Modeling Of PV System Research Articles

Techno-enviro-economic analysis of grid-connected solar powered floating PV water pumping system for farmland applications: A numerical design model

To meet the required load of a farm in the rural area in Mafraq, Jordan, the complete floating photovoltaic (FPV) water pumping sizing, modelling, and optimization of an on-grid PV system with comprehensive capacity, energy output cost, and emission estimations are outlined in this work. The novelty of this study lies in its comprehensive approach that integrates technical, environmental, and economic factors into a unified framework for designing a PV water pumping system, particularly in scenarios where grid supply is feasible or economically viable. A proposal has been made to install PV panels over the water lake to improve the overall system efficiency and to give an aesthetic appearance. The proposed system is composed of a 165 kW PV array and three 55 kW inverters, which cost 54696.92 JD as the initial cost, CO2 emission reduction of more than 5000 tons and produce electricity at 0.028 JD/kWh. The results indicated that the FPV option demonstrates an about 5 % increase in efficiency compared to the other two scenarios. Also, the FPV option has higher costs due to a 25 % increase in system cost but results in lower CO2 emissions compared to the other two options. Top of Form As shown from the results, the two sizing methods for solar water pumping systems, the equations-based method, and the PVsyst simulation tool give the same results. By following this methodology, one can assess the load, size the system, simulate its operation, and analyse the expected performance. Furthermore, the findings of this study could be valuable in designing a grid-connected FPV water pumping system.

Optimal planning and modelling of the solar roof-top PV system with different incentive policy schemes for residential prosumers: a real-time case study

Optimal planning and modelling of the solar roof-top PV system with different incentive policy schemes for residential prosumers: a real-time case study

Unsupervised fault detection approach based on depth auto-encoder for photovoltaic power generation system

Fault detection for photovoltaic power generation system is a challenging problem in condition monitoring and troubleshooting, which aims to maintain the safe operation of equipment and improve the benefit of photovoltaic industry. Aiming at the problems of frequent failures of photovoltaic power generation system, large amount of operating data and difficult to obtain fault samples, we propose an unsupervised fault detection approach for photovoltaic power generation system via bidirectional long/short memory deep auto-encoder which combines the auto-encoder in deep learning with the Bi-directional Long Short-Term Memory (BiLSTM). Specifically, We first take the statistical feature enhanced as the input of an auto-encoder based on BiLSTM. Then, we build a simulation model of Grid-connected PV system. Finally, we use the operation results under normal conditions to train the fault detection model to obtain the reconstruction error and determine the fault detection threshold, so as to judge the anomalies of the photovoltaic power generation system. We simulate the shadow occlusion fault and verify the effectiveness of the proposed method, and the fault detection accuracy of 0.95 is achieved. Compare with other models, the results show that it could set up better dependence on multi-dimensional data in time sequences, effectively testing solar panel failures and solving insufficient data labels problems.

Parameters extraction of photovoltaic models using enhanced generalized normal distribution optimization with neighborhood search

The photovoltaic system has been widely integrated into electrical power grids to produce clean and sustainable energy sources. Precisely modeling of PV systems is crucial to simulate and asset the performance of such power system. Modeling of PV system is a challenge because the characteristic curve of current and voltage is nonlinear and has unknown parameters due to insufficient data points in manufacture’s data sheet. This work proposes generalized normal distribution optimization based on neighborhood search strategies (NSGNDO) to extract the parameter of single diode model (SDM), double diode model (DDM), and PV module model (PVM). The root means square error (RMSE) is used as a performance indicator. Two commercial PV models like RTC France solar cell and PWP201 are used to validate the ability of NSGNDO to precisely estimated the PV system’s parameters. The results show the superiority of NSGNDO over competitive optimization methods and can reduce the RMSE to 2.05296E-03 for PWP201 and to 9.8248E-04 for RTC France solar cell which prove that NSGNDO can be used as competitor method to identify the parameters of PV solar system. The statistical analysis shows the robustness of NSGNDO through statistical measurements and Wilcoxon rank test.’

