Showing papers on "Grid-connected photovoltaic power system published in 2019"

Accurate photovoltaic power forecasting models using deep LSTM-RNN

Abstract: Photovoltaic (PV) is one of the most promising renewable energy sources. To ensure secure operation and economic integration of PV in smart grids, accurate forecasting of PV power is an important issue. In this paper, we propose the use of long short-term memory recurrent neural network (LSTM-RNN) to accurately forecast the output power of PV systems. The LSTM networks can model the temporal changes in PV output power because of their recurrent architecture and memory units. The proposed method is evaluated using hourly datasets of different sites for a year. We compare the proposed method with three PV forecasting methods. The use of LSTM offers a further reduction in the forecasting error compared with the other methods. The proposed forecasting method can be a helpful tool for planning and controlling smart grids.

An Integrated Step-Up Inverter Without Transformer and Leakage Current for Grid-Connected Photovoltaic System

Abstract: In this paper, an integrated step-up inverter without transformer is investigated for photovoltaic (PV) power generation. The proposed topology can be derived by combining a traditional boost converter with a single-phase full bridge dc–ac converter. The main features of the integrated inverter are: First, the leakage current caused by the solar cell array-to-ground parasitic capacitance can be theoretically reduced to zero due to the characteristics of the converter configuration, which can improve the efficiency and the reliability of the PV generation system; second, the output ac voltage of the proposed inverter can be higher than the input dc voltage, which is capable of connecting low voltage PV panels to the grid; third, only five active switches are used in the presented inverter, and those switching devices can be synchronously driven by various sinusoidal pulsewidth modulation methods based on the carrier; therefore, the proposed inverter is compact and with curtailed cost. The working principle and analysis of the proposed integrated inverter are elaborated. Finally, simulation and experimental results are obtained in a lab prototype, which agree well with the theoretical analysis.

Adaptive Reactive Power Control of PV Power Plants for Improved Power Transfer Capability Under Ultra-Weak Grid Conditions

Abstract: This paper analyzes the power transfer limitation of the photovoltaic (PV) power plant under the ultra-weak grid condition, i.e., when the short-circuit ratio (SCR) is close to 1. It explicitly identifies that a minimum SCR of 2 is required for the PV power plant to deliver the rated active power when operating with the unity power factor. Then, considering the reactive power compensation from PV inverters, the minimum SCR in respect to power factor (PF) is derived, and the optimized coordination of the active and reactive power is exploited. It is revealed that the power transfer capability of PV power plant under the ultra-weak grid is significantly improved with the low PF operation. An adaptive reactive power droop control is next proposed to effectively distribute the reactive power demands to the individual inverters, and meanwhile, maximize the power transfer capacity of the PV power plant. Simulation results of a 200-MW PV power plant demonstrate that the proposed method can ensure the rated power transfer of PV power plant with the SCR of 1.25, provided that the PV inverters are operated with the minimal PF=0.9.

Techno-economic analysis of 1 MWp grid connected solar PV plant in Malaysia

Abstract: Most of the public and private technical universities in Malaysia have considerably abundant free areas, which could be a better place for equipping the renewable energy harvesters. The main object...

Intelligent hybrid power generation system using new hybrid fuzzy-neural for photovoltaic system and RBFNSM for wind turbine in the grid connected mode

Abstract: Photovoltaic (PV) generation is growing increasingly fast as a renewable energy source. Nevertheless, the drawback of the PV system is intermittent because of depending on weather conditions. Therefore, the wind power can be considered to assist for a stable and reliable output from the PV generation system for loads and improve the dynamic performance of the whole generation system in the grid connected mode. In this paper, a novel topology of an intelligent hybrid generation system with PV and wind turbine is presented. In order to capture the maximum power, a hybrid fuzzy-neural maximum power point tracking (MPPT) method is applied in the PV system. The average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison with the conventional methods. The pitch angle of the wind turbine is controlled by radial basis function network-sliding mode (RBFNSM). Different conditions are represented in simulation results that compare the real power values with those of the presented methods. The obtained results verify the effectiveness and superiority of the proposed method which has the advantages of robustness, fast response and good performance. Detailed mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have been proposed using Matlab/Simulink.

