Modeling and simulation of a grid-connected PV generation system for electromagnetic transient analysis

This paper addresses modeling and simulation of a grid-connected photovoltaic system (GCPS) to analyze its grid interface behavior and control performance in the system design. A simple circuit model of the solar array is used to easily simulate its inherent characteristics with the basic specification data. Detailed power and protection control of the GCPS as well as its electrical circuits have been represented by user-defined and built-in components to take into account transients in normal and fault conditions, which are dominated by its power electronic controller. The model has been described with the reference to and implemented in PSCAD/EMTDC, a power system transient software package. Extensive simulation results are presented and analyzed to validate that the proposed simulation model is effective for control and protection performance evaluation of the GCPS in terms of electromagnetic transient analysis.     

A sizing method for stand-alone PV installations with variable demand

The practical applicability of the considerations made in a previous paper to characterize energy balances in stand-alone photovoltaic systems (SAPV) is presented. Given that energy balances were characterized based on monthly estimations, the method is appropriate for sizing installations with variable monthly demands and variable monthly panel tilt (for seasonal estimations).The method presented is original in that it is the only method proposed for this type of demand. The method is based on the rational utilization of daily solar radiation distribution functions. When exact mathematical expressions are not available, approximate empirical expressions can be used. The more precise the statistical characterization of the solar radiation on the receiver module, the more precise the sizing method given that the characterization will solely depend on the distribution function of the daily global irradiation on the tilted surface H_gβi.This method, like previous ones, uses the concept of loss of load probability (LLP) as a parameter to characterize system design and includes information on the standard deviation of this parameter (σ_LLP) as well as two new parameters: annual number of system failures (f) and the standard deviation of annual number of system failures (σ_f).This paper therefore provides an analytical method for evaluating and sizing stand-alone PV systems with variable monthly demand and panel inclination. The sizing method has also been applied in a practical manner.     

Modeling and maximum power point tracking (MPPT) method for PV array under partial shade conditions

Influenced by partial shade, PV module aging or fault, there are multiple peaks on PV array's output power–voltage (P–V) characteristic curve. Conventional maximum power point tracking (MPPT) methods are effective for single peak P–V characteristic under uniform solar irradiation, but they may fail in global MPP tracking under multi-peak P–V characteristics. Existing methods in literature for this problem are still unsatisfactory in terms of effectiveness, complexity and speed. In this paper, we first analyze the mathematical model of PV array that is suitable for simulation of complex partial shade situation. Then an adaptive MPPT (AMPPT) method is proposed, which can find real global maximum power point (MPP) for different partial shade conditions. When output characteristic of PV array varies, AMPPT will adjust tracking strategies to search for global peak area (GPA). Then it is easy for conventional MPPT to track the global MPP in GPA. Simulation and experimental results verify that the proposed AMPPT method is able to find real global MPP accurately, quickly and smoothly for complex multi-peak P–V characteristics. Comparison analysis results demonstrate that AMPPT is more effective for most shade types.     

A fast and low cost analog maximum power point tracking method for low power photovoltaic systems

Low power photovoltaic (PV) systems are commonly used in stand-alone applications. For these systems, a simple and cost-effective maximum power point tracking (MPPT) solution is essential. In this paper, a fast and low cost analog MPPT method for low power PV systems is proposed. By using two voltage approximation lines (VALs) to approximate the maximum power point (MPP) locus, a low-complexity analog MPPT circuit can be developed. Theoretical derivation and detailed design procedure will be provided in this paper. The proposed method boasts the advantages such as simple structure, low cost, fast tracking speed and high tracking efficiency. To validate the correctness of the proposed method, simulation and experimental results of an 87 W PV system will also be provided to demonstrate the effectiveness of the proposed technique.     

Approaches for developing a sizing method for stand-alone PV systems with variable demand

Accurate sizing is one of the most important aspects to take into consideration when designing a stand-alone photovoltaic system (SAPV). Various methods, which differ in terms of their simplicity or reliability, have been developed for this purpose. Analytical methods, which seek functional relationships between variables of interest to the sizing problem, are one of these approaches.A series of rational considerations are presented in this paper with the aim of shedding light upon the basic principles and results of various sizing methods proposed by different authors. These considerations set the basis for a new analytical method that has been designed for systems with variable monthly energy demands.Following previous approaches, the method proposed is based on the concept of loss of load probability (LLP)—a parameter that is used to characterize system design. The method includes information on the standard deviation of loss of load probability (σ_LLP) and on two new parameters: annual number of system failures (f) and standard deviation of annual number of failures (σ_f).The method proves useful for sizing a PV system in a reliable manner and serves to explain the discrepancies found in the research on systems with LLP<10⁻². We demonstrate that reliability depends not only on the sizing variables and on the distribution function of solar radiation, but on the minimum value as well, which in a given location and with a monthly average clearness index, achieves total solar radiation on the receiver surface.     

