Two-stage Photovoltaic System Research Articles

Research on inertia characteristics of two-stage photovoltaic systems under generalized sag control

With the vast majority of photovoltaic (PV) power generation linked to the grid, the mainstream maximum power point tracking control cannot provide effective inertia support capability for the system. This paper examines the inertia source and action rules of three typical grid-tied photovoltaic systems under generalized sag control at the physical mechanism level, using the theory of the static synchronous generator model as a guide. It is found that the PV system under generalized sag is also capable of supporting the system through inertia. The boost converter, direct current bus capacitor, and inverter all contribute to the inertia capability of the PV system, but it is necessary to couple the control of the responding link with the grid frequency. The closer the action link is to the grid, the faster the speed of the corresponding grid frequency, but the weaker the inertia effect is provided to the system. The accuracy of the aforementioned analysis is confirmed by the simulation.

A Transformerless Photovoltaic System Employing a Cubic Cell Boost Converter for Low Voltage Application

A photovoltaic (PV) system is commonly used to satisfy the power demand of the utility. This paper investigates the utilization of a high voltage gain Cubic Cell Boost Converter (CCBC) in a transformerless photovoltaic (PV) system for low voltage applications. The proposed system is a combination of a CCBC and a three-phase inverter creating a two-stage three-phase PV system. The CCBC is linked with the low-scale PV sources to step up its input DC voltage and maintain a constant DC bus voltage by employing the Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) control algorithm. The DC bus is further connected to an LCL filter based three-phase inverter using a synchronous reference frame (dq) control scheme to power the three-phase utility. The proposed combination is validated by simulating in MATLAB/ SIMULINK environment for a 5.5 kW PV source and achieved an efficiency of 91% with 1.91% of inverter Total Harmonic Distortion (THD) at unity power factor. In the proposed system, CCBC with P&O MPPT control provides a high step-up DC bus voltage with less input current ripple and output voltage ripple and maintains a constant DC bus under variable solar irradiance. This work does not account for the common leakage current that is often produced in a transformerless PV system.

Frequency regulation method for two-stage PV system based on DC voltage coordination

The current frequency regulation methods for a photovoltaic (PV) system cannot balance frequency support and primary control performances. This paper proposes a frequency regulation method for a two-stage PV system by controlling DC voltage, which is coordinated with the enhanced virtual inertia control (VIC) of the DC capacitor. The power reserve control of the PV arrays is improved considering the characteristics of the VIC, thereby strengthening the frequency regulation ability of the PV system. An active DC voltage recovery control is designed at the inverter to restore the frequency support ability after primary frequency control. With MATLAB/Simulink software, the performance of the proposed method in dealing with different load sizes, load change trends, and DC voltage recovery coefficient is verified by comparing it with other traditional methods in different scenarios. The proposed method can fully use the available power to improve the frequency nadir, rate of change of frequency, and voltage recovery ability.

Intelligent Controller Based on Artificial Neural Network and INC Based MPPT for Grid Integrated Solar PV System

Solar photovoltaic (PV) systems have become an integral part of today's advanced energy infrastructure due to its low kinetic energy, its abundance availability, and its freedom from human interference. Solar PV systems have the potential to greatly reduce our reliance on fossil fuels, but their intermittent nature means they cannot provide a constant source of electricity. The system's security should be well thought out, and it should be able to withstand a lot of abuse. The current energy system faces a significant difficulty in ensuring continuous supply. In this study, a three-phase, two-stage photovoltaic system that is managed by artificial neural networks (ANN). A DC-DC boost converter with maximum power point tracking (MPPT) based on the incremental conductance (INC) method is incorporated in the first stage. In the next step, an ANN-based controller optimizes the performance of a three-phase switching PWM inverter that is connected to the grid by controlling currents along the d-q axis. Comprehensive simulations were carried out using MATLAB or Simulink to evaluate the system's performance under various illumination and temperature conditions. Results show that the suggested approach outperforms the baseline in a number of areas. Better dynamic reactions, accurate tracking of reference currents within permissible bounds, and quick settling periods after startup are all displayed by it. These findings show that our method has the potential to greatly improve the efficiency and dependability of solar PV systems. The results of this study have implications for renewable energy in general and present a viable path toward enhancing the resilience and sustainability of energy infrastructure.

