Grid-connected Photovoltaic System Research Articles

Enhancing solar efficiency in steppe regions: a comprehensive performance evaluation of photovoltaic systems in M’sila, Algeria

This study assesses a 10 kW grid-connected solar PV system in Algeria's harsh steppe climate in M'Sila, characterised by intense solar radiation and considerable temperature variations. High temperatures reduce photovoltaic conversion efficiency and increase thermal stresses, prompting a detailed investigation into PV systems' challenges in such environments. The research reveals that M'Sila's system generates 7,794.8 kWh annually, with an efficiency range of 16%–19.2%, peaking slightly. Unique thermal management techniques are necessary to sustain efficiency, as extreme heat causes efficiency losses of up to 20%. The levelized cost of energy (LCOE) of $0.0138 per kWh makes the system economically viable in these conditions. The investment proves worthwhile, yielding annual savings of $304. The M'Sila solar system also reduces CO₂ emissions by 4.07 tonnes per year. Algeria’s shift toward renewable energy and carbon reduction gains an additional $59.11 annually in “carbon credit” from these emissions reductions. This research supports Algeria’s renewable energy goals by guiding energy companies and decision-makers to improve efficiency and minimise environmental impact in steppe regions like M'Sila.

Enhanced model predictive control using artificial neural networks for grid-connected two-level inverters

Integrating artificial intelligence (AI) to improve the performance of photovoltaic systems is compelling for two main reasons. First, AI technologies are making significant progress and are widely applied across various fields, such as medicine and agriculture. Second, the world is experiencing an increasing demand for energy while simultaneously facing the challenge of reducing reliance on traditional energy sources that exacerbate carbon emissions and climate change. This emphasizes the critical importance of transitioning to sustainable and clean energy solutions. In this context, photovoltaic panels have emerged as one of the most promising and widely adopted renewable energy sources. As the global reliance on solar energy grows, enhancing the efficiency and reliability of solar energy systems has become imperative. However, this transition is accompanied by significant challenges, particularly in integrating these systems with existing power grids. The complexities involved in achieving seamless integration, maintaining consistent performance, and preventing system failures necessitate the adoption of advanced technologies. These challenges are further exacerbated by the need to manage fluctuations in energy production, optimize energy storage, and ensure the long-term sustainability of solar power. This paper presents a novel approach for controlling ANN-MPC solar inverters, leveraging artificial neural networks (ANN) to address the challenges related to the efficiency of photovoltaic systems and their integration with the grid, ultimately reducing dependence on conventional energy sources. Initially, the ANN-based model is trained using large datasets derived from the system inputs and outputs, taking into account all critical operating conditions, such as sudden changes in current. Following the training process, the model acquires extensive data, enabling it to adapt to all transient conditions the system may encounter. The model continuously evolves to improve the efficiency of grid-connected photovoltaic systems. Additionally, experimental validation and performance testing of the proposed model are conducted to verify the effectiveness and flexibility of the ANN-based approach. The experimental results confirm the proposed approach's ability to enhance the performance of grid-connected electrical systems, reduce computational costs, and achieve model-free control.

Optimal control of grid-connected overvoltage of distributed photovoltaic power generation based on cluster division

To address the overvoltage problem caused by the reverse flow of current when a high proportion of distributed photovoltaic (PV) is connected to the distribution network, this paper proposes a grid-connected voltage regulation control strategy based on the cluster division of the Distributed Model Predictive Control (DMPC) algorithm. Firstly, the overvoltage responsibility of each node is calculated using the Shapley value method. This is combined with k-means clustering to achieve effective cluster division, enabling dynamic adjustment of the active and reactive power of photovoltaic power generation units to stabilize regional voltage. Secondly, a group grid-connected voltage control strategy is introduced. This strategy controls the active and reactive power outputs by integrating real-time power output and voltage information from PV generating units in the region with the DMPC algorithm, ensuring overall voltage stability of the grid-connected system. Finally, actual overvoltage data from a 10 kV distribution line in the Dingxi power grid, Gansu Province, is used to verify that under the proposed control strategy, PV grid-connected overvoltage nodes are maintained within 1.06 p.u. The control effect is improved by a margin of 0.05 compared to traditional control methods. This demonstrates the effectiveness of the grouped grid-connected voltage regulation control strategy, achieving smoother voltage regulation performance in distributed PV grid-connected systems.