An accurate method for the PV model identification based on a genetic algorithm and the interior-point method

Due to the PV module simulation requirements as well as recent applications of model-based controllers, the accurate photovoltaic (PV) model identification method is becoming essential to reduce the PV power losses effectively. The classical PV model identification methods use the manufacturers provided maximum power point (MPP) at the standard test condition (STC). However, the nominal operating cell temperature (NOCT) is the more practical condition and it is shown that the extracted model is not well suited to it. The proposed method in this paper estimates an accurate equivalent electrical circuit for the PV modules using both the STC and NOCT information provided by manufacturers. A multi-objective global optimization problem is formulated using only the main equation of the PV module at these two conditions that restrains the errors due to employing the experimental temperature coefficients. A novel combination of a genetic algorithm (GA) and the interior-point method (IPM) allows the proposed method to be fast and accurate regardless the PV technology. It is shown that the overall error, which is defined by the sum of the MPP errors of both the STC and the NOCT conditions, is improved by a factor between 5.1% and 31% depending on the PV technology.     

Application of a combined particle swarm optimization and perturb and observe method for MPPT in PV systems under partial shading conditions

This paper explains the development of a new algorithm for maximum power point tracking (MPPT) in large PV systems under partial shading conditions (PSC). The new algorithm combines the use of particle swarm optimization (PSO) for MPPT during the initial stages of tracking and then employs the traditional perturb and observe (PO) method at the final stages. The methodology has been first simulated in two different PV configurations under varying shading patterns and experimentally verified using a microcontroller based experimental system. The integration of swarm intelligence with PO algorithm is shown to yield faster convergence to the global maximum power point (GMPP) than when the two methods are individually used. The oscillations in the output power, voltage and current of the PV system with the proposed method are the least when compared to the ones obtained during PSO based MPPT.     

光照不均匀情况下光伏阵列最大功率跟踪控制

当光伏阵列受到不均匀光照时,输出的功率电压曲线含有多个局域峰值。针对此光照不均匀情况,建立光伏阵列多峰数学模型,并提出一种最大功率跟踪控制方法。采用连续函数构建光照不均匀情况下光伏阵列输出功率电压曲线;依次从该曲线的两侧或中部迭代搜索各局部最大功率点,确保在各种光照情况下均获得全局最大功率;通过Matlab仿真实例验证了所提多峰数学模型和最大功率跟踪控制方法的正确性。     

Optimal sizing of a grid-connected PV system for various PV module technologies and inclinations, inverter efficiency characteristics and locations

An optimal sizing methodology based on an energy approach is described and applied to grid-connected photovoltaic systems taking into account the photovoltaic module technology and inclination, the inverter type and the location. A model describing the efficiency for m-Si, p-Si, a-Si and CIS is used. The method has been applied on various meteorological stations in Bulgaria and Corsica (France). The main parameter affecting the sizing is the inverter efficiency curve. The influence of the PV module technology seems less important except for amorphous photovoltaic modules for which special remarks have been made. The inclination on the PV system influences the performances particularly when the inverter is undersized compared to the PV peak power.     

A novel maximum power point tracking in partially shaded PV systems using a hybrid method

To exploit photovoltaic systems, a major point that merits attention is to find maximum output power for the efficiency increase. The output power of solar cells depends on the ambient temperature and intensity of solar radiation. The cloud phenomenon creates a partially shaded on solar arrays; in this condition, the power–voltage curve of a solar array has several local maximum points. When there is uniform radiation, conventional methods of maximum power point tracking (MPPT) can be used. However, these methods are not efficient in partially shaded, due to the existence of several Maximum Power Points (MPPs) in the power-voltage characteristic. In this paper, a novel method for MPP tracking under the partially shaded is proposed, which is a combination of observational tracking and constant–voltage methods. When there is uniform radiation, the tracking operation is observed and tracked by a fuzzy logic–based approach. The proposed method is based on the existence of a relationship between radiation intensity and MPP voltage. In the existence of this relationship, the MPP voltage can be calculated by measuring the intensity of radiation at any moment. In addition, partially shaded works using the constant-voltage method. To verify the simulation results, laboratory implementation was performed. The results show that with considering the MPPs, the output power increases about 10% while the partially shaded is applied.     