Fault Ride-Through Strategy for Two-Stage Grid-Connected Photovoltaic System Enabling Load Compensation Capabilities

Abstract: This paper proposes an extended Kalman filter (EKF) based control strategy for fault ride-through operation in two-stage grid-connected photovoltaic (GPV) system. Unlike the conventional controllers for ride-through operation, the proposed strategy does not compromise with power quality improvement features in the system while enabling ride-through operation. The controller accounts for nonlinear loads in the system, grid harmonic-currents elimination, and grid-currents balancing even during the harmonic/distorted grid voltages. The IEEE Standard-1547.4 compels the distributed resource to ride-through during voltage disturbances caused by faults. For the ride-through operation, a limit is imposed on PV active power injection to prevent inverter overcurrents and dc-link energy aggregation, which reduces the lifetime of dc-link capacitor. The reactive power is fed to the grid, as per the depth in voltage-sag. The derated PV array power is supplied in cases where the inverter cannot handle the utmost PV-power. The power quality improvement is ensured using EKF state estimator, which precisely estimates the fundamental load currents. In distribution network with modern nonlinear loads, especially at far radial ends, the grid voltages are prone to huge diversions and the proposed controller provides a possible solution to maintain active/reactive power support and maintain power quality in the network. The effectiveness of the strategy is demonstrated through simulations and experiments. Under all disturbances, the harmonic content in grid currents is observed within limits, in accordance with the IEEE Standard-519.

Comparative analysis of MPPT algorithms bio-inspired by grey wolves employing a feed-forward control loop in a three-phase grid-connected photovoltaic system

Abstract: It is well-known that performance of photovoltaic (PV) systems can be severely deteriorated when PV arrays are subjected to partial shading conditions, once the traditional techniques used for maximum power point tracking (MPPT) could not operate in the global maximum power point (GMPP). Thus, to overcome this problem and achieve the GMPP, four MPPT techniques bio-inspired in the grey wolf optimisation (GWO) are presented. These MPPT techniques, which are named as GWO, GWO-Beta, GWO-IC (Incremental Conductance), and GWO-P&O (Perturb and Observe), are evaluated and compared to each other by employing a double-stage three-phase grid-connected PV system, which is composed of DC/DC converter and three-phase inverter. Commonly, the DC-bus voltage regulation of double-stage PV systems presents slow dynamic behaviour to avoid disturbances in the currents injected into the grid. As a result, MPPT algorithms suffer with this problem since they must be executed considering this condition. To overcome this problem, a feed-forward control loop (FFCL) is implemented to improve the DC-bus voltage regulation during abrupt solar irradiance changes, as well as accelerating the MPPT algorithms dynamics. By means of extensive experimental and simulation results, the performance and effectiveness of the four MPPT techniques, as well as the FFCL, are evaluated.

Control of asymmetrical cascaded multilevel inverter for a grid-connected photovoltaic system

Abstract: This article presents a generalised asymmetrical cascaded multilevel inverter (MLI) for a single-phase grid-connected photovoltaic (PV) system and their control strategy. The control strategy, including maximum power tracking along with a suitable interface, is implemented for maximum power transfer from the PV source to the single-phase low-power grid. The balancing of DC-link voltages for an asymmetrical MLI under variable solar parameters as well as grid parameter variation is implemented using the proposed control strategy. The voltage controllers maintain the constant DC-link voltage ratio, whereas the current controller injects the sinusoidal current into the grid at unity power factor and track the grid voltage under variation of grid voltage using grid tracker. Stability analysis of the proposed grid-connected asymmetrical inverter system is also incorporated. The whole grid-tied PV system is simulated in the MATLAB/SIMULINK environment and the exhaustive simulation results of the system under different transient conditions are presented. In addition, a laboratory prototype for a low-power grid-tied PV system has been developed and implemented using DS1103. The performance of the system is also tested at varying irradiance conditions and the corresponding experimental results are also presented.

A Fast Fault Identification in a Grid-Connected Photovoltaic System Using Wavelet Multi-Resolution Singular Spectrum Entropy and Support Vector Machine

Abstract: A new protection scheme based on applying a combination of wavelet multi-resolution singular spectrum entropy and support vector machine is proposed to identify different types of grid faults in a three-phase grid-tied photovoltaic system. In this technique, discrete wavelet transform with multi-resolution singular spectrum entropy is utilized to extract the unique features of three-phase voltage signals at the point of common coupling. The three-phase voltage signals are decomposed to provide detail and approximation coefficients of wavelet transform. Then, various features between different types of grid faults can be extracted by a combination of multi resolution analysis and spectrum analysis with entropy as the output. The constructed features vector is utilized as input data of a support vector machine classifier to identify and classify various types of faults. The results illustrate that the proposed intelligent technique not only recognizes different types of grid faults correctly, but also performs quickly in identifying grid faults in a grid-connected photovoltaic system. Apart from this, a graphical investigation is executed to observe the effects of different types of grid faults in photovoltaic (PV) operation which highlight the necessity of intelligent protection methods to protect PV systems.

