Maximum Solar Power Research Articles

Strain-Induced SiP–PtS2 Heterostructure with Fast Carrier Transport for Boosted Photocatalytic Hydrogen Conversion

Earth-abundant silicon-, phosphorus-, and sulfur-related compounds are crucial for optoelectronic application. Specifically, experimentally proven monolayer SiP has attracted a great deal of attention in above listed field owing to its unique properties but is plagued with challenges such as photocorrosion and poor charge separation. Moreover, theoretical understanding on the relationship of the interface and photocatalytic activity in SiP-based chemicals is not well understood. In this work, hybrid functional first-principles calculations were used to explore the photocatalytic hydrogen evolution activity of SiP–PtS2 heterostructure. Further examination of phonon, ab initio molecular dynamics (AIMD), and elastic property simulations confirms its dynamical stability. Its computed band gap of 1.59 eV is suitable for maximizing solar energy conversion efficiency, with noticeable strong absorption coefficients of 105 cm–1 order across visible–ultraviolet domains, asymmetric decent carrier mobility (∼103 cm2 V–1 s–1), and low exciton binding energy (0.56 eV). Differences in charge density and Bader and Mulliken population analyses reveal that charge flows from the SiP to the PtS2 layers, performing the dual functions of segregating photoinduced charge carriers and increasing their lifetimes. The relative band alignment of the monolayers promotes a spatial separation of the charges. An important feature of this heterostructure is that the band edges cross the water redox potential at pH of 0 upon −2% of compressive biaxial straining, with ΔG for hydrogen evolution reaction (HER) barrier lower than −0.2 eV. The quadratic relationship between biaxial strain and atomic energy indicates that both the system and strains are elastic. Redox thermodynamic analysis predicts facile hydrogen production on the heterostructure. In particular, the calculated maximum solar power conversion efficiency (PCE) and solar-to-hydrogen (STH) efficiency can reach 22.9 and 23.8%, respectively.

A Review of Time-Based Solar Photovoltaic Tracking Systems

Solar energy is the cleanest and most abundant form of energy that can be obtained from the Sun. Solar panels convert this energy to generate solar power, which can be used for various electrical purposes, particularly in rural areas. Maximum solar power can be generated only when the Sun is perpendicular to the panel, which can be achieved only for a few hours when using a fixed solar panel system, hence the development of an automatic solar tracking system. Over the years, different solar tracking systems have been proposed and developed, and a few have been reviewed in the literature. However, the existing review works have not adequately provided a comprehensive survey and taxonomies of these solar tracking systems to show the trends and possible further research direction. This paper aims to bridge these gaps by extensively reviewing these time-based solar tracking systems based on axis rotation and drive types. Lessons learned from the comprehensive review have been highlighted and discussed. Finally, critical open research issues are identified and elaborated.

Design, Construction, and Control Tracking of Solar Thermal Concentrator by Using PLC in Erbil

This paper demonstrates the construction designing analysis and control strategies for fully tracking concentrated solar thermal by using programmable logic control in the city of Erbil-Iraq. This work used the parabolic dish as a concentrated solar thermal. At the focal point, the collected form of energy is used for heating a (water) in the receiver, analyzing this prototype in real-time with two different shapes of the receiver and comparing the results. For tracking the parabolic dish, four light-dependent resistors are used to detect the sun's position in the sky so that the tracking system follows it to make the beam radiation perpendicular to the collector surface all of the time during the day for maximum solar power energy. This work discusses the essential stages of a two-axis prototype; implementation, solar-location strategy, the analysis in terms of theory, structural design, and material. For two-axis-prototype is implemented with the help of programmable logic control -Siemens (S7-1200) as a control unit. This study results show that a parabolic dish tracker with a cylindrical conical receiver obtains 15.25% Improved efficiency in comparison to the cylindrical receiver. According to the testing results of the prototype design, both shapes of the receiver are convenient for steam production.

