO behaves in a multimodal landscape considering different starting points. Robust stochastic algorithms that are based on a population of search agents are used to guarantee convergence to the global MPP. In this paper, the maximum power point under PSC was tracked using two meta-heuristic algorithms namely, particle swarm optimization (PSO) and the firefly algorithm (FA). The performances of these algorithms in tracking the maximum power point are evaluated. The efficiency, standard deviation (STD), and root mean square error (RMSE) of the PSO and FA algorithms are compared to those of the PnO algorithm. The PSO was found to have the lowest RMSE, and the FA had the lowest STD. The efficiency of the PSO and FA were relatively the same. Simulation results show that PSO and FA-based MPPT algorithms can efficiently track the global maximum power point (GMPP) irrespectively of the starting points. On the other hand, PnO is shown to be unreliable under PSC even with different starting points.

Avaliação de conforto término em estações de trabalho localizadas próximo a fachadas envidraçadas: modelos de ajuste solar

Abstract Although solar radiation exposure strongly impacts people's thermal comfort, workstations are frequently positioned close to glazed façades. Solar adjustment models have been developed to include the solar radiation impact on people's thermal comfort, which the Fanger and Adaptative models do not address. Nonetheless, those models present differences in their calculation procedures, which have not been thoroughly investigated. This study aims to verify differences in thermal comfort results by applying various solar adjustment models of thermal comfort indices for a person sitting close to a highly glazed façade in an office room. The analyses were based on indoor environment data from computer thermal simulations in EnergyPlus for a temperate climate in Brazil. The results for the same room demonstrated significant differences. For example, the hourly difference between the solar-adjustment models reached 1.7 in PMV, and the MRT was up to 17.6 ºC higher than the mean result calculated through EnergyPlus. The need for solar radiation incidence control is also reinforced. Although the results were not compared with measurement data or people's thermal perception, the limitations and advantages of each solar adjustment model were numerically analysed, broadening the discussions about the solar adjustment models and the consequences of the choices among them.

Improving the Efficiency of Environmental Temperature Control in Homes and Buildings

This research developed an effective environmental temperature control system for homes and buildings. The study used a photovoltaic panel (PV) and developed a solar installation with thermosiphon circulation, which has a flat solar collector and heat-insulating translucent glass with double glazing with reduced pressure. The coolant is made of thin-walled corrugated stainless pipe. The heat from the solar flux heats the liquid removed from the collector, and cold water from the siphon enters its place. There is a constant circulation of heat, which increases heat transfer efficiency by eliminating additional partitions between the panel and thermal insulation. We have also developed a solar system control controller, which includes an electronic unit with six sensors. The six sensors are controlled by the STM32 programmable Logistics Integrated circuit (FPGA), designed to monitor the entire solar system, and the drives include power relays. The performance of the photovoltaic panel and the room’s temperature change are calculated during both the simulation and testing of the controller. The standard error was 20% compared to other controllers. During the experiment, the consumption savings amounted to about 1% due to the control signal in the controller, which has a significant impact on the service life of the equipment.

A Review on Machine Learning Applications for Solar Plants

A solar plant system has complex nonlinear dynamics with uncertainties due to variations in system parameters and insolation. Thereby, it is difficult to approximate these complex dynamics with conventional algorithms whereas Machine Learning (ML) methods yield the essential performance required. ML models are key units in recent sensor systems for solar plant design, forecasting, maintenance, and control to provide the best safety, reliability, robustness, and performance as compared to classical methods which are usually employed in the hardware and software of solar plants. Considering this, the goal of our paper is to explore and analyze ML technologies and their advantages and shortcomings as compared to classical methods for the design, forecasting, maintenance, and control of solar plants. In contrast with other review articles, our research briefly summarizes our intelligent, self-adaptive models for sizing, forecasting, maintenance, and control of a solar plant; sets benchmarks for performance comparison of the reviewed ML models for a solar plant's system; proposes a simple but effective integration scheme of an ML sensor solar plant system's implementation and outlines its future digital transformation into a smart solar plant based on the integrated cutting-edge technologies; and estimates the impact of ML technologies based on the proposed scheme on a solar plant value chain.

Design of Solar Panel Tracking Control System

This paper analyzes the overall scheme design, circuit design and PLC control program design of the system, and expounds the application research of realizing the conversion of solar energy to electric energy based on PLC control technology. With the development of economy and the progress of society, people put forward higher and higher requirements for energy. Finding sustainable development and green energy is one of the major issues facing mankind in this century and beyond. Developing new energy sources and making full use of existing energy sources have received great attention from scientists all over the world. As an inexhaustible and clean energy, solar power generation will get unprecedented development. With the development and industrialization of solar energy technology, its cost performance and efficiency will be greatly improved. Therefore, this design has high feasibility, practicality and energy conservation and environmental protection value.