Direct Model Predictive Control of Novel H-Bridge Multilevel Inverter Based Grid-Connected Photovoltaic System

Abstract: In this paper, a direct model predictive control (DMPC) for the novel H-Bridge multilevel inverter topology-based grid-connected photovoltaic system (GCPS) is presented. The DMPC has several advantages over the conventional control techniques, including optimality, ability to handle multiple control goals, and direct manipulation of semiconductor switches instead of the modulator. The main control goals in the GCPS are to extract the maximum energy from the photovoltaic (PV) system and inject the current into the grid with minimum total harmonic distortion (THD) or close to unity power factor. The DMPC performs well in terms of these control goals. The entire GCPS with the proposed controller is simulated in Simulink MATLAB and the results are compared with the existing GCPSs in the literature. The usage of less number of semiconductor switches while keeping the same number of output voltage levels made the proposed GCPS efficient, less costly, and simpler in design. Moreover, its voltage and current THD are comparable with the systems existing in the literature.

Modeling and Design of the Vector Control for a Three-Phase Single-Stage Grid-Connected PV System with LVRT Capability according to the Spanish Grid Code

Abstract: This article deals with the vector control in dq axes of a three-phase grid-connected photovoltaic system with single-stage topology and low-voltage-ride-through capability. The photovoltaic generator is built using an array of several series-parallel Suntech PV modules and is modeled as a Lookup Table (two-dimensional; 2-D). The requirements adopted when grid voltage sags occur are based in both the IEC 61400-21 European normative and the allowed amount of reactive power to be delivered according to the Spanish grid code, which avoids the disconnection of the inverter under grid faults by a limitation in the magnitude of the three-phase output inverter currents. For this, the calculation of the positive- and negative-sequences of the grid voltages is made and a conventional three-phase Phase-Locked Loop is used for the inverter-grid synchronization, allowing the control of the active and reactive powers solely with the dq components of the inverter currents. A detailed enhanced flowchart of the control algorithm with low-voltage-ride-through capability is presented and several simulations and experiments using Matlab/SIMULINK and the Controller Hardware-in-the-Loop simulation technique, respectively, are run for several types of one- and three-phase voltage sags in order to validate its behavior.

Stability improvement and control of grid-connected photovoltaic system during faults using supercapacitor

Abstract: This paper describes the stability improvement of grid-connected photovoltaic (PV) system using supercapacitor (SC). The proposed technique is applied on PV system which using maximum power point tracking of perturbation and observation (P&O) algorithm. The P&O algorithm is used to extract the maximum power from the studied PV system. The effect of SC as a type of storage device on PV system appears at the abnormal conditions of grid faults. This technique is used to compensate the system parameters at different fault conditions. The control strategy of SC technique is developed for continuously charging and discharging to achieve its objective. In addition, the control system is presented in order to maintain the DC link voltage and to manage the power transit between the SC and the grid. The whole grid-connected PV system with SC energy storage system (ESS) is modeled and simulated using MATLAB/SIMULINK software and also the control system strategies are demonstrated. The effects of different fault conditions on the behaviors of studied grid-connected PV system with the SC ESS technique are investigated. A comparison between the behaviors of studied PV system in cases of without SC and with SC technique is studied. Also, the variations of DC voltage, active power, and reactive power for the studied PV system equipped without and with SC technique are investigated. The simulation results present a clear improvement for the system stability in case of using SC. Numerical results illustrate the validity of proposed technique with satisfactory values.

Grid Connected-Photovoltaic System (GC-PVS): Issues and Challenges

Abstract: Smart grid is the key technology for an effective utilization of the Renewable Energy Sources (RES). The utilization of RES for the generation of electricity is increasingly gaining interest of researchers during the last decades. The main reason behind this is global incentivization, the increasing price of petroleum products, climate issues and deregulations in the energy market. As the Government of India, (MNRE i.e. Ministry of New & Renewable Energy) is targeting to generate 20000 MW power through grid-connected solar PVS by the year 2022 therefore, the main focus in this paper has been presented on power generation through grid-connected PVS. The emerging smart grid technology has enabled the grid-connected PVS as an evolving process in today's world for electrical power generation. However, apart from so many advantages, there are several issues and challenges associated with the integration of PVS to the electric utility grid hence, the investigation to find out available possible solutions to overcome these issues becomes essential in order to enhance the performance of grid-connected PVS. The most severe constraint associated with this emerging technology is it high penetration level. If during low load conditions there is some mismatch found between the real power output and the load profile characteristics of PVS then it may result into large reverse power flow, high power losses or severe voltage violation. In this paper, several issues and challenges associated with the integration of solar PVS with the electric utility grid are presented.

