Junction Surface Recombination Concept as Applied to Silicon Solar Cell Maximum Power Point Determination Using Matlab/Simulink: Effect of Temperature

In this work, we study the method for determining the maximum of the minority carrier recombination velocity at the junction Sfmax, corresponding to the maximum power delivered by the photovoltaic generator. For this, we study the temperature influence on the behavior of the front white biased solar cell in steady state. By solving the continuity equation of excess minority carrier in the base, we have established the expressions of the photocurrent density, the recombination velocity on the back side of the base Sb, and the photovoltage. The photocurrent density and the photovoltage are plotted as a function of Sf, called, minority carrier recombination velocity at the junction surface, for different temperature values. The illuminated I-V characteristic curves of the solar cell are then derived. To better characterize the solar cell, we study the electrical power delivered by the base of the solar cell to the external charge circuit as either junction surface recombination velocity or photovoltage dependent. From the output power versus junction surface recombination velocity Sf, we have deduced an eigenvalue equation depending on junction recombination velocity. This equation allows to obtain the maximum junction recombination velocity Sfmax corresponding to the maximum power delivered by the photovoltaic generator, throughout simulink model. Finally, we deduce the conversion efficiency of the solar cell.

Irradiation Energy Effect on a Silicon Solar Cell: Maximum Power Point Determination

The aim of this study is to determinate the electrical parameters of a white biased silicon solar cell submitted to an irradiation energy of particles (protons, helium, electrons and heavy ions). A theoretical study of the influence of irradiation energy on the photocurrent density, the photovoltage, the maximum power, as well as the maximum efficiency of the solar cell is presented through a resolution of the continuity equation relative to excess minority carrier. Then the expressions of the photocurrent density Jph, the photovoltage Vph, and the excess minority carrier recombination velocity at the back side Sb are established dependent of irradiation parameters ∅p, Kl respectively irradiation flux and intensity. In this work, we propose a method for determining the recombination velocity of the excess minority carrier at the junction Sfmax corresponding to the maximum power point delivered by the photovoltaic generator under the influence of the irradiation. It is then obtained by calculating the derivative of the power with respect to the excess minority carrier recombination velocity Sf at the junction emitter-base. A transcendental equation solution is deduced as eigenvalue, leading to the junction recombination velocity of excess minority carrier and also yields the solar cell maximum conversion efficiency.

Maximum Power Point Tracking With Fractional Order High Pass Filter for Proton Exchange Membrane Fuel Cell

Proton exchange membrane fuel cell (PEMFC) is widely recognized as a potentially renewable and green energy source based on hydrogen. Maximum power point tracking (MPPT) is one of the most important working conditions to be considered. In order to improve the performance such as convergence and robustness under disturbance and uncertainty, a fractional order high pass filter (FOHPF) is applied for the MPPT controller design based on the traditional extremum seeking control (ESC). The controller is designed with integerorder integrator (IO-I) and low pass filter (IO-LPF) together with fractional order high pass filter (FOHPF), by substituting the normal HPF in the original ESC system. With this FOHPF ESC, better convergence and smoother performance are achieved while maintaining the robust specifications. First, tracking stability is discussed under the commensurate-order condition. Then, simulation results are included to validate the proposed new FOHPF ESC scheme under disturbance. Finally, comparison results between FOHPF ESC and the traditional ESC method are also provided. © 2014 Chinese Association of Automation.

Comparative assessment of maximum power point tracking procedures for photovoltaic systems

The fast growing demands and increasing awareness for the environment, PV systems are being rapidly installed for numerous applications.However, one of the important challenges in utilizing a PV source is the maximum power harnessing using various maximum power point tracking techniques available. With the large number of MPPT techniques, each having some merits and demerits, confusion is always there for their proper selection. Discussion on various proposed procedures for maximum power point tracking of photovoltaic array has been done. Based on different parameters analysis of MPPT techniques is carried out. This assessment will serve as a suitable reference for selection, understanding different ways and means of MPPT.

Modeling and control of a small solar fuel cell hybrid energy system

This paper describes a solar photovoltaic fuel cell (PVEC) hybrid generation system consisting of a photovoltaic (PV) generator, a proton exchange membrane fuel cell (PEMFC), an electrolyser, a supercapacitor, a storage gas tank and power conditioning unit (PCU). The load is supplied from the PV generator with a fuel cell working in parallel. Excess PV energy when available is converted to hydrogen using an electrolyser for later use in the fuel cell. The individual mathematical model for each component is presented. Control strategy for the system is described. MATLAB/Simulink is used for the simulation of this highly nonlinear hybrid energy system. The simulation results are shown in the paper.