Fault detection and monitoring of solar photovoltaic panels using internet of things technology with fuzzy logic controller

Purpose. This article proposes a new control monitoring grid connected hybrid system. The proposed system, automatic detection or monitoring of fault occurrence in the photovoltaic application is extremely mandatory in the recent days since the system gets severely damaged by the occurrence of different faults, which in turn results in performance degradation and malfunctioning of the system. The novelty of the proposed work consists in presenting solar power monitoring and power control based Internet of things algorithm. In consideration to this viewpoint, the present study proposes the Internet of Things (IoT) based automatic fault detection approach, which is highly beneficial in preventing the system damage since it is capable enough to identify the emergence of fault on time without any complexities to generate Dc voltage and maintain the constant voltage for grid connected hybrid system. Methods. The proposed DC-DC Boost converter is employed in this system to maximize the photovoltaic output in an efficient manner whereas the Perturb and Observe algorithm is implemented to accomplish the process of maximum power point tracking irrespective of the changes in the climatic conditions and then the Arduino microcontroller is employed to analyse the faults in the system through different sensors. Eventually, the IoT based monitoring using fuzzy nonlinear autoregressive exogenous approach is implemented for classifying the faults in an efficient manner to provide accurate solution of fault occurrence for preventing the system from failure or damage. Results. The results obtained clearly show that the power quality issue, the proposed system to overcome through monitoring of fault solar panel and improving of power quality. The obtained output from the hybrid system is fed to the grid through a 3ϕ voltage source inverter is more reliable and maintained power quality. The power obtained from the entire hybrid setup is measured by the sensor present in the IoT based module. The experimental validation is carried out in ATmega328P based Arduino UNO for validating the present system in an efficient manner. Originality. The automatic Fault detection and monitoring of solar photovoltaic system and compensation of grid stability in distribution network based IoT approach is utilized along with sensor controller. Practical value. The work concerns a network comprising of electronic embedded devices, physical objects, network connections, and sensors enabling the sensing, analysis, and exchange of data. It tracks and manages network statistics for safe and efficient power delivery. The study is validated by the simulation results based on real interfacing and real time implementation.

Changing the climate risk trajectory for coral reefs

Coral reefs are extremely vulnerable to climate change and their recent degradation will continue unless we can instigate strong global climate action with effective regional interventions. Many types of intervention have been proposed and some aspects of their deployment are now being tested. However, their long-term efficacy under climate change can only be evaluated using complex biophysical models applied over a range of plausible socio-economic pathways. The associated uncertainties in climate trajectories, ecological responses, and the mitigating effects of interventions, necessitate the use of a risk-based approach to evaluating model results. I show that ensemble modeling can be used to develop rigorous risk assessments suitable for comparing intervention strategies. A major strength of this approach is that all the key elements required for risk assessment (exposure, sensitivity, adaptive capacity, and impacts) can be generated by the model in a dynamically consistent form. This is a major advance on semi-quantitative climate change vulnerability risk assessments that estimate these quantities independently and then combine them under additional assumptions. Applying ensemble modeling risk assessment to the Great Barrier Reef (GBR) suggests that regional intervention strategies, such as solar radiation management (SRM) and control of coral predators, can slow the increase in risk and potentially avoid extreme risks predicted for the second half of the century. Model results further suggest that deployments focused within the northern and central GBR will be most effective due to underlying patterns of reef connectivity.

Solar energy application and its effect on microorganisms in food waste anaerobic fermentation regulated by organic load

Semi-continuous anaerobic digestion (AD) of food waste (FW) was conducted by solar intelligent control system to explore the impact of temperature fluctuation on microorganisms and its engineering applicability. According to analysis of the AD system at different organic loading rate (OLR), introduction of the solar intelligent control system into AD could save electric energy. Temperature fluctuation caused by climate and other factors reduced methane production by 31.79%. Before reaching the optimum OLR, the methane yield increased with the promotion of OLR and was at the optimum when OLR = 4.5 kg ⋅ m−3 ⋅ d−1. Enzyme activities changed with the change of pH. Lower pH limited the enzyme activities. At the initial stage of the reaction, Clostridium and Lactobacillus dominated, which made content of amylase and lipase reach 264.07 U/mL (solar group), 331.02 U/mL (electric group), and 276.44 U/mL (solar group), 306.75 U/mL (electric group), respectively. Temperature fluctuation brought in by the solar intelligent control system had a great effect on microbial activity. Microbial community structure was influenced by the OLR change. Methanobacterium became the main methanogenic bacterium at the middle and late stage. After analysis, it is feasible to introduce solar energy into AD.