Machine Learning Based Islanding Detection for Grid Connected Photovoltaic System

Abstract: This paper focus on developing a new islanding detection method with the help of machine learning and signal processing technique. The islanding detection method make sure that there is a proper remote monitoring of the grid integrated photovoltaic (PV) system. In case of grid fault or maintained of the grid, a proper informed signal is provided to various distributed generation (DG) networks so that they can disconnect with the grid and operate in isolated mode. A simulation of 1kW grid connected PV system is performed. The signal such as voltage, current and frequency are recorded at point of common coupling (PCC). The feature of recorded signals are extracted using wavelet transformation. The extracted features are used to form a islanding scenarios matrix. The matrix is further utilized to train a classifier using machine learning algorithm. From the result it can be observed that the trained classifier depicted 97.9% training accuracy with a training time of 16.9 sec which is better when compared with the literature. Further the trained classifier is subjected to test with an unknown islanding condition to observe the robustness of the classifier.

An Efficient Islanding Classification Technique for Single Phase Grid Connected Photovoltaic System

Abstract: Integration of renewable energy systems into low voltage buses leads to complexity for protection systems and unplanned islanding. Therefore, a need to reconfigure the typical protection configurations arises. In this paper an efficient islanding classification technique is developed to provide remote monitoring and operation of grid connected distributed generation systems. A simulation is developed by considering a 1kW grid connected photovoltaic system. The voltage and current measurements at the point of common coupling act as a main source of data for developing the classification algorithm. Wavelet transform is utilised for extracting features and creating a feature matrix for all possible scenarios of islanding. The feature matrix is subjected to machine learning approach for creating a trained data set which helps in classifying the islanding scenario. The results depicted 100% training and 97%testing efficiency under 0.2 seconds which is better when compared with the conventional methods and literature.

Design and Performance Analysis of 250 kW Grid-Connected Photovoltaic System in Iraqi Environment Using PVsyst Software

Abstract: A 250 kW grid-connected photovoltaic (PV) plant systems have been installed at the Ministry of Electricity in Baghdad and penetrated to the Iraqi national grid since November 2017. This is the first high power grid-connected PV system that has been installed in Iraq and it’s one of the four parts 1MW large-scale PV systems that should be completed in early of 2019. This paper presents the design and performance analysis of this system using a PVsyst software package. The performance ratio and different losses that occurred in the system are also calculated. The results show that the performance ratio is 75% using 1428 photovoltaic panels type (Sharp 175Wp) spread over an area of 1858 m². The total energy injected into the grid is (346692 kWh/year) .Based on the simulation results that developed in this paper, the practical PV grid-tied system has been implemented in Baghdad site.

Particle Swarm Optimization based Adaptive Neuro-Fuzzy Inference System for MPPT Control of a Three-Phase Grid-Connected Photovoltaic System

Abstract: This paper presents the analysis and operation of a grid connected photovoltaic (PV)energy conversion system with an Adaptive Neuro-Fuzzy Inference System (ANFIS)based maximum power point tracking (MPPT)algorithm. Particle swarm optimization is used to train the membership functions while the least squares algorithm is used to update the consequent parameters of the ANFIS with changing operating condition of PV solar system. The MPPT algorithm maximizes conversion efficiency by adjusting the duty cycle of the buck boost converter to change the output voltage of the solar panel and hence achieving the maximum panel output power for a given set of environmental conditions. The ANFIS is trained by using a hybrid algorithm implementing least squares estimator and particle swarm optimization with data obtained by operating the system using the Perturb and Observe (P&O)MPPT algorithm. The performance of the proposed ANFIS based MPPT algorithm is validated in simulation using MATLAB/Simulink at different operating conditions. It is proven that the designed ANFIS based MPPT scheme achieves a very fast response with little oscillations while transferring maximum power from solar panel to the grid line as compared to the conventional P&O based MPPT scheme.