Metaheuristics Assisted Efficiency Maximizing Flexible Power Point Tracking of a Photovoltaic Array Under the Partial Shading

The vast installation of the photovoltaic (PV) plants has necessitated bringing more flexibility to the PV power generation instead of the simple maximum power point tracking (MPPT). Certain flexible power point tracking (FPPT) techniques have already emerged to operate the PV array not only at the maximum power point (MPP) but also below the MPP. Similarly to the MPPT, the FPPT also needs special control techniques to operate under the partial shading condition. Apart from the local peak blockage problem, there is an issue of solution multiplicity in the FPPT. As there may be multiple equilibrium points for a specific power level, a procedure is needed to dynamically select the equilibrium at the highest voltage level so that the thermal stress on semiconductor devices can be minimized by maximizing the power conversion efficiency. The present work is undertaken to meet the particular objective. A metaheuristics assisted efficiency maximizing (MAEM) control algorithm is suggested to attain the desired power regulation under partial shading. A specific implementation of the MAEM control is shown for a two-stage PV system with due consideration for the duty ratio quantization effect. The proposed MAEM-FPPT control technique is thoroughly verified via both MATLAB simulations and practical experimentation.

Hybrid sensor-aided direct duty cycle control approach for maximum power point tracking in two-stage photovoltaic systems

A novel maximum power point tracking (MPPT) approach for two-stage photovoltaic (PV) systems is proposed, which is a hybridization of Perturb & Observe (P&O) with a modified version of the Fractional Open Circuit Voltage (FOCV) algorithm. Differently from other hybrid algorithms which merge P&O with FOCV or Fractional Short Circuit Current (FSCC), the proposed algorithm enables direct duty cycle control (DDCC), which significantly reduces efficiency losses due to steady-state oscillations. Also unlike similar methods, it provides a mechanism for tracking the global maximum power point during partial shading (PS). Validation of the proposed method is carried out via computer simulations and a practical experiment, whose results show that it yields superior performance compared to commonly used MPPT algorithms and, on more detailed analysis, improves standard P&O efficiency by a large margin (up to 15% at uniform irradiance and 27% during PS). Furthermore, it outperforms a similar hybrid, but non-DDCC, algorithm by up to 7% in efficiency.

Evaluation of the Main Control Strategies for Grid-Connected PV Systems

The present study aims at analyzing and assessing the performance of grid-connected photovoltaic (PV) systems, where the considered arrangement is the two-stage PV system. Normally, the maximum power point tracking (MPPT) process is utilized in the first stage of this topology (DC-DC). Furthermore, the active and reactive power control procedure is accomplished in the second stage (DC-AC). Different control strategies have been discussed in the literature for grid integration of the PV systems. However, we present the main techniques, which are considered the commonly utilized and effective methods to control such system. In this regard, and for MPPT, popularly the perturb and observe (P&O) and incremental conductance (INC) are employed to extract the maximum power from the PV source. Moreover, and to improve the performance of the aforementioned methods, an adaptive step can be utilized to enhance the steady-state response. For the inversion stage, the well-known and benchmarking technique voltage-oriented control, the dead-beat method, and the model predictive control algorithms will be discussed and evaluated using experimental tests. The robustness against parameters variation is considered and an extended Kalman filter (EKF) is used to estimate the system’s parameters. Future scope and directions for the research in this area are also addressed.

Low-frequency oscillation analysis of two-stage photovoltaic grid-connected system

The low-frequency oscillation (LFO) problem of photovoltaic (PV) grid-connected systems has been a critical concern for safe operation, whereas the impact of dc-side components of PV plants are always ignored and single-stage PV plant is used. This paper performs a comprehensive analysis of the LFOs in the two-stage PV grid-connected system. The complete small-signal model of the two-stage PV system is built. On this basis, the LFO modes and high-frequency oscillation (HFO) modes are calculated and related participating components are determined. Then, the impact of key parameters on the LFO characteristics is investigated with the root locus analysis. The theoretical analysis is verified through PSCAD/EMTDC simulations.