Optimization of Electrics Parameters CdS/CdTe Thin Film Solar Cell Using Dielectric Model

Abstract *Corresponding author. In this paper, the electrical properties of heterojunction solar cells thin film n-CdS/p-CdTe from dielectric model have been studied. Based on the expression of the minority, carriers density in the p-CdTe base of solar cell, the photocurrent density and that of the photo voltage are determined according to the cell dimensions, doping levels, the absorption coefficient, the solar irradiance and the temperature, etc. Fitting using Mathcad and Origin Lab software on the photocurrent and the photovoltage of the n-CdS/p-CdTe enabled to determine the series, shunt resistance and the maximum power point. The results obtained, in good agreement with experimental results, allow operating simulations for optimizing maximum outputs parameters (Ip, Vp). Thereafter, it is proposed a type of photovoltaic generator module with a good command of the design parameters for better efficiency.

Design of a Level-3 electric vehicle charging station using a 1-MW solar system via the distributed maximum power point tracking technique

Solar power is mostly influenced by solar irradiation,weather conditions,solar array mismatches and partial shading conditions.Therefore,before installing solar arrays,it is necessary to simulate and determine the possible power generated.Maximum power point tracking is needed in order to make sure that,at any time,the maximum power will be extracted from the photovoltaic system.However,maximum power point tracking is not a suitable solution for mismatches and partial shading conditions.To overcome the drawbacks of maximum power point tracking due to mismatches and shadows,distributed maximum power point tracking is util-ized in this paper.The solar farm can be distributed in different ways,including one DC-DC converter per group of modules or per module.In this paper,distributed maximum power point tracking per module is implemented,which has the highest efficiency.This technology is applied to electric vehicles(EVs)that can be charged with a Level 3 charging station in<1 hour.However,the problem is that charging an EV in<1 hour puts a lot of stress on the power grid,and there is not always enough peak power reserve in the existing power grid to charge EVs at that rate.Therefore,a Level 3(fast DC)EV charging station using a solar farm by implementing distributed maximum power point tracking is utilized to address this issue.Finally,the simulation result is reported using MATLAB®,LTSPICE and the System Advisor Model.Simulation results show that the proposed 1-MW solar system will provide 5 MWh of power each day,which is enough to fully charge~120 EVs each day.Additionally,the use of the proposed photovoltaic system benefits the environment by removing a huge amount of greenhouse gases and hazardous pollutants.For example,instead of supplying EVs with power from coal-fired power plants,1989 pounds of CO_(2) will be eliminated from the air per hour.

Artificial Neural Network Maximum Power Point Tracker for Solar Electric Vehicle

This paper proposes an artificial neural network maximum power point tracker (MPPT) for solar electric vehicles. The MPPT is based on a highly efficient boost converter with insulated gate bipolar transis- tor (IGBT) power switch. The reference voltage for MPPT is obtained by artificial neural network (ANN) with gradient descent momentum algorithm. The tracking algorithm changes the duty-cycle of the converter so that the PV-module voltage equals the voltage corresponding to the MPPT at any given insolation, tempera- ture, and load conditions. For fast response, the system is implemented using digital signal processor (DSP). The overall system stability is improved by including a proportional-integral-derivative (PID) controller, which is also used to match the reference and battery voltage levels. The controller, based on the information sup- plied by the ANN, generates the boost converter duty-cycle. The energy obtained is used to charge the lith- ium ion battery stack for the solar vehicle. The experimental and simulation results show that the proposed scheme is highly efficient.

Assessment of high-gain quadratic boost converter with hybrid-based maximum power point tracking technique for solar photovoltaic systems

Solar photovoltaic(SPV)modules have a low output voltage and are load-dependent.Therefore,it is critical that the SPV system has an adequate DC-DC converter to regulate and improve the output voltage to get maximum output voltage.To meet load requirements,the voltage must be increased,necessitating the use of energy-efficient power electronic converters.The performance of an SPV system coupled to a high-gain quadratic boost converter(HG-QBC)with a load is investigated in this paper.The suggested HG-QBC for the SPV system at a lower value of duty ratio provides high voltage gain with a boost factor of four times.An analytical comparison is carried out with the various existing boost converters in terms of the components and the boost factor.The issue of locating the maximum power generation point from the SPV system is crucial.As a result,choosing an appropriate maximum power point tracker(MPPT)-based technique to obtain the peak power output of the SPV system under the rapidly varying atmospheric conditions is vital.To determine the highest output power of an SPV system,a hybrid-based MPPT with a neural network assisted by a perturb and observe(P&O)technique is proposed.For the HG-QBC,a comparison of the proposed MPPT with a traditional P&O-based MPPT is illustrated.The comparative analysis takes into account rise time,settling time and voltage ripples.The output voltage and power characteristics of the proposed model are analysed under constant and varying irradiation conditions using MATLAB®/Simulink®.The results of a hybrid-based MPPT show that the oscillations are minimum at the maximum power point with fewer ripples of 0.20%and a settling time of 1.2 s in comparison with the other two techniques.