Grid-connected double-stage PV system with space vector PWM inverter and MPPT

Because of the increasing demand for non-conventional energy sources, photovoltaic system integration into the electrical grid is becoming more crucial. It is advised to employ a double-stage grid-connected PV system. This can be employed with the main parts boost converter, which helps to boost the DC output from the PV channels. And next one is the space vector pulse width modulation (SVPWM) inverter which can provide better harmonic performance and higher efficiency compared to traditional PWM methods. The SVPWM technique is employed to modulate the inverter output, generating a sinusoidal AC waveform that matches the grid frequency and voltage. By adjusting the pulse width to achieve effective and trustworthy grid integration. To maximize power extraction takes place by using maximum power point tracking (MPPT). The SVPWM inverter is crucial in converting DC power to AC power and enabling grid connection. Utilizing SVPWM allows exact control of voltage magnitude, frequency, and phase angle to provide high-quality sinusoidal AC output voltage. The power quality of the electricity pumped into the grid is improved by this precise management, which also ensures adherence to grid standards and reduces harmonic interference.

Enhancing Grid-Connected Photovoltaic Systems' Power Quality through a Dynamic Voltage Restorer Equipped with an Innovative Sliding Mode and PR Control System.

This study focuses on enhancing power quality in on-grid photovoltaic (PV) schemes through an innovative dynamic voltage restorer (DVR) that integrates two control strategies with a multi-level inverter. The DVR, a power electronic compensator, corrects voltage disturbances such as sag and swell by adjusting the voltage at the point of common coupling (PCC). It utilizes sliding mode control (SMC) for normal operations and proportional resonance (PR) during voltage disruptions, ensuring accurate voltage correction. The system's multi-level inverter offers a distinct advantage over traditional high-frequency inverters, which typically suffer from significant switching losses in high-power applications. The multi-level inverter effectively detects and mitigates voltage issues while minimizing harmonic distortion. The study evaluates the DVR's performance under various conditions, including voltage swell, disruption, mild sag, and severe sag. Simulation results using the Simulink tool demonstrate that the proposed DVR significantly reduces voltage disturbances and enhances power quality in the PV panel's output, the PCC, and the injected voltage. The findings suggest that this dual-control DVR designe, with its efficient use of a multi-level inverter, is a promising solution for improving power quality and stability in on-grid PV arrangements.

A data-driven approach to grid-connected PV system reliability assessment: Combining deep learning and hybrid optimization

A data-driven approach to grid-connected PV system reliability assessment: Combining deep learning and hybrid optimization

A Comprehensive Analysis of the Influencing Factors of Interharmonics on a Distributed PV Grid-Connected Power Generation System

In this paper, a detailed mathematical model for the interharmonic current in a distributed grid-connected photovoltaic (PV) system is proposed and the factors affecting its output characteristics are analyzed comprehensively. First of all, a transfer function approach is used to build a mathematical model for the interharmonic current in grid-connected PV systems. Then, the equation of the PV generator output characteristics is linearized. Furthermore, a real-time calculation method of the amplitude of interharmonic current is introduced based on the established mathematical model. Moreover, a series of comparative tests are conducted, and how various factors such as the MPPT parameters, the main circuit parameters and the environmental factors affect the interharmonic current are investigated. Finally, a series of simulation and experimental tests are conducted to verify the accuracy of the mathematical model for the interharmonic current and the real-time calculation method. The results show that the proposed model is useful for improving the performance of grid-connected PV systems in terms of the behavior of the interharmonic current. Moreover, the mathematical model and the analysis of the influencing factors provide valuable insights for improving system efficiency and reliability in practical applications.