Modeling and Simulation of Grid-Tied Three-Phase PV System in Lahore, Pakistan

This research examines the implementation of grid-tied solar inverters in Lahore’s energy infrastructure, considering the city’s growing energy demands. Utilizing MATLAB/Simulink for modeling solar photovoltaic systems in Lahore’s arid climate, our study focuses on a house in Askari X housing society, Lahore, Pakistan, with a 5.1 kW load. The results demonstrate the expected system variation of a Grid-Tied PV System during grid disruptions, and the model’s consistent performance across varying irradiance conditions suggests potential economic advantages through net metering. These findings offer practical insights into the economic feasibility and dependability of grid-tied solar inverters in Lahore, highlighting their potential to contribute to the city’s energy needs.

Assessment of the synthetic inertial response of an actual solar PV power plant

As the large-scale integration of renewable energy grows, inertia in power systems is reduced, which causes the rate of change of frequency to increase and worsens the frequency nadir during disturbances. There is, therefore, an urgent need to accelerate the development of international standards and regulations that require solar PV systems and other renewable installations to also contribute to stability in the network by emulating inertia. Spain is a pioneer in this field: it is currently the only country that includes the synthetic inertia technical requirement in its grid code. In this context, the present paper analyzes the synthetic inertial response of a PV system model that forms part of an actual PV power plant in Spain under two scenarios, according to its grid code: i) when measurements are conducted at the power conversion PV system level and hence only its control algorithms are executed; and ii) when measurements are conducted at the power plant level and the power plant controller also influences the response of the entire installation. Among its aims, this paper seeks to thoroughly assess the response of an actual PV power conversion system that has the capability of actively contributing to frequency regulation in a network and to critically analyze the suitability of having a power plant controller when the PV facility contributes to power-frequency control by means of an inertial response. The results reveal, at the power conversion PV system level, that the inertia emulation module significantly reduces the response times of the installation to changes in frequency -by more than 68% in the worst case under frequency increases, and by 73% under frequency decreases, thus contributing to more rapid power-frequency regulation in the network. However, at the power plant level, the power plant controller disturbs the PV power conversion system’s behavior and causes the opposite effect: response times increase -up to more than 7% in the most unfavorable case when the inertia module is enabled.

Mathematical Modeling and Simulation of Photovoltaic Array

This work deals with modeling and simulation of PV system which can be connected to the distribution power network. It means photovoltaic array. I try to draw up a specification of PV array problems because these sources have certain specific features, that are given by their characters. I give a attention to the characteristics of PV cells that influence the reliability and quality of the power supply. I also deal with these behaviour of PV array in the distribution grid, their possible influence on a voltage regulation, influence of their power variation on voltage waveform at the point of connection and also an examination of different variants of PV array connection.

Dwarf Mongoose Optimizer for Optimal Modeling of Solar PV Systems and Parameter Extraction

This article presents a modified intelligent metaheuristic form of the Dwarf Mongoose Optimizer (MDMO) for optimal modeling and parameter extraction of solar photovoltaic (SPV) systems. The foraging manner of the dwarf mongoose animals (DMAs) motivated the DMO’s primary design. It makes use of distinct DMA societal groups, including the alpha category, scouts, and babysitters. The alpha female initiates foraging and chooses the foraging path, bedding places, and distance travelled for the group. The newly presented MDMO has an extra alpha-directed knowledge-gaining strategy to increase searching expertise, and its modifying approach has been led to some extent by the amended alpha. For two diverse SPV modules, Kyocera KC200GT and R.T.C. France SPV modules, the proposed MDMO is used as opposed to the DMO to efficiently estimate SPV characteristics. By employing the MDMO technique, the simulation results improve the electrical characteristics of SPV systems. The minimization of the root mean square error value (RMSE) has been used to compare the efficiency of the proposed algorithm and other reported methods. Based on that, the proposed MDMO outperforms the standard DMO. In terms of average efficiency, the MDMO outperforms the standard DMO approach for the KC200GT module by 91.7%, 84.63%, and 75.7% for the single-, double-, and triple-diode versions, respectively. The employed MDMO technique for the R.T.C France SPV system has success rates of 100%, 96.67%, and 66.67%, while the DMO’s success rates are 6.67%, 10%, and 0% for the single-, double-, and triple-diode models, respectively.