A New Analytical MPPT-Based Induction Motor Drive for Solar PV Water Pumping System With Battery Backup

In this article, an analytical method is presented to achieve maximum power point tracking (MPPT) for a solar photovoltaic (PV) array-based water pumping system comprising of an induction motor drive (IMD). The gating signals are generated using the space vector pulsewidth modulation (SVPWM) method for three-phase inverter. This analytical MPPT control (AMPPTC) scheme exhibits fast dynamic performance and minimum overshoot with the IMD-based water pumping system. Additionally, the AMPPTC scheme provides absolute steady-state robustness under variations in solar irradiance/parameters that improves the stability of the system under a wide speed range of IMD and makes the system insensitive toward parameter variations. The dc-link voltage regulation is assured by three-phase inverter, and MPPT regulation is achieved by the boost converter. This two-stage PV system, with MPPT controlled boost converter and SVPWM-based three-phase inverter operating the pump, is modeled and simulated in Simulink environment of MATLAB. The performance and robustness of the AMPPTC-based PV water pumping system are corroborated through the laboratory experimentation.

Estimation of the Output Characteristic of a Photovoltaic Generator under Power Curtailment and Considering Converter Losses

Power curtailment methods contribute to the frequency stability of power systems with a high share of photovoltaic generation. This paper focuses on an online strategy that estimates the output characteristic of a photovoltaic generator while operating in power curtailment mode by using voltage and current measurements and the nonlinear least-squares curve-fitting. In contrast to previously reported methods, this work introduces an improvement consisting of the estimation of the power losses of the electronic converter that connects the photovoltaic panel with the grid. Thus, the impact of a mismatch between the dc-side and the ac-side is reduced. The procedure is tested at different power levels and with fluctuations of irradiance and temperature. The results show that the converter efficiency, expressed as an exponential function with two quadratic equations, is associated with irradiance and temperature. It is also found that the two-stage converter efficiency is mainly affected by the irradiance level when the photovoltaic system operates on the left side of the power-voltage characteristic. In contrast, the temperature level influences the converter efficiency significantly when working on the right side of the maximum power point. The estimated efficiency curves can improve the accuracy of the power curtailment method and can be used for designing the two-stage converter. The effectiveness of the proposed power curtailment method has been tested in a two-stage photovoltaic system through MATLAB/Simulink.

Sliding Mode Control-Based MPPT and Output Voltage Regulation of a Stand-alone PV System

Abstract When it comes to reducing emissions caused by the generation of electricity, among different renewable energy sources, the solar energy gains prominence, due to its geographical availability, simplicity of implementation, and absence of physical moving parts. However, the performance of photovoltaic systems is dependent on environmental conditions. Depending on temperature and solar irradiation, the photovoltaic (PV) system has an operating point where maximum power can be generated. The techniques that are implemented to find this operating point are the so-called maximum power point tracking (MPPT) algorithms. Since weather conditions are variable in nature, the output voltage of the PV system needs to be regulated to remain equal to the reference. Most of the existing studies focus either on MPPT or on voltage regulation of the PV system. In this paper, the two-stage PV system is implemented so that both MPPT and voltage regulation are achieved simultaneously. Additionally, an improved version of the perturb and observe (P&O) algorithm based on artificial potential fields (APF), called APF-P&O, is presented. According to the results of the simulations carried out in MATLAB/Simulink software, the APF-P&O method is more efficient than the conventional method.

Contribution to the Control of the Power Switches of DC-DC Converters with two stages of a Photovoltaic System

The work presented in this article proposes the design and the realization of a PWM controller, which allows the control of the power switches of DC-DC converters of discrete two-stage photovoltaic systems in series. The method employed is based on the use of two drivers by exploiting their functionalities in order to improve and control the two power switches of the discretized photovoltaic system. The proposed technique is validated by experimentation on a photovoltaic system, the upper stage of which can request a floating voltage on the MOSFET drain of up to 30V. the studied PV installation is equipped by a protection circuit block for protect the PV equipments in the event of poor connection or deterioration of elements in system blocks. The simulations and the experiments showed a good functioning of the control unit which ensured: An amplitude of the PWM signals large enough to control the power switches, optimal system operation regardless of load and weather changes and good efficiency, and protection of the installation in the event of malfunction.