Power Quality Enhancement in Grid-Connected Solar PV Systems Using Adaptive Control and Multilevel Inverter Topologies Under Dynamic Grid Conditions

This paper introduces a control strategy that uses an integrator-based positive sequence estimator to improve the power quality of a grid-connected double-stage solar PV system. The control extracts positive sequence components from distorted and unbalanced grid voltages to calculate unit templates and grid reference currents during grid anomalies like distortion, unbalance, sag/swell, and DC offset. A feedforward term is introduced to the photovoltaic array to ensure rapid transient response, and the DC-link voltage is adaptively regulated to reduce the voltage source converter (VSC) losses during weak grid conditions. The paper compares the performance of two-level and three-level inverters in this system configuration, highlighting the differences in power quality improvement, harmonic reduction, and system efficiency under various grid disturbances and intermittent solar conditions. Simulation results, performed in MATLAB, validate the superior performance of the three-level inverter in terms of lower total harmonic distortion (THD) in grid currents, in compliance with IEEE standard 519, while demonstrating the satisfactory response of both inverter types during challenging grid conditions like intermittent solar irradiation, DC offset, voltage distortions, unbalance, and voltage sag/swell.

A single switch high step-up DC-DC converter derived from coupled inductor and switched capacitor for a photovoltaic system

This study suggests a single switch high step-up DC-DC Converter derived from coupled inductor and switched capacitor used in Grid-Connected Photovoltaic systems. In the suggested converter, a part of the yield voltage is produced by parallel charging of the capacitors on the side of the secondary winding and their series discharge together with the secondary winding. The other part of the output voltage is obtained by simultaneously charging the boost and buck-boost capacitors and discharging them in series with the input voltage source. Finally, these two parts make the output voltage in series, so that high voltage gain with proper duty cycle is obtained. In addition, boost and buck-boost capacitors absorb leakage inductance energy leading to a reduction of the switch voltage stress. As a result, switching losses are reduced and by choosing a switch with lower RDS(ON), conduction losses are also reduced. Finally, a prototype with an output power of 200 Watts, and a voltage conversion of 24–400 Volts was made to confirm the performance in the laboratory, which has the highest efficiency of 95.89%.

Review Paper of Grid-Connected Solar PV Systems With Decoupled Control

This paper presents a decoupled control for grid-connected solar photovoltaic (PV) system. The control framework used in this paper aims not to track the changing maximum power point (MPP) for extracting power at MPP, hence blocking the MPP tracking issue against the effect of solar radiation and temperature. Real power is produced by tracking the control voltage with a zero-dynamics-based controller. A cascaded loop controller with inner loop to regulate the control voltage is incorporated to ensure the produced real power follows the reference power in the presence of power disturbance. The proposed control scheme with the consideration of the inverter's rated voltage shows improved system dynamics. Simulations in various conditions are conducted to prove the effectiveness of the proposed control strategies. CIGRE 13-node benchmark system is used as the case study to evaluate the results of the PV system connected to a more complex power system. It has been shown that the proposed controller allows the total production of the energy under maximum power point conditions and also improves the overall stability of distributed generation connected to the grid. Therefore, it can be implemented to increase the capacity of renewable inverter-based power generation and the power system quality.

Adaptive Generalized Extended State Observer for a Single Phase PV Grid-connected System Operating Under the Sudanese-Sahelian Climate of Cameroon