Integration of Stability Model of PV System by Using WEEC Model and Generic Type 4 PV Model in PSSE Software

Integration of Stability Model of PV System by Using WEEC Model and Generic Type 4 PV Model in PSSE Software

Power distribution technique and small-signal modeling of grid-integrated solar PV system with hybrid energy storage systems

A model of a grid-integrated AC/DC microgrid with the assimilation of renewable energy resources and supercapacitors with battery storage-based hybrid energy storage is considered in this paper. The insertion of renewable resources and energy storage devices in the existing power grid requires rigorous analysis of the power balance and system stability. The microgrid is designed to absorb/deliver the defined power from/to the utility grid in a bidirectional manner. To simplify the power control strategy, the total power requirement in the system is divided into slow and fast varying components. So, the grid and battery will share the slowly varying components and the supercapacitor will suppress the fast varying components. This control strategy ensures improved performance by retaining the unity power factor operation of the grid, faster DC link voltage recovery, and harmonic mitigation. Again, a double-loop control structure based on small-signal modeling of the system is presented for stability analysis of the proposed system. MATLAB/Simulink results along with real-time simulation results are provided in this paper for verification of the proposed control technique.

Advanced Rapid Predictive and Modulation Model for PV System

In the real-time case of the power management system, renewable energy improves power generation to reduce demand. Since this type of renewable energy system is not sufficient to generate power to the load with controlled energy in grid systems and other related high-power applications. The existing models refer to the static parameters to control the regulation factor of the DC converter. This leads to a delay in step response and the other related features which will affect the output power with noise and surge peaks. In this work, a novel model of the optimal controlling model was proposed to improve the switching activities of the converter circuit. In this, the DC–DC converter design needs to enhance for reducing the noise at converted DC output. The controller tunes gain the parameters according to the feedback signal dynamically to reduce the step response time. For this process, a rapid model predictive and modulation-based controller with maximum power point tracking analyzer are used to estimate operating point of the PV system and control the switching devices accordingly. This improves the high-frequency switching activities to reduce the noise level in DC output. This can also reduce the noise at DC output. The inverter was connected at the output terminal of DC–DC converter for the AC load components. The space vector pulse width modulation technique was used for driving the inverter switches to reduce the total harmonic distortion from the output waveform to the load terminal. The simulation result and the experimental result show the performance of the proposed controller comparing with traditional controlling models.

Biogeography-Based Teaching Learning-Based Optimization Algorithm for Identifying One-Diode, Two-Diode and Three-Diode Models of Photovoltaic Cell and Module

This article handles the challenging problem of identifying the unknown parameters of solar cell three models on one hand and of photovoltaic module three models on the other hand. This challenge serves as the basis for fault detection, control, and modelling of PV systems. An accurate model of PV is essential for the simulation research of PV systems, where it has a significant role in the dynamic study of these systems. The mathematical models of the PV cell and module have nonlinear I-V and P-V characteristics with many undefined parameters. In this paper, this identification problem is solved as an optimization problem based on metaheuristic optimization algorithms. These algorithms use root mean square error (RMSE) between the calculated and the measured current as an objective function. A new metaheuristic amalgamation algorithm, namely biogeography-based teaching learning-based optimization (BB-TLBO) is proposed. This algorithm is a hybridization of two algorithms, the first one is called BBO (biogeography-based optimization) and the second is TLBO (teaching learning-based optimization). The BB-TLBO is proposed to identify the unknown parameters of one, two and three-diode models of the RTC France silicon solar cell and of the commercial photovoltaic solar module monocrystalline STM6-40/36, taking into account the performance indices: high precision, more reliability, short execution time and high convergence speed. This identification is carried out using experimental data from the RTC France silicon solar cell and the STM6-40/36 photovoltaic module. The efficiency of BB-TLBO is checked by comparing its identification results with its own single algorithm BBO, TLBO and newly introduced hybrid algorithms such as DOLADE, LAPSO and others. The results reveal that the suggested approach surpasses all compared algorithms in terms of RMSE (RMSE min, RMSE mean and RMSE max), standard deviation of RMSE values (STD), CPU (execution time), and convergence speed.