Comparison between SiC- and Si-Based Inverters for Photovoltaic Power Generation Systems

100-W class power storage systems were developed, which comprised spherical Si solar cells, a maximum power point tracking charge control-ler, a lithium-ion battery, and one of two different types of direct current (DC)-alter- nating current (AC) converters. One inverter used SiC met-al-oxide-semicon-ductor field-effect transistors (MOSFETs) as switching devices while the other used Si MOSFETs. In these 100-W class inverters, the ON resistance was considered to have little influence on the efficiency. Nevertheless, the SiC-based inverter exhibited an approximately 3% higher DC-AC conversion efficiency than the Si-based inverter. Power loss analysis indicated that the higher efficiency resulted predominantly from lower switching and reverse recovery losses in the SiC MOSFETs compared with in the Si MOSFETs.

Experimental Analysis to Extract the Maximum Output of Serial and Parallel PV Module Configurations under Partial Shadow Conditions: A Case Study for Bambey, Senegal

Using an experimental setup, the series configurations (SC) and the parallel configurations (PC) of the PV cell connection are studied to compare their performance under the condition of partial shading s. The performance of the configurations is evaluated by comparing the open-circuit voltage, the short-circuit current, the maximum power point (MPP), the voltage and current corresponding to MPP, and the Fill Factor (FF). The variations of the series resistance and the shunt resistance of a PV module under different irradiance levels are also determined by considering the effect of thermal voltage. Finally, a comparison between the performance losses in the different configurations is presented. The results of this study show that the parallel configuration has the best performance under the conditions of partial shade in the context of this work.

基于SSA-ELM神经网络控制器的光伏MPPT方法

光伏电池板所处环境的非线性变化使得光伏电池的功率保持在最大功率点(maximum power point,MPP)非常困难。传统的最大功率点跟踪(maximum power point tracking,MPPT)方法普遍存在技术缺陷,无法满足当前需求。针对光伏发电MPPT问题,该文提出了一种基于麻雀搜索算法优化的极限学习机(sparrow search algorithm-extreme learning machine,SSA-ELM)神经网络控制器的MPPT方法。与传统技术相比,该MPPT方法在稳定性、速度、超调和MPP的振荡等方面的效果均较好。使用MATLAB/Simulink平台进行仿真实验,验证了所提控制策略及理论分析的正确性。

Photovoltaic Powered Reverse Osmosis Plant for Brackish Water without Batteries with Self Acting Pressure Valve and MPPT

This paper presents a PV （photovoltaic） powered RO （reverse osmosis） plant for brackish water without batteries and a self-regulating pressure valve. The aim is to extract the maximum power from the PV module using an MPPT （maximum power point tracking） technique for powering a solar water pump and maintain constant the pressure in the RO membranes by using the self-operated valve. A Buck type converter using the InCond （incremental conductance） MPPT was developed for this application. The MPPT chosen was simulated, tested and validated, showing an efficiency of 86.8%. The technical feasibility of the RO plant was made by PLC （programmable logic controller） and was tested for two salinity levels （1,000 and 1,500 mg/L of TDS （total dissolved solids））. These salinity levels chosen are commonly found in most brackish water wells of the semi-arid region of Northeastern Brazil. The RO plant could permeate 175.3 L/day of drinking water with 120 mg/L of TDS and specific energy consumption of 2.56 kWh/m3.