Solar Maximum Power Point Tracking Algorithm Based on Wavelet Neural Network

With the development of human civilization, the shortage of resources and environmental pollution are increasing. Renewable energy is the only way to solve the problem of harmonious coexistence between human civilization and environment. More and more of them have come into our lives to reduce the burden of the earth and benefit mankind. Nowadays, due to the increasing gap of traditional power supply, solar energy has become a mainstream renewable energy, more and more applications, to provide us with green energy and improve our lives. The research on the application of solar energy system is of great academic value. This paper mainly studies the solar maximum power point tracking (MPPT) algorithm based on wavelet neural network (WNN). This paper analyzes several common maximum power tracking control methods, describes the structure design of WNN maximum power tracking control algorithm, and describes the structure and working principle of photovoltaic cells. In this paper, the output power of MPPT mode is analyzed and compared by simulating the use of solar photovoltaic system. In the meantime, the output voltage of solar charging panel in the charging process is studied. The experimental results show that the output power of the power supply in MPPT mode is kept at 0.2, and the output power of the solar panel is improved at every moment with the change of the external environment. At 9 o'clock, the output voltage of the solar panel is 3.6, and at 11 o'clock, the output voltage is 4.11.

Hybrid bat–grasshopper and bat–modified multiverse optimization for solar photovoltaics maximum power generation

A hybrid BAT with Grasshopper (GH) algorithm and BAT-MMVO (Modified Multiverse Optimization) are exhibited for harvesting maximum power from photovoltaics (PV) using the Xilinx System Generator (XSG) implanted controller. Using a hybrid BAT-GH and BAT-MMVO algorithm, the proposed implanted controller finds the best switching pulse for the boost converter. The implanted controller, switching schemes, and the Photovoltaic (PV) supported boost converter were built using the XSG domain. The hardware implementation of the best two cases were done using a microcontroller in a smaller scale. This aims to gather the maximum amount of power by a PV array for solar irradiation and cell temperature under varied environmental situations. The PV structure in the XSG domain is used to construct the system model for prediction. The major emphasis of this work is to keep the difference of actual power and reference power as minimum. Finally, the implanted controller's performance is compared to that of other existing hybrid controllers. The performance of the proposed algorithm is found to yield good results in terms of power extraction. The theoretical and experimental results are presented. The computational efforts for the implementation of the algorithm are found to be less complex when compared to other existing methods.

Solar Power Prediction using Regression Models

Solar power prediction is an important problem that has gained significant attention in recent years due to the increasing demand for renewable energy sources. In this paper, we present the results of using four different regression models for solar power prediction: linear regression, logistic regression, Lasso regression, and elastic regression. Our results show that all four models are able to accurately predict solar power, but Lasso regression and elastic regression outperform linear and logistic regression in terms of predicting the maximum solar power output. We also discuss the advantages and disadvantages of each model in the context of solar power prediction.

Solar photovoltaic Maximum Power Point Tracking controller optimization using Grey Wolf Optimizer: A performance comparison between bio-inspired and traditional algorithms

Solar photovoltaic systems are widely used; however, their performance is bound to weather conditions, depending on irradiation, temperature, and the effect of shadows. Maximum Power Point Tracking techniques have been developed to solve this issue. Standard methods use mainly-two algorithms: Perturb and Observe and Incremental Conductance. However, such algorithms perform differently when the Solar photovoltaic system works under sudden solar irradiation changes, temperature, and load changes. This research proposes an optimized Maximum Power Point Tracking controller based on the Grey Wolf Optimization algorithm using the MATLAB/Simulink software as an alternative to the traditional techniques. Global efficiency and Root Mean Square Error evaluate the controller's performance. The response time is analyzed using the Grey Wolf Optimizer algorithm, Wolf Optimizer Algorithm, Simulated Annealing, and Particle Swarm Optimization. These four metaheuristic algorithms are compared to the Perturb and Observe, and Incremental Conductance algorithms. The models are analyzed for the transient state and full-day operation scenarios for constant and variable irradiations, temperatures, and loads. The comparative results show that the Maximum Power Point Tracking controller optimized by the Grey Wolf Optimizer algorithm has superior performance, giving an average 6% output power higher than the other controllers under the test scenarios evaluated. The efficiency of the proposed model was, on average, 3% higher than the Incremental Conductance and Perturb & Observe controllers. For the MPPT controller tunning stage, the Grey Wolf Optimizer Algorithm had the best performance with an RMSE of 255.3549 with a compute time of 27.3 min; the worst performing was the Particle Swarm Optimization with an RMSE of 332.4075 and 27.8 min computation time. The proposed GWO optimized MPPT controller had the faster settling time for each irradiation level compared, with an average of 0.175 s. Also, results showed an improvement of the system response throughout the Maximum Power Point Tracking controller optimized by the Grey Wolf Optimizer algorithm since a lower curling effect is obtained at power converter outputs.