Investigation of the trail environment to enhance the efficiency of the solar cell through pre-installation study

This research investigates the performance of solar photovoltaic modules in real-world climatic conditions at various locations in India using MATLAB simulation. The study utilizes a single-diode model and a detailed simulation of a solar PV module to analyze the P-V and I-V characteristics of the module on a monthly basis. The month-wise power output is evaluated in relation to temperature and solar irradiance under various weather conditions. To model the PV module, the input parameters such as solar irradiance and temperature were first determined, and an appropriate PV panel model was selected based on the complexity and accuracy required. The PV panel model was then set up in MATLAB and run to generate the output data. The simulated results were compared to the verified data sheet of the JAM60S10-350/MR module, demonstrating that the simulation accurately represents the PV solar module's performance curve. The study aims to identify the most efficient locations for installing solar PV modules for optimal efficiency. Different models such as single-diode, two-diode, and PV system model can be used to model PV panels depending on the specific conditions being simulated and the level of accuracy required.

Modeling and simulation of PV system with three phase inverter along PV, IV curves using MATLAB/Simulink

Modeling and simulation of PV system with three phase inverter along PV, IV curves using MATLAB/Simulink

Parameter Estimation of Solar PV Using Ali Baba and Forty Thieves Optimization Technique

The modeling of a solar PV system is challenging due to its nonlinear current vs. voltage characteristics. Although various optimization techniques have been applied for the parameter estimation of the solar PV system, there is still a scope to attain the best-optimized results. This paper uses a new meta-heuristic optimization algorithm and a classical technique named Ali Baba and the Forty Thieves (AFT) with Newton Rapson (NR) method to estimate solar PV system parameters. The well-known story of Ali Baba and the Forty Thieves has inspired the AFT. Besides, the inappropriate objective function used in earlier research to extract parameters from solar PV models is recognized. The experimental findings demonstrate that the suggested approach performs better when compared to state-of-the-art algorithms. Between the measured data and the computed data for AFT, the root mean square error values for the five PV models, such as single diode model (SDM), double diode model (DDM), Photowatt-PWP201, STM6-40/36, and STP6-120/36, are respectively 7.72 × 10−04 ± 6.121 × 10−16, 7.412 × 10−04 ± 9.52 × 10−06, 2.052 × 10−03 ± 3.05 × 10−17, 0.001721922 ± 2.19 × 10−17, and 0.014450817 ± 3.42 × 10−16. In terms of accuracy, the obtained results indicate that the proposed AFT algorithm is more efficient than the other optimization techniques available in the literature. The excellent correlation between the estimated parameters from characteristic curves and observed data for SDM, DDM, Photowatt-PWP201, STM6-40/36, and STP6-120/36 demonstrates that the proposed AFT is a potential option among the techniques available in the literature. The Friedman and Wilcoxon tests have been used to assess the statistical validity of the proposed algorithms.

Numerical Investigation of a Solar PV/T Air Collector Under the Climatic Conditions of Zarqa, Jordan

The use of hybrid photovoltaic/thermal (PV/T) and low concentrating photovoltaic/thermal (LCPV/T) systems can significantly enhance the overall solar energy conversion efficiency by delivering electricity and thermal energy. This paper presents a case study using a standing PV system's theoretical and modeling approach that can be modified to adapt to the hybrid technology. Firstly, a single-pass conventional PV/T air-cooled collector is investigated based on heat transfer and electrical models under the climatic conditions of Zarqa, Jordan. The performance parameters are evaluated using thermal and electrical properties of the considered PV installation and measured meteorological data. Results show that the total energy produced varies between a maximum of 134.6 kWh/m2 in July and a minimum of 81.7 kWh/m2 in January. The annual average hourly variation of overall energy efficiency ranges between 79.2% and 88.4%. Moreover, the dissipated thermal energy can meet 63.6% of the total energy required to ventilate the Hashemite University Presidency Building during the winter months. Finally, the performance of the modeled PV/T system air system coupled with flat boosters to provide a low irradiation concentration ratio (CR) is explored. The maximum electric output of the resulting LCPV/T system is compared with the uncooled system. It is found that the percentage improvement due to air cooling ranges between 0.72% at CR=1 and 2.77% at CR=2.5