Maximum power point traking controller for PV systems using neural networks

This paper presents a development and implementation of a PC-based maximum power point tracker (MPPT) for PV system using neural networks (NN). The system consists of a PV module via a MPPT supplying a dc motor that drives an air fan. The control algorithm is developed to use the artificial NN for detecting the optimal operating point under different operating conditions, then the control action gives the driving signals to the MPPT. A PC is used for data acquisition, running the control algorithm, data storage, as well as data display and analysis. The system has been implemented and tested under various operating conditions.The experimental results showed that the PV system with MPPT always tracks the peak power point of the PV module under various operating conditions. The MPPT transmits about 97% of the actual maximum power generated by the PV module. The MPPT not only increases the power from the PV module to the load, but also maintains longer operating periods for the PV system. The air velocity and the air mass flow rate of the mechanical load are increased considerably, due to the increase of the PV system power. It is also found that, the increase in the output energy due to using the MPPT is about 45.2% for a clear sunny day.     

Evaluation of a new maximum power point tracker (MPPT) applied to the photovoltaic stand-alone systems

In this paper a comparative study through experimental work between a new low-cost maximum power point tracker (MPPT) and the conventional configurations of the photovoltaic (PV) regulators under different atmospheric conditions is presented. The comparison is made by means of the energy production obtained by the PV generator of each system. From the results obtained it can be concluded that, depending on the charge state of the batteries, the MPPT can increase the overall efficiency of the system between 2.8% and 18.5% compared with the performance of a conventional system.     

Estimation of the maximum power and normal operating power of a photovoltaic module by neural networks

This paper presents an application of the neural networks for identification of the maximum power (MP) and the normal operating power (NOP) of a photovoltaic (PV) module. Two neural networks are developed; the first is the maximum power neural network (MPNN) and the second is the normal operating power neural network (NOPNN). The two neural networks receive the solar radiation and the PV module surface temperature as inputs, and estimate the MP and the NOP of a PV module as outputs. The training process for the two neural networks used a series of input/output data pairs. The training inputs are the solar radiation and the PV module surface temperature, while the outputs are the PV module MP for the MPNN and the PV module NOP for the NOPNN. The results showed that, the proposed neural networks introduced a good accurate prediction for the PV module MP and NOP compared with the measured values.     

New algorithm using only one variable measurement applied to a maximum power point tracker

A novel algorithm for seeking the maximum power point of a photovoltaic (PV) array for any temperature and solar irradiation level, needing only the PV current value, is proposed. Satisfactory theoretical and experimental results are presented and were obtained when the algorithm was included on a 100 W 24 V PV buck converter prototype, using an inexpensive microcontroller. The load of the system used was a battery and a resistance. The main advantage of this new maximum power point tracking (MPPT), when is compared with others, is that it only uses the measurement of the photovoltaic current, I_PV.     

Improved particle swarm optimization for photovoltaic system connected to the grid with low voltage ride through capability

Grid connected photovoltaic (PV) system encounters different types of abnormalities during grid faults; the grid side inverter is subjected to three serious problems which are excessive DC link voltage, high AC currents and loss of grid-voltage synchronization. This high DC link voltage may damage the inverter. Also, the voltage sags will force the PV system to be disconnected from the grid according to grid code. This paper presents a novel control strategy of the two-stage three-phase PV system to improve the Low-Voltage Ride-Through (LVRT) capability according to the grid connection requirement. The non-linear control technique using Improved Particle Swarm Optimization (IPSO) of a PV system connected to the grid through an isolated high frequency DC–DC full bridge converter and a three-phase three level neutral point clamped DC-AC converter (3LNPC²) with output power control under severe faults of grid voltage. The paper, also discusses the transient behavior and the performance limit for LVRT by using a DC-Chopper circuit. The model has been implemented in MATLAB/SIMULINK. The proposed control succeeded to track MPP, achieved LVRT requirements and improving the quality of DC link voltage. The paper shows superiority of IPSO than Incremental Conductance (IC) method during MPPT mode of PV system.     