Challenges in lighting education: a recommended practice

Although lighting is a theme usually loved by architects, there are few studies about appropriate pedagogical strategies focusing on its teaching in architectural undergraduate courses. This subject rarely is present in conferences, symposia, and similar events regarding architectural education. Due to historical mistakes, lighting education is often conducted in such courses with no link to the architectural design process. Regarding daylighting, it not always goes beyond solar geometry and insolation control, and electrical lighting is addressed to the discipline of electrical installations, strictly based on a calculation approach. It urges to present lighting to students as an integral and indissociable part of the architectural space itself. Also, it is essential to support a process of learning based on observation and laboratory experimentation. This paper discusses these issues and presents a pedagogical proposal favouring drawing with light, both daylighting and electrical lighting, since the first steps of the architectural design process. An electronic tool yet under development and destined to help in decision-making related to daylighting in the initial phases of design development is also presented. For a sustainable and safe future in a world in rapid transformations due to technological advances and pandemic events, lighting education deserves to be exhaustively studied by educators and architecture schools worldwide. Sharing knowledge in a network seems to be the best way for such an objective.

Solar PV Inverter Reactive Power Disaggregation and Control Setting Estimation

The wide variety of inverter control settings for solar photovoltaics (PV) causes the accurate knowledge of these settings to be difficult to obtain in practice. This paper addresses the problem of determining inverter reactive power control settings from net load advanced metering infrastructure (AMI) data. The estimation is first cast as fitting parameterized control curves. We argue for an intuitive and practical approach to preprocess the AMI data, which exposes the setting to be extracted. We then develop a more general approach with a data-driven reactive power disaggregation algorithm, reframing the problem as a maximum likelihood estimation for the native load reactive power. These methods form the first approach for reconstructing reactive power control settings of solar PV inverters from net load data. The constrained curve fitting algorithm is tested on 701 loads with behind-the-meter (BTM) PV systems with identical control settings. The settings are accurately reconstructed with mean absolute percentage errors between 0.425% and 2.870%. The disaggregation-based approach is then tested on 451 loads with variable BTM PV control settings. Different configurations of this algorithm reconstruct the PV inverter reactive power timeseries with root mean squared errors between 0.173 and 0.198 kVAR.

Thermal Structure of the Martian Upper Mesosphere/Lower Thermosphere From MAVEN/IUVS Stellar Occultations

AbstractWe report the first detailed study of the diurnal thermal structure of upper mesosphere/lower thermosphere (∼80 to 160 km) of Mars from stellar occultation observations by the Imaging Ultraviolet Spectrograph (IUVS) aboard the NASA Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft. Due to stray light contamination, analyses of this data set to date have been confined to the nighttime events. This study makes use of a revised algorithm for removal of stray light from occultation spectra to retrieve the dayside events as well. The dayside is observed to be warmer than the nightside, with the maximum day/night difference of ∼30 K in the lower thermosphere, ∼20 K around the mesopause, with little diurnal variations at lower altitudes. This is consistent with the radiative time constant which is of the order of 1 Mars day in the to Pa region. The data also shows that the regions at pressure less than Pa are under strong solar control with no prominent migrating tidal signatures. In contrast, on Earth, the radiative time constant near the mesopause is ∼10 Earth days and the temperature variations due to tides are quite large. The Mars Climate Database shows a diurnal trend opposite to the data in the mesosphere, with the dayside mesopause predicted to be cooler than the nightside by ∼10 K along with signatures of a vertically propagating tide. The IUVS data set provides an unprecedented constraint on the structure of the Martian mesosphere.

Comparison of Growth Characteristics of Strawberry according to Integrated Solar Radiation Control by Growth Stages

Comparison of Growth Characteristics of Strawberry according to Integrated Solar Radiation Control by Growth Stages

Rancang Bangun Sistem Irigasi Otomatis Berbasis RTC Menggunakan Solar Panel

Sinarancang Village, Mundu District, Cirebon Regency is one of the best agricultural producing villages in Mundu District. Agriculture will become more productive as a result of developments and new technologies such as sensors, devices, and information technology that can group data into big data. Watering with the manual method is less effective because it requires time,effort, and operators who cannot leave the land for a long time. Therefore, an Automatic Irrigation System based on solar panels was created and implemented. This system uses Real Time lock (RTC) as a time calculator. The type of RTC used is the RTC DS 1307 which is compatible with Arduino. Solar Panels are used as a substitute for PLN's power supply. System components consist of solar panels, control boxes, pumps, and nozzle taps. The system has been tested and the voltage to activate the pump is about 12volts. The time interval for circulating air in the nozzle faucet when the pump is active is about 6-10 seconds. The system is implemented on dry land by utilizing air sources from higher ground so that it is effective for the watering system