The effect of short-term inverter saturation on modeled hourly PV output using minute DC power measurements

PV system modeling is primarily done on hourly timescales and so cannot capture subhourly effects, including inverter saturation. Inverter saturation occurs when the potential dc power, Pdc, produced by the collectors is greater than the inverter capacity, and some of the PV power is lost or “clipped.” The inverter clips power rapidly, and calculations based on hour-averaged Pdc will overestimate ac power output for hours in which clipping occurs intermittently. Clipping is greater in systems with high ratios of collectors to inverter capacity, “dc:ac ratio.” We studied this modeling error using minute-scale Pdc measurements from a test site in Birmingham AL that had four different mounting configurations equipped with oversized inverters; i.e., 0.8 dc:ac ratio. PV output was calculated using minute- and hour-averaged Pdc and modeled inverters with dc:ac ratios up to 2.0. The modeling errors due to short term inverter saturation were approximately 2% of the annual output for 1.4 dc:ac ratios. We present the effect of mounting type, dc:ac ratio, season, and hour-of-day on these errors for the study site.

The feasibility of using rooftop solar PV fed to the grid for Khalifa Town houses in the Kingdom of Bahrain

The fast-growing construction industry and residential buildings in Bahrain create massive energy and environmental demands. Therefore, Bahrain has set a national renewable energy target of 5% by 2025.The novelty of this study is investigating the feasibility of using rooftop photovoltaic systems, Fed to the national grid, in residential buildings (Khalifa Town, Bahrain) - located in arid zone - combining architecture aesthetics, social acceptability and functionality. The assessment of the rooftop area and the PV system modeling was carried using AutoCAD and PVsyst software. Consideration was given to design aesthetics and the functionality of having PV panels on the roof, without losing the use of the roof for social gathering and activities. Our results show that installing 17 kW - PV panels, for each of 1,724 villas in the town, will produce annual solar electricity of 44,953 MWh, which is sufficient to meet about 43 % of the total town’s electricity needs. This rooftops installation will cut CO2 emission by 34,794 tons, i.e., reducing 21 % of the town’s total CO2 emissions.The study shows that the payback will be 9.6 years if the government purchases each kWh of solar electricity for 29 fils (USD ¢7.5). Establishing feed-in-tariff policy (FIT) will reduce the payback period and accordingly boost local PV manufacturing and create more green - collar jobs.

A novel approach for optimal sizing of stand-alone solar PV systems with power quality considerations

Designing reliable and cost-effective solar PV systems with compliance to national and international power quality standards is critical for their economical, efficient, and safe operation. The conventional approaches currently being used to optimally size the solar PV systems generally ignore power quality criteria during the initial design phase. This paper fills this gap by presenting a novel Genetic Algorithm (GA) based strategy to design a stand-alone solar PV system featuring optimal system size with conformance to power quality standards. MATLAB/Simulink environment was used to develop a detailed model of solar PV system, including a robust control mechanism for maximum power point tracking, battery bi-directional control, and inverter output control. An optimisation algorithm based on the single-objective GA was then designed to find the optimal PV array size, battery capacity, and the values of harmonic filter components so that the total investment cost is minimised and load demand as well as power quality criteria over the studied period are satisfied. The simulation results, corroborated with insightful discussions demonstrate that ignoring power quality criteria by selecting improper non-optimal system parameters can lead to inadmissible voltages and THD levels in the system. In contrast, the proposed design strategy can successfully devise a solar PV system that is optimally sized and complies with power quality standards.

Correction: Mekonnen et al. Modeling, Analysis and Optimization of Grid-Integrated and Islanded Solar PV Systems for the Ethiopian Residential Sector: Considering an Emerging Utility Tariff Plan for 2021 and Beyond. Energies 2021, 14, 3360

The authors wish to make the following corrections to their paper [...]