Predictive Fixed Switching Maximum Power Point Tracking Algorithm with Dual Adaptive Step-Size for PV Systems

Maximum power point tracking (MPPT) is an essential and primary objective in photovoltaic (PV) systems implementation. Thus, in this article, the predictive fixed switching MPPT technique is proposed for a two-stage PV system, where the system under consideration consists of a PV source, boost converter, and two-level inverter. The MPPT design is based on dual adaptive step-size realization to limit the duty cycle oscillations at a steady state. Furthermore, the PI controller is eliminated, which simplifies the MPPT implementation. The suggested tuning procedure of the duty cycle is compared with the conventional adaptive step-size perturb and observe (P&O) method. The inverter is controlled using an efficient finite-set model predictive control (FS-MPC) algorithm with reduced computation burden, where the optimal switching state vector is identified based on the polarity of the reference voltage in the α-β reference frame and without any need for sector determination. Furthermore, the cost function of the FS-MPC algorithm is modified to include the reduction of the switching frequency as a secondary objective for the inverter control. The overall control methodology is evaluated using experimental results at different operating conditions.

Power production strategies for two-stage PV systems during grid faults

The paper comprehensively addresses the control algorithm for the photovoltaic (PV) system. The system’s operation during both nominal and faulty grid conditions, most notably voltage unbalances, is addressed. The control of the boost converters and the inverter that secures reliable and maximized power production is proposed. Specifically, the paper offers a novel DC-link voltage stabilization algorithm that is not based on conventional approaches, such as droop schemes. Rather, the DC-link voltage rate of change is used to realize safe primary energy sources’ power management during transients caused by grid disturbances. This offers improved robustness, reliability and scalability. Moreover, the improved grid-connected converter control is proposed. It enables the production of arbitrary currents and powers profiles, during different working regimes, respecting the converter’s ratings. Consequently, higher-layer control functions can be realized by utilizing the proposed scheme. Also, the flexible power production prioritization feature is integrated into the overall solution. Such an extensive set of features was not demonstrated for PV systems in the literature previously. Different hardware topologies are regarded – centralized, decentralized and distributed. The proposed control schemes were tested using the hardware-in-the-loop (HIL) environment and were validated through the analysis of the obtained results.

Advanced Control Strategy With Voltage Sag Classification for Single-Phase Grid-Connected Photovoltaic System

This article develops a fault ride-through control strategy for achieving low-voltage ride through in single-phase grid-connected photovoltaic (PV) systems (GCPVS). The proposed control system adapts a neural network classifier for islanding classification and model predictive control for achieving the control of the two-stage PV system. This control scheme takes advantage of the nonlinear nature of the power converters and develops a cost function-based approach to achieve fast and efficient control. In addition, the proposed controller provides voltage support to the grid during voltage sags by injecting minimum reactive current within the threshold. The operation of the proposed control strategy is verified by performing simulation tests on a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$4\ {\text{kW}}$</tex-math></inline-formula> GCPVS by creating a sag type of fault in the utility. Further, laboratory experiments were carried out with the developed controller. The results ensure that the proposed control system adheres to the grid requirements by enabling voltage support during grid faults.

Inverter Control Performance Study on Solar PV Systems and Its Effect on Power Quality

Power generation faces a major challenge in meeting peak load requirements. Energy suppliers are highly dependent on fossil fuels due to the limited resources of non-renewable energy production. Therefore, researchers and scientists are looking for distributed generators (DGs) to provide additional power during peak periods of the energy curve. Solar energy gives them an extra twist to meet the load demand during this time. As a result, the grid-based solar photovoltaic (PV) system is attracting particular attention from researchers and industry in order to reduce the burden of fossil fuel power generation. Single-stage and two-stage photovoltaic systems are suitable for grid connection with or without battery holder. This article provides a comprehensive overview of a grid connected solar system. The entire architecture of the on-grid photovoltaic system includes the construction of a photovoltaic generator, MPPT methods and DC-DC converters.