Analysis of self-consumption of energy from grid-connected photovoltaic system for various load scenarios with short-term buffering

Abstract: Energy from photovoltaics (PV) is becoming an important contributor to the energy mix for many countries. However, its impact on the distribution network is troublesome due the uncontrollable bidirectional transfers and might lead to the reduction in various forms of support for development of distributed PV systems in the future. This could be avoided by shifting from selling to self-consumption of PV energy, so the owner of PV would benefit mostly from reductions in energy purchase. This would also reduce overall power demand and transfer losses in the energy network, for the benefit of the climate. In order to achieve this goal, the PV system must be carefully adjusted to the local consumption profile and annual energy demand. The paper investigates the adjustment opportunities for the PV system with various local consumption scenarios and optional short-term energy buffering, with view of lowering the interaction with the utility grid. The simulation takes into account full-year period and gives guidelines for PV and battery sizing, presented for systems of any size.

Intelligent controller based power quality improvement of microgrid integration of photovoltaic power system using new cascade multilevel inverter

Abstract: Now a day the power demand has a major problem for developing countries due to the growth of population, industries, IT companies and other needs. In this present situation the fossil fuel-based power generation alone does not support the consumer needs, poor power quality due to nonlinear function and very harmful for environment. The main objective of this paper is improving the power quality of grid connected photovoltaic power system through a new cascade H-bridge multilevel inverter. The proposed research work has been modelled and controlled by ANFIS intelligence in MATLAB simulation environment. The simulation results are analysed under various operating conditions for improve the performance of proposed system. Finally, the proposed system THD value of simulation results is compared with IEEE 1547 standard for prove the effectiveness of proposed research work.

Optimization of the fuzzy MPPT controller by GA for the single-phase grid-connected photovoltaic system controlled by sliding mode

Abstract: This paper focuses on the performance of a single-phase inverter coupled to the grid in terms of optimal photovoltaic transfer, using the concept of sliding-mode variable structure systems. Moreover, a fuzzy logic control technique optimized by genetic algorithm (GA) associated with a boost converter is used to extract the Maximum Power Point Tracking (MPPT).The validation of the results using Matlab/Simulink software is carried under different environmental and operating conditions to verify the satisfactory performance of the proposed control strategies.The original version of this article supplied to AIP Publishing contained an error in the author’s name. The name originally appeared as, Layachi Zaghba, but the correct name is Zaghba Layachi. An updated version of this article, with the author’s name corrected, was published on January 23, 2020.

Hardware Approach to Mitigate the Effects of Module Mismatch in a Grid-connected Photovoltaic System: A Review

Abstract: This study reviews the hardware approach to mitigate the effects of module mismatch in a grid-connected photovoltaic (PV) system. Unlike software solutions, i.e. the maximum power tracking algorithm, hardware techniques are well suited to enhance energy yield because of their inherent ability to extract energy from the mismatched module. Despite the extra cost of the additional circuitry, hardware techniques have recently gained popularity because of their long-term financial benefits. Notwithstanding the growing interest in this topic, review papers that provide updates on the technological developments of the three main hardware solutions, namely micro inverter, DC power optimizer, and energy recovery circuits, are lacking. This is in contrast to software solutions, which have had a considerable number of reputable reviews. Thus, a comprehensive review paper is appropriate at this juncture to provide up-to-date information on the latest topologies, highlight their merits/drawbacks, and evaluate their comparative performance.

Backstepping based power control of a three-phase Single-stage Grid-connected PV system

Abstract: In order to reduce costs while maintaining superior performance, this paper presents a new control methodology of a three-phase grid connected photovoltaic system without using the intermediary DC/DC converter. Based on the synchronized nonlinear model of the whole photovoltaic system, two controllers have been proposed for the three-phase inverter in order to ensure the operation of the PV system at the maximum power point with unity power factor and minimum grid disturbance. Grid synchronization has been ensured by a three-phase 2 nd order PLL (Phase-Locked Loop). The stability of each controller is demonstrated by means of Lyapunov analysis and evaluated under changing atmospheric conditions using the Matlab/Simulink environment, the simulation results clearly demonstrate the performance provided by each controller.