Fabrication of Color Glass by Pearlescent Pigments and Dissolved EVA Film.

In this paper, we propose a single-layer thin-film color glass manufacturing process for building-integrated photovoltaics (BIPV) with excellent aesthetics and high transmittance, through a solution process using pearlescent pigments. As a matrix for the color solution, ethylene vinyl acetate (EVA), which serves as an encapsulant and adhesive for the photovoltaic module (PV), was dissolved and used as a matrix for the color solution. The color glass produced is excellent in securing the aesthetics of buildings, has a high transmittance of 90% or more, outputs a maximum solar power generation efficiency of 91% from a solar cell, and can minimize the deterioration of power generation efficiency. In addition, the characteristics do not change over time, so it is suitable as color glass for BIPV. Through this study, the solution-based color glass manufacturing process for BIPV using dissolved EVA as a matrix forms a single-layer thin film with good color extensions. The choice of EVA as a matrix makes it possible for color glass to be easily attached to a solar panel using a heat press method. This proposed technique makes it easier and simpler to manufacture color glass as compared to the physical vapor deposition process. The adoption of this solution process technique to fabricate pearlescent pigment-based color glass can effectively reduce the time and cost of the process, so it is expected to be applied to the low-cost BIPV market with excellent aesthetics and high transmittance.

A study of a solar PV and wind-based residential DC NanoGrid with dual energy storage system under islanded/ interconnected/grid-tied modes

Progress in Direct Current (DC) power technologies has paved way for the emergence of DC Nano Grid (NG) as a new research area drawing international attention. This paper aims to design a simple and cohesive control algorithm for a solar PV and wind generator coupled low power residential DC NG with electrical and thermal energy storage systems. The envisaged NG control architecture extracts maximum power from solar PV, effects maximum active power transfer from wind generator with voltage regulation of the DC bus, draws/delivers balanced sinusoidal currents at Unity Power Factor (UPF) from/to the grid and monitors power scheduling to DC and thermal loads. The maximum solar PV power is extracted through incremental conductance algorithm and maximum wind power is tracked using a polynomial curve fit equation derived from the wind power curves without implementation of any speed/torque control loops. The maximum active power transfer from wind and UPF operation of the grid is achieved using a reference current generation method based on symmetrical components theory of equal current strategy with no complex transformations. A power factor of 0.99 with generation of balanced sinusoidal currents during both grid power import and export is achieved. Further, the operation of the proposed DC NG in all possible modes such as islanded/grid-tied/interconnected modes are monitored through a supervisory controller implemented in OPAL-4510 Real Time Digital Simulator (RTDS) under varying solar irradiation, wind velocity and load conditions, which projects the suitability of the system to be implemented in any geographical location (hilly terrain/rural/urban) either with limited availability of renewable sources or grid supply. The successful operation of the system is validated through experimentation on a 120 W scaled-down hardware prototype.

Perovskite Solar Cells and Thermoelectric Generator Hybrid Array Feeding a Synchronous Reluctance Motor for an Efficient Water Pumping System