Estimation of equivalent circuit parameters of PV module and its application to optimal operation of PV system

A method to estimate the equivalent circuit parameters of a PV (photovoltaic) module is presented. The parameters are calculated using a least-squares fitting of the equivalent model current–voltage characteristic with the measured one. For applications of the equivalent circuit model parameters, a quantitative diagnostic method of the PV modules by evaluating the parameters is introduced and examined by simulation. A new maximum peak power tracking (MPPT) method using the model parameters, a solar insolation, and a cell temperature is also shown. Its performance is compared with other MPPT control algorithms by simulations. The performance of the proposed method was better than other MPPT methods.     

A novel maximum power point tracking technique based on fuzzy logic for photovoltaic systems

Maximum power point tracking (MPPT) techniques are considered a crucial part in photovoltaic system design to maximise the output power of a photovoltaic array. Whilst several techniques have been designed, Perturb and Observe (P&O) is widely used for MPPT due to its low cost and simple implementation. Fuzzy logic (FL) is another common technique that achieves vastly improved performance for MPPT technique in terms of response speed and low fluctuation about the maximum power point. However, major issues of the conventional FL-MPPT are a drift problem associated with changing irradiance and complex implementation when compared with the P&O-MPPT. In this paper, a novel MPPT technique based on FL control and P&O algorithm is presented. The proposed method incorporates the advantages of the P&O-MPPT to account for slow and fast changes in solar irradiance and the reduced processing time for the FL-MPPT to address complex engineering problems when the membership functions are few. To evaluate the performance, the P&O-MPPT, FL-MPPT and the proposed method are simulated by a MATLAB-SIMULINK model for a grid-connected PV system. The EN 50530 standard test is used to calculate the efficiency of the proposed method under varying weather conditions. The simulation results demonstrate that the proposed technique accurately tracks the maximum power point and avoids the drift problem, whilst achieving efficiencies of greater than 99.6%.     

A comparison of the performance of different PV module types in temperate climates

The performances of five different types of photovoltaic modules have been measured for more than a year in the temperate climate of Perth, Western Australia. Perth averages over 5.4 peak sun hours (PSH) each day, from less than 3 in the winter months to over 8 at the height of summer. The average sun-up temperatures range between 16.5 °C and 28 °C. The types of modules examined in this study are: crystalline silicon (c-Si), laser grooved buried contact (LGBC) c-Si, polycrystalline silicon (p-Si), triple junction amorphous silicon (3j a-Si) and copper indium diselenide (CIS). Using a purpose built outdoor monitoring facility the energy production under actual operating conditions has been measured for each module. The annual and monthly performance ratios (PRs) have been calculated for the different modules and a comparison is presented here. The I–V characteristics and maximum power at standard test conditions have been measured for each module prior to, and at regular intervals, during outdoor exposure. These values are compared to the manufacturers’ values, and monitored over time for the modules operated in the field.     

Analysis and enhancement of PV efficiency with incremental conductance MPPT technique under non-linear loading conditions

This paper presents experimental evaluations for variation in the efficiency of energy extracted from a photovoltaic (PV) module (under non-linear loading) incorporated with an incremental conductance(IC) maximum power point tracking (MPPT) algorithm. The focus is on the evaluation of the PV panel under non-linear loading conditions using the experimental installation of a 100W_p photovoltaic array connected to a DC–DC converter and a KVA inverter feeding a non-linear load. Under the conditions of non-linear loading, both the simulation and experiment show that the MPPT technique fails to attain maximum power point due to the presence of ripples in the current leading eventually to a reduction in efficiency. In this paper, panel current is taken as a function of load impedance in the MPPT algorithm to eradicate power variation, as load impedance varies with supply voltage under non-linear conditions. The system is simulated for different non-linear loads using MATLAB-Simulink. A TMDSSOLAREXPKIT was used for MPPT control. In case 2, the inverter is connected to a single phase grid. When a voltage swell occurs in the grid, PV power drops. This power loss is reduced using the proposed MPPT method. The results of simulations and experimental measurements and cost efficiency calculations are presented.     

光伏电池单元最大功率点跟踪的直接检测法

最大功率点跟踪是提高光伏发电系统使用效率的有效途径之一,常用的跟踪方法都是根据电池输出的电压和电流值来寻求最大功率点的.文章提出了一种通过检测温度及光强的直接检测法,用求极值的方法直接得出光伏电池最大输出功率点及相应负载与温度和光照强度之间的数值关系,并与一组硅电池片参数进行了比较,其结果表明了该方法的可行性.