Experimental Realization for P&O Maximum Power Point Tracking Applied for Single-Stage Three-Phase Grid-Connected Photovoltaic System

Abstract: This paper offerings the implementation of three-phase single-stage grid-connected photovoltaic (PV) scheme via the perturb and observe (P&O) maximum power point tracking (MPPT) procedure. The proposed technique has several benefits such as high efficiency, simple topology, and the isolation vagaries can be tracking in fast smoothly outwardly of fluctuation. MPPT is implemented experimentally to approve the theoretical results to obtain maximum power from solar array. The construction of the mathematical system was performing through Matlab/Simulink environment. dSPACE MicroLabBox was used to verification the experimental work. The resulting was examined in simulation testing and experimental verifications, the proposed MPPT technique demonstrations satisfactory performance with high efficiency in application of single-stage grid connection of three-phase PV system.

Parallel Operation of Current-Source Inverter for Low-Voltage High-Current Grid-Connected Photovoltaic System

Abstract: Solar energy is very potential to be developed in a tropical country such as in Indonesia. This energy source is eco-friendly because it can eliminate air pollution such as caused by conventional fossil fuels. This research article presents analysis results of a novel grid-connected photovoltaic system using low-voltage high-current system. The electrical energy produced by the photovoltaic system was sent into the electrical power grid using two or more H-bridge current source inverters operated in parallel. The proposed system is very suitable for large size photovoltaic system because of its some merits. The inverter circuits work generating sinusoidal output currents and controlling the power delivered into the grid. The test results of the new system showed that the system worked properly as interface between photovoltaic system and the electrical grid delivering high ac current with low harmonic distortion.

Economic Analysis of Residential Grid-connected Photovoltaic System with Lithium-ion Battery Storage

Abstract: Residential roof-mounted photovoltaic (PV) system paired with battery storage systems can minimize dependence on grid electricity and reduce electricity bill. Moreover, the economic viability of such systems is subject to the efficient utilization of excess electricity generated, most often with the aid of net metering. In recent time, energy storage market is exponentially growing and batteries are being installed in a grid-connected household to maximize the use of on-site electricity generated by PV. Nevertheless, batteries have not yet reached economic profitability in most grid-connected scenarios. Moreover, the economic and technical viability of such systems is still under discussion. This work, therefore, presents the optimization results of residential grid-connected PV system paired with a lithium-ion battery (LiB) of a household located in Yobe, Nigeria. The model is implemented in Matlab environment. The model takes into account both technical and economic parameters, such as battery state of health and state of charge over a period of time, storage investment cost, and electricity price. Moreover, the power flow paths at different interval of time are demonstrated and the result of the sensitivity analysis in term of return on investment (ROI) is presented. The results obtained shows that the ROI dependent on so many factors such as electricity price and energy storage system price. We also identify that PV system with LiB if installed; the household electricity bill will result in an earnings of €2943 because of the less energy consumption from the grid of about 45.7% less as compared with the case without LiB.

Analysis of an energy storage sizing for grid-connected photovoltaic system

Abstract: This paper present on the analysis of an energy storage sizing for a small grid-connected PV system. This project is to study the proper sizing of energy storage (battery) in a grid-connected PV system for consumers whom purchase and sell electricity from and to the utility grid. The goal is to minimize the total cost of the operation for a consumer with a PV system with a battery storage system. This is to make sure that minimizing the total annual operating cost while maintaining an efficient system. This study uses typical consumer load consumption, and solar irradiance data throughout a year, while varying the type of battery storage (study lead acid and Lithium ion battery) as an energy storage for a similar system. Since lithium ion is not the main options to be integrated with PV system, this study will then reveal the data in terms of cost on why it is not a popular choice.

Study on a Simplified Structure of a Two-Stage Grid-Connected Photovoltaic System for Parameter Design Optimization

Abstract: Conventional parameter designs of two-stage grid-connected photovoltaic (PV) system relied on its mathematical model of the cascade structure (CS), but the procedure is excessively cumbersome to implement. Besides, for a two-stage converter system, the coupling interaction between the power converters can directly lead to a poor parameter design. To overcome this drawback, this paper uses a simplified structure (SS) of single-phase two-stage grid-connected PV system to better design the parameters of the front-stage dc-dc converter. After establishing the small-signal model for SS and CS in the PV system, the relative eigenvalue sensitivity is used as the criterion for judging the influence of some parameters on the stability of the two structures. The stable boundary of MPPT control parameters is compared and discussed in SS and CS, respectively. In addition, the relationship between the front-stage dc-dc converter and the rear-stage dc-ac inverter is analyzed by the modal participation factor calculated in CS. An experiment is also performed at the end of this paper to further verify the feasibility of using SS to design the parameters of the dc-dc converter in the PV system.