Nowadays, water pumping systems based on photovoltaics as a source of electricity have widely increased. System cost and efficiency still require enhancement in order to spread their application. Perovskite solar cells (PSCs) are the most hopeful third-generation photovoltaic for replacing the silicon-based photovoltaic thanks to their high power conversion efficiency, reaching 25.8%; tunable band-gap; long diffusion length; low fabrication temperature; and low cost. In this work, for the first time, we proposed a high-power-density hybrid perovskite solar cell thermoelectric generator (TEG) array for feeding a synchronous reluctance motor (SynRM) driving a water pump for use in an irrigation system. A control technique was used to achieve two functions. The first function was driving the motor to obtain the maximum torque/ampere. The second was harvesting the maximum perovskite solar cell array output power on the basis of the maximum power point tracking (MPPT) algorithm using the perturbation and observation approach. Thus, the proposed hybrid perovskite solar cell–thermoelectric generator feeds the motor via an inverter without DC–DC converters or batteries. Accordingly, the short life problems and the high replacement cost are avoided. The proposed complete system was simulated via the MATLAB package. Moreover, a complete laboratory infrastructure was constructed for testing the proposed high-power-density hybrid perovskite solar cell–TEG array for the water pumping system. The results revealed that using the high-power-density hybrid perovskite solar cell–TEG array, both the motor’s output power and the pump’s flow rate were improved by 11% and 14%, respectively, compared to only using the perovskite solar cell array. Finally, both the simulation and experimental results proved the high-performance efficiency of the system in addition to showing its system complexity and cost reduction.

Wind-Driven DFIG–Battery–PV-Based System With Advance DSOSF-FLL Control

In this article, a wind-driven doubly fed induction generator (DFIG), battery, and photovoltaic (PV) array-based system with advanced discrete second-order sequence filter-frequency locked loop control for grid-side converter (GSC) is presented. The improved grid-side control provides the reactive power demand of load connected at the point of common coupling. The GSC control provides active and reactive power sharing and mitigates the power quality issues at unbalanced and nonlinear load conditions. Moreover, it gives a satisfactory performance during the dynamic wind speeds and load variation. The maximum wind power is extracted using the tip speed ratio algorithm. The necessary quantity of reactive power for DFIG is delivered by the rotor-side converter (RSC). The battery with a bidirectional converter is connected to the common dc link of the DFIG. The battery is used to maintain the dc-link voltage between RSC and GSC and it stores the power in light-load conditions. It provides the load demand during lower wind speed and solar irradiation. The maximum solar power is extracted by well-established incremental conductance (InC) algorithm, which provides optimum performance during the high dynamic variation of solar irradiation. Moreover, the InC algorithm increases the system's stability and reduces costs. It is easy to implement and handle nonlinearity. The feedforward PV component is added with the active load current component to improve the dynamic behavior of the system. Simulated and test results show the performance of the developed system in different dynamic conditions, such as load unbalancing, changes in PV insolation, and change in speed from the cut-in to cut-out speeds of the wind turbine. Moreover, obtained results show the battery behavior during different dynamic conditions.

Design and Analysis of P&O algorithm based MPPT solar system in PSIM

Conventional solar panels suffer with non-identical losses (resistive losses, diode leakage, loss of material properties etc.). To overcome these unwanted phenomena, a solar maximum power point tracking (MPPT) algorithm has been introduced. In this paper, the algorithms used for tracking the sun (or the solar maximum power point tracking algorithm) has been introduced & a brief description of the basic & easiest algorithm i.e., the P&O Algorithm using PSIM software has been provided to give a clear view about the concept & implementation of MPPT. Keywords: Photovoltaic, MPPT, P&O, PSIM

Over-Voltage Regulation of Distribution Networks by Coordinated Operation of PV Inverters and Demand Side Management Program

The increase of Photovoltaics (PV) units’ penetration factor in the power grids might create overvoltage over the network buses. The active power curtailment (APC) and the reactive power provision methods use inverters to regulate their output active and reactive powers for high PV-penetrated grids. However, the mentioned solutions would reduce the maximum injectable active solar power to the grid, not financially acceptable. Continuous employment of the maximum apparent power capacity of the inverters will practically decrease the inverters’ lifetime, require special design considerations, and make the control system complex. To overcome those issues, a feasible solution would be increasing the load consumption within the time intervals in which the grid faces the over-voltage problem. In this research, the demand response (DR) program is employed. Load shifting techniques are exerted to move a portion of loads from the peak hours to when further power consumption is expected for voltage level reduction purposes. A new long-term strategy based on the coordinated operation of the PV inverters and load shifting techniques is proposed to resolve the over-voltage issue in the network. Consequently, the PV inverter’s contribution to voltage control is reduced; a new sight of DR potential is implemented, and also the under-voltage level in peak times is decreased significantly.