Knowing the health of a system allows to guarante its efficiency and sustainability. The state observer is one of several techniques used by authors to estimate system state. This paper focuses on the problem of simultaneous states estimation of DC (Direct Current) and AC (Alternating Current) sides of a single-phase Photovoltaic (PV) grid-connected operating under the Sudanese-Sahelian climate of Cameroon. A generalized extended state observer (GESO) has been designed to simultaneously estimate the three states and the three disturbances of the system. A good estimation of the state and disturbances is achieved by the appropriate choice of the observer gain and the disturbance compensation gain resulting from the correct pole placement. The GESO robustness has been tested by varying the PV voltage and grid voltage. When there are no input fluctuations, the estimation errors of nominal states and disturbances converge to zero. The fluctuation in PV voltage resulting from partial shading has a significant impact on the boost converter current. The boost converter current varies proportionally with the drop in voltage due to partial shading from 55% to 59%. Under the grid voltage fluctuation, the boost converter current remains stable while the DC bus voltage and inverter current are significantly affected. The proposed GESO prove its robustness to perturbations from the PV array and grid side into the Single-Phase PV Grid-connected System. This paper contributes to the study of observers applied to the PV system and points the way to future work on diagnosing faults in PV systems operating in Cameroon's Sudanese-Sahelian climate.

Direct Normal Irradiance Prediction-Based Optimum Interval Tilt Angles for Enhancement of Energy Output, Levelized Cost of Energy, and CO2 Emission in a Grid-Connected Photovoltaic System

Abstract The tilt angle of photovoltaic (PV) panels is a crucial determinant of their performance and can be adjusted using different tracking methods. Periodically changing the tilt angle strikes a practical balance between efficiency and cost. This work introduces a bi-directional long short-term memory (Bi-LSTM)-based direct normal irradiance (DNI) prediction to estimate the time intervals for the tilt angle adjustments. DNI prediction involves 22-year (2000–2022) historical time series data and the Bi-LSTM deep learning model to predict DNI at different time frames for the location Madurai, India. Using the predicted DNI, tilt angle-based DNI is mapped using the tilt angle correlation through a nearest neighborhood interpolation method. DNI potential over a specific period is utilized to find the optimum time intervals for the tilt angle adjustments. The simulation study of this work is implemented with a 5 kW grid-connected solar PV system using pvsyst software. The effectiveness of the proposed methodology is evaluated based on the improvements in power output, levelized cost of energy (LCOE), and carbon emission reductions and compared with other existing methods. The results showed that using the proposed optimal tilt angle intervals led to a 10.31% increase in PV output power, the lowest LCOE at 3.61 c/kW h, and 8.363 tCO2/year carbon emissions.

Control of transient power compensation for virtual impedance VSG in Quasi-Z-source photovoltaic grid integration system

The virtual impedance solution effectively addresses the power coupling issues and improves small-signal stability in grid-connected Virtual Synchronous Generator (VSG) systems but can deteriorate the system's transient synchronous stability, particularly in high-voltage lines with significant line inductance exacerbating this effect. To address these contradictions, the paper first analyzes the power coupling mechanisms of the system, highlighting how the line reactance ratio (R/X) and power angle (δ) affect system stability, and describes the transient stability of VSGs using the equal area criterion. Leveraging the advantages of quasi-Z-source inverters, they are applied to VSG grid-connected systems, proposing an improved VSG control strategy tailored for quasi-Z-source photovoltaic grid-connected systems. This strategy introduces virtual active power at the point of common coupling (PCC) and uses it as power feedback in the control loop, instead of using real active power. The control model is validated on an experimental platform, demonstrating that the VSG control strategy with transient power compensation significantly enhances system transient stability while preserving small-signal stability. This comprehensive approach bridges the gap between maintaining essential stability functions and enhancing dynamic performance under various operational conditions.

Economic feasibility assessment of optimum grid-connected PV/battery systems to meet electricity demand for industrial buildings in Saudi Arabia