Small-Signal Modeling and Analysis of Virtual Inertia-Based PV Systems

Renewable energy sources normally provide low inertia, which allows a little time for controlling the system. The inertia emulation has recently been introduced for photovoltaic (PV) generation to fight against the small inertia and improve the energy efficiency. The main purpose of this article is to analyze the stability of a virtual inertia-based three-phase two-stage PV system for smart grid applications. Dynamics of DC/DC converter, DC/AC converter, AC side filter, virtual inertia controller, and controllers of the DC/DC and DC/AC converters are considered in the modeling procedure. Eigenvalue analysis is performed to evaluate the sensitivity of the design parameters on stability of a grid-connected virtual inertia PV system. Time-domain simulations using MATLAB/Simscape Power System toolbox are used to validate the eigenvalue analysis results.

Structure-Preservation Model Aggregation for Two-Stage Inverters Based Large-Scale Photovoltaic System

With the increasing penetration level of large-scale photovoltaic (PV) generator connected to the grid, an accurate simulation model is required for the dynamic analysis of the PV system. However, the detailed electromagnetic simulation of the large-scale system is complex and the dynamic response capability is estimated with obstacle caused by large computational burdens. Therefore, a precise dynamic aggregated model is indispensable for the displacement of the large-scale PV system. The structure-preservation based aggregated model with comprehensive equivalent parameters for large-scale PV system is proposed in this paper. A complete two-stage PV system model is established to analyze the dynamics of the system. Then, the aggregation method is obtained by comparing the dynamic equations of the detailed model with the aggregated model, which is based on the energy relationship in the PV system. Furthermore, four different case studies are considered including the aggregation of identical and different ten parallel-connected PV units both under the same irradiance condition, and the aggregation of different ten parallel-connected PV units under different irradiance and weak grid scenarios, where the aggregation models are obtained through the proposed equivalent modeling method. Finally, the effectiveness of the proposed aggregation method is verified by the simulation results from PSCAD/EMTDC platform, and the consistency between the aggregated model and the detailed model is confirmed under different disturbances of irradiance variation, and continuous symmetric and asymmetric grid faults.

A State-Space Dynamic Model for Photovoltaic Systems With Full Ancillary Services Support

Large-scale photovoltaic (PV) integration to the network necessitates accurate modeling of PV system dynamics under solar irradiance changes and disturbances in the power system. Most of the available PV dynamic models in the literature are scope-specific, neglecting some control functions and employing simplifications. In this paper, a complete dynamic model for two-stage PV systems is presented, given in entirely state-space form and explicit equations that takes into account all power circuit dynamics and modern control functions. This is a holistic approach that considers a full range of ancillary services required by modern grid codes, supports both balanced and unbalanced grid operation, and accounts for the discontinuous conduction mode of the dc/dc converter of the system. The proposed dynamic model is evaluated and compared to other approaches based on the literature, against scenarios of irradiance variation, voltage sags, and frequency distortion. Simulation results in MATLAB/Simulink indicate high accuracy at low computational cost and complexity.

A comprehensive state-space model of two-stage grid-connected PV systems in transient network analysis

The large-scale deployment of distributed photovoltaic (PV) systems on the low voltage distribution network (LVDN) poses significant challenges to network operators related to the dynamic interactions of the PV systems and the network. To address these challenges and implement grid support services (GSS’s), accurate and efficient PV system models are required that allow large networks with integrated PV to be simulated in an economical time frame. For this purpose, an accurate, computationally inexpensive, linearised, state-space model of a two-stage PV system in the dq0 rotating reference frame is presented in this paper. The model includes both the DC/DC and DC/AC converters, all system controllers, parasitic components, system losses, and an efficient PV array model. The performance of the model is validated with measured experimental data from a power hardware in the loop (PHIL) testbed at various simulated step changes in irradiance. The developed model is applied to a modified radial European LVDN benchmark with multiple distributed PV systems to demonstrate some of the functions, applications and advantages. A combined active and reactive power voltage-dependent droop control characteristic for GSS’s is demonstrated with solar irradiation step changes and measured solar irradiation data applied to each PV system. A full electromagnetic transient (EMT) PV system model developed in MATLAB is presented and compared to the linear state-space (LSS) model. The results demonstrate a computational burden reduction of 116:1 without loss of accuracy providing significant benefits and functionality for the study of large-scale grid integration of PV systems.