Designing of Dual Power Generation Solar Plus Wind Energy Hybrid System using MPPT

Renewable energy is another energy efficiency solution within the modern day of life. The production of energy contributes significantly to the environment and thus human health to the environment. In India, wind and solar energy are available at no cost throughout the year.In India there is a power shortage and load restrictions. Due to power shortages and problems in many regions, to bridge the gap between electricity demand and supply, we must use a hybrid system.The paper aims to improve the power demand using Wind and Solar energy within the MATLAB software. The hybrid model has Solar panels Maximum power point tracking, power converter, turbine and PMSG generator.

Reduced oscillations based perturb and observe solar maximum power point tracking scheme to enhance efficacy and speed of a photovoltaic system

This paper puts forward a reduced oscillation based perturb and observe (ROP&O) maximum power point (MPP) tracking (MPPT) technique to mitigate the probability of loss of tracking direction and to reduce oscillations around MPP when the solar photovoltaic (PV) array is subjected under periodically changing irradiance. The proposed technique retains the structure of conventional perturb and observe (P&O) technique additionally incorporating a unique structure of dynamic step sizing, along with proportional-integral (PI) controller which potently alters the duty cycle (𝐷) of the DC-DC boost power converter (BPC). The ROP&O MPPT technique is compared with conventional P&O and incremental conductance (IC) schemes in terms of tracking efficacy (𝜂), ripples in PV voltage and PV current, convergence time, and the error rates. The efficacy of the proposed scheme lies between 99.06% to 99.80%. Moreover, the time to obtain MPP is 0.018 sec. which is about five times faster than the P&O technique and fifteen times faster than the IC technique. Also, the proposed MPPT technique is benchmarked using three-phase grid integration, and the power quality of the grid current is observed in terms of total harmonic distortion (THD).

Angle Dependence of Solar Power Capacity: The Case of Setit Humera

The solar power capacity depends on orientation angle of the solar panel. This study evaluates the angle dependence of solar power capacity for a summer season in 2017. Using three solar panels, with 10 Watt capacity each placed on a metallic frame to facilitate changing tilt and azimuth angles independently. Experiments were done for the first six days of three months, and the first three days of each month were used to measure voltages for different tilt angles by changing from 0° to 26° in steps of 2o. The remaining three days of a week of every month, the middle solar panel was fixed at a tilt angle that yielded maximum power while the two panels were moved with azimuth angles from 0o to 270 in steps of 3o to clockwise and counterclockwise with respect to the middle solar panel. A digital multimeter was used to record the circuit voltage of the solar panels with 10 ohms resistor serving as a load. Data gathering was done every ten minutes, during the daytime from 9:30 am to 16:30 pm. The study has shown that the maximum power output was obtained at the tilt angle of 4o in June and July, 2o in August and a season tilt was found at 4o. Maximum solar power outputs were obtained when solar panels facing east and west were oriented between 0o and 3o. This recommends that the maximum solar power production depends on the tilt angle of 4o and clockwise and counterclockwise of 3o orientation for this geographical location.

Modeling of solar batteries operating modes

For the solar power engineering development it is essential to determine the photovoltaic plant energy indicators by modeling the solar batteries operating modes. To obtain an adequate solar battery model, we need to determine its main parameters on the basis of an equivalent electric circuit. Modeling the solar battery operating mode, it is necessary to take into account the influence of its heating temperature. We propose a combined research algorithm in MS Excel with the installed add-on “Search for a solution” for modeling of solar battery operating mode. We have given the results of modeling the solar battery operating mode where the calculated solar battery maximum power including its heating, satisfactory matches with the experimental data. The research shows that excluding the solar battery heating, the maximum power value and, accordingly, its efficiency are overestimated in comparison with the experimental data. Moreover, the results of modeling excluding its heating do not provide the required accuracy and the modeling mistakes are more than 30% especially at relatively high values of solar radiation. The given model allows to determine the equivalent circuit parameters and determine the solar battery maximum power depending on the considered factors of its heating temperature and the incoming solar energy.