This study presents a comprehensive analysis of the energy performance and economic feasibility of optimal power generation systems, including an electrical network and a grid-connected PV/battery system, designed to meet the electricity demands of an industrial building in Saudi ‘Arabia’s Eastern region. The building, located in Abqaiq City, spans approximately 29,000 m2 and has an average annual electrical consumption of 6,500 MWh. The primary focus is on assessing the economic feasibility of these systems under local grid conditions. Simulations using PVsyst software were conducted for three configurations: grid-connected PV and PV with battery. The findings indicate that bifacial PV modules increase energy harvesting in coastal arid climate regions, with specific production ranging from 2,235 to 2,158 kWh/kWp/year and a PR between 95.9 % and 92.6 %. The grid-connected PV system is more feasible under industrial electricity tariffs, with a levelized cost of energy of $0.016/kWh, an NPV of $4,233,274, an ROI of 426.5 %, and a payback period of 4.7 years. These systems achieve energy savings of approximately 66 % for grid-connected PV and 89 % for hybrid PV/battery systems. Additionally, commercial and global tariffs significantly enhance the NPV and ROI of both systems, reducing the payback period and improving economic feasibility. Under commercial tariffs, the grid-connected PV system excels in ROI and payback period, while the hybrid system outperforms in NPV under global tariffs. By addressing economic and climate challenges in harsh coastal environments, this work provides valuable insights for sustainable investment decisions in an industrial city context

Advanced control strategies for multilevel inverter in grid-connected and off-grid photovoltaic systems: A multi-objective approach using LS-PWM for THD reduction

Advanced control strategies for multilevel inverter in grid-connected and off-grid photovoltaic systems: A multi-objective approach using LS-PWM for THD reduction

Research on adaptive control strategies for grid-friendly photovoltaic storage network systems

Abstract To address the critical issue of frequency stability in grid-connected photovoltaic energy storage systems, a control strategy based on grid-friendly technologies is proposed. This strategy integrates the principles and topology of traditional Virtual Synchronous Generator (VSG) with adaptive VSG control and pre-synchronization techniques. Firstly, based on the traditional VSG control strategy, the frequency operation curve of the VSG is divided into three intervals corresponding to different control modes: islanding mode, PV-storage frequency stabilization mode, and adaptive regulation mode. Each mode is analysed to understand the impact of different inertia and damping coefficients on system output characteristics. A control strategy that allows for adaptive adjustment of inertia and damping coefficients is designed, referencing the power angle characteristic curve and frequency oscillation curve of a synchronous generator (SG). By introducing inertia elements, the robustness of the system against disturbances is enhanced. Utilizing the operational characteristics of energy storage, the combined PV and energy storage system can better interact with and support the grid. Finally, simulation experiments are conducted by using MATLAB/Simulink. The proposed strategy is compared with traditional adaptive control and VSG control strategies. The results demonstrate that the proposed grid-friendly VSG control strategy offers superior frequency stability, robustness, and response speed.

Optimal Placement and Upgrade of Solar PV Integration in a Grid-Connected Solar Photovoltaic System.

Optimal Placement and Upgrade of Solar PV Integration in a Grid-Connected Solar Photovoltaic System.

MMC-Based PV Grid-Connected System With SMES-Battery Hybrid Energy Storage System

MMC-Based PV Grid-Connected System With SMES-Battery Hybrid Energy Storage System

Design of a two-stage photovoltaic grid-connected system with dual closed-loop control

Abstract This paper designs a two-stage photovoltaic grid-connected system with dual closed-loop control, cascading the topological structures of photovoltaic cells, boost chopper circuits, and inverter circuits. The front-stage boost chopper circuit control utilizes the incremental conductance method to achieve maximum power point tracking control. The rear-stage inverter circuit employs a dual closed-loop control system with an outer voltage loop and an inner current loop, incorporating a proportional-integral controller, to ensure stable DC-side voltage and unity power factor for grid connection. A simulation model of the two-stage photovoltaic grid-connected system designed in this paper was constructed and analyzed through simulation runs. The firmness of the DC-side voltage and the achievement of unity power factor during grid connection confirmed the operability and resultiveness of the cascaded topology and the control method.

High-Voltage Ride-Through Method for Single-Stage Grid-connected Photovoltaic System Based on Model Predictive Control

High-Voltage Ride-Through Method for Single-Stage Grid-connected Photovoltaic System Based on Model Predictive Control