基于萤火虫优化模糊P&O的微生物燃料电池最大功率点跟踪

针对微生物燃料电池产电量低、输出不稳定等问题,提出一种混合萤火虫优化和模糊改进扰动观测的最大功率点跟踪算法,利用双种群萤火虫算法的全局优化能力和模糊控制的逻辑推理能力产生更精确的控制信号,通过Boost变换器对等效负载进行动态调节。结果表明:基于双种群萤火虫优化-模糊扰动观测的最大功率点跟踪算法能以更快的速度追踪到并稳定在最大功率点,降低了稳态误差,抑制了功率振荡,提高了抗干扰能力,显著改善了微生物燃料电池的产电能力和供电质量。

考虑风光出力不确定性的风光储微电网系统智能协调控制策略

对风光储互补的微电网发电系统进行研究,针对风光发电与负载功率不匹配问题,提出了一种基于新型变步长电导增量法的最大功率点追踪控制方法,利用基于Ziegler-Nichols法的改进自适应PID算法实现负载功率蓄电池充放电控制的协同控制策略。通过在MATLAB/Simulink中搭建仿真模型并进行验证,证明了所述方案的准确性以及可行性。

基于混合电解槽自适应控制的光伏制绿氢系统研究

构建光伏阵列与混合电解槽耦合于交流母线的制氢系统。为提高光伏发电系统在环境变化下的能效,采用基于自适应步长扰动观测式的最大功率点追踪技术,光伏直流侧利用超级电容的快速响应和电荷平滑的特性稳定母线电压,网侧变流器采用虚拟同步机控制策略,实现快速响应电网变化需求,提供电网惯性和频率支撑,增强系统稳定性和可靠性;并针对传统单一电解槽制氢系统在固定工作模式下面临的能源浪费、适应性不足等问题,结合碱性电解槽和质子交换膜电解槽的优势,引入一种电解槽自适应控制系统,根据光伏输出功率和电解槽的状态实时调整工作模式,使系统在不同场景下保持较高的灵活性和稳定性。最后通过仿真验证所搭建模型与控制策略的正确性与有效性。

基于I-V曲线逆推法的光伏组件故障诊断策略

光伏组件故障诊断一般依赖于对辐照度和温度等环境变量的测量,对分散的组件故障判别不够精确。文章提出了基于逆推I-V曲线法的光伏组件故障诊断策略。该策略事先提取光伏组件模型参数,然后计算不同辐照度及太阳能电池温度下的I-V曲线,形成I-V曲线库;在运行时无须实时监测太阳能电池运行时表面辐照度及平均温度,仅测量光伏组件的开路电压、短路电流和最大功率点电压、电流,即可判断出组件是否发生故障。搭建实验平台对典型故障进行模拟并利用该策略进行判别,结果表明,文章提出的策略能够有效判断组件的故障。利用该策略研发了单板故障监测模块,实现了光伏组件在线故障判断,提高了光伏组件故障判断的精确性及光伏电站运行的可靠性和经济性。

基于Boost电路的光伏系统MPPT变工况分析

近年来,太阳能因其卓越的环保特性、可再生能源的特质以及可持续发展的重要性,成为了能源领域备受关注的研究和实践焦点。然而,太阳能的高效利用受多种气象因素的影响,包括温度、光照强度和天气变化等。这些因素对太阳能系统的性能和能源产出构成了重大挑战。研究了一种提高太阳能利用率的方法,即通过调节Boost电路的占空比来调节太阳能电池板的输出电压,实现对太阳能电池板的变工况最大功率点追踪,从而应对温度、光照强度等天气条件的变化。

光伏并网系统的建模与仿真

根据光伏电池数学模型,在Matlab软件中建立光伏电池的仿真模型并进行了仿真,仿真结果表明,光伏电池的输出呈明显的非线性特性,并随环境温度和光照的变化而变化。在光伏电池最大功率点跟踪方面,提出了一种变步长扰动观察法,可根据外界环境变化,使光伏阵列快速、准确地跟踪最大功率点,同时也能保证系统的稳定。此外,对于逆变器模块,由建模仿真验证了三电平逆变器并网控制策略,得到了稳定的三相正弦电压和电流,为光伏系统稳定并网提供了支撑。

光伏电池工程用数学模型研究

光伏电池输出特性曲线方程是光伏发电理论研究的基础,本文结合该曲线和质点平抛运动轨迹的相似性,在原有的光伏电池工程指数模型基础上,首次提出了另一种更便于计算的光伏电池工程用数学模型。该模型的特点是用在三个不同重力场g0、g1和g2下的质点平抛的运动轨迹来代替光伏电池输出特性曲线。运用物理学中的平抛运动公式换算出电池输出特性曲线,通过调节g0、g1分界点的位置,使得本模型在不同的环境条件下最大功率点附近的误差尽可能小。实验表明该模型生成数据和实测数据的误差能满足工程精度要求,模型运算量和指数模型比较,减少了运算量。