A Novel Multiport Converter Interface for Solar Panels of CubeSat

Maximization of solar energy harvest and miniaturization of dc–dc converters are essential for low earth orbit (LEO) CubeSats, which are constrained by volume and weight restrictions. The state-of-the-art electric power system (EPS) architectures utilize several individual dc–dc converters to maximize solar energy harvest but it has a tradeoff with miniaturization as it requires several inductors. The main objective of this article is to propose a single-inductor-based multiport converter topology for the LEO CubeSat's EPS. The proposed topology interfaces the photovoltaic (PV) panels to the energy storage system and a control strategy have been developed to extract maximum solar power from each PV panel under wide varying irradiation conditions of the LEO CubeSat. The proposed topology consists of series-connected half-bridge modules fed by PV panels and their output is supplied to the energy storage system via a boost converter. The principle of operation is introduced followed by steady-state analysis and converter dynamics analysis. The performance of the proposed converter is verified for several case studies with an experimental prototype developed based on 1U CubeSat specifications.

Improved generalised integrator for optimal dispatch of SyRG‐based pico‐hydro‐PV system

The fluctuating outputs from renewable energy sources (RESs) and variable load power demand deteriorate the current quality, thus an improved generalised integrator with a frequency-locked loop (IGI-FLL) control strategy is used, which is not only easy but simple to attain a quick and precise fundamental extraction. IGI-FLL control method is utilised with all-pass filter and is capable to accomplish enhanced harmonics, noise and DC offset rejection ability while estimating fundamental component of the load current. In addition, the FLL structure is used to increase the frequency immunity against voltage variations. It provides improved steady-state and dynamic performances with flexibility in parameter tuning in comparison to SOGI-FLL algorithm. It also presents a cost-effective and robust genetic algorithm (GA)-based optimisation to provide optimum battery charging and discharging power while satisfying the state-of-charge (SOC) limits under RES uncertainty. In this islanded microgrid, a Synchronous Reluctance Generator for pico-hydro and photovoltaic array is used so that this hybrid system utilises maximum solar PV array power, matches the load, or else charges the battery energy storage while maintaining power balance in the microgrid. Comparative outcomes authenticate the efficacy of the algorithm to handle the issue of RES uncertainty and load unbalance in an islanded microgrid.

Grid integrated solar energy transfer system with a two‐layer complex coefficient filter‐based control

In this paper, a novel control strategy for grid-integrated solar energy transfer system (SETS) is proposed which enhances the grid power quality along with active power injection. Some of the conventional grid synchronization controls face problems due to imperfect estimation of fundamental active load current during both grid-side and load-side disturbances. The proposed two-layer multiple-complex coefficient filter control improves the performance of SETS by accurately estimating the fundamental active load current at adverse operating conditions. One layer extracts the fundamental positive sequence of the sensed three-phase grid voltages and derives the unit in-phase voltage templates for grid currents reference generation to achieve unity power factor operation. The second layer evaluates the average active fundamental component of the load currents, and finally derives the reference amplitude of three-phase grid currents. The two-stage SETS consists of a quadratic boost DC-DC converter to extract the maximum solar array power forming an interface between PV array and inverter. It also provides high voltage gain and decreases the length of the PV array string while maintaining a low DC-link voltage ripple, extending the service life of the SETS. The effect of a nonlinear unbalanced load is nullified and therefore the grid current's waveform quality is maintained in compliance with the IEEE-519 standard during the dynamic operating conditions. The SETS provides sinusoidal, balanced, and steady grid currents at unity power factor withstanding adverse operating conditions such as distorted grid voltages, varying irradiance and varying unbalanced nonlinear load currents. Due to its flexibility to operate in such adverse conditions, the proposed control based SETS is suitable for grid-connected applications. Simulations are carried out in MATLAB/Simulink and results validate the performance of the SETS. The hardware prototype of the proposed SETS is developed and rigorously tested under various operating conditions to validate the proposed claims.