Adaptive neuro-fuzzy inference system-based maximum power point tracking of solar PV modules for fast varying solar radiations

This paper analyses the operation of an adaptive neuro-fuzzy inference system (ANFIS)-based maximum power point tracking (MPPT) for solar photovoltaic (SPV) energy generation system. The MPPT works on the principle of adjusting the voltage of the SPV modules by changing the duty ratio of the boost converter. The duty ratio of the boost converter is calculated for a given solar irradiance and temperature condition by a closed-loop control scheme. The ANFIS is trained to generate maximum power corresponding to the given solar irradiance level and temperature. The response of the ANFIS-based control system is highly precise and offers an extremely fast response. The response time is seen as nearly 1 ms for fast varying cell temperature and 6 ms for fast varying solar irradiance. The simulation is done for fast-changing solar irradiance and temperature conditions. The response of the proposed controller is also presented.     

Application of QOCGWO-RFA for maximum power point tracking (MPPT) and power flow management of solar PV generation system

A hybrid technique for solar PV array (SPV) generating system for maximizing the power to load is proposed in this dissertation. The proposed hybrid technique is the joint execution of both the Quasi Oppositional Chaotic Grey Wolf Optimizer (QOCGWO) with Random Forest Algorithm (RFA) and hence it is named as QOCGWO-RFA technique. Here, QOCGWO optimizes the exact duty cycles required for the DC-DC converter of SPV based on the voltage and current parameters. RFA predicts the control signals of the voltage source inverter (VSI) based on the active and reactive power variations in the load side. With this control technique, the system parameter variations and external disturbances are reduced and the load demands are satisfied optimally. The proposed strategy is implemented in MATLAB/Simulink working platform with three different case studies and compared with existing techniques. With these case studies, the proposed technique generates the optimal PV power of 2.1 kW.     

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.     

太阳能光伏发电最大功率跟踪控制器的研究

针对目前太阳能发电系统效率低、铅酸蓄电池使用寿命短等问题,利用微控制器MC9S08QG8设计一种太阳能控制器。该控制器采用升降压式DC/DC转换电路、利用电压扰动法实现最大功率点跟踪,使太阳能电池始终保持最大功率输出;控制器还能实时测量蓄电池的端电压,对蓄电池进行充放电保护。该控制器软硬件结合、可靠性高,提高了太阳能发电系统的效率,延长了蓄电池的使用寿命。     

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.     

分布式光伏发电系统最大功率点跟踪技术比较研究

基于当前光伏阵列最大功率点跟踪技术的研究现状,介绍了适用于分布式光伏发电系统最大功率点跟踪的各种常用控制方法,阐述了每一种控制方法的技术原理,分析和比较了这些常用控制方法的特点,总结了各自的优点和缺点,最后对分布式光伏发电系统最大功率点跟踪方法的选择问题进行了探讨,并指出了具体选择方法时应综合考虑的各种因素。     

Evaluation of a proper controller performance for maximum-power point tracking of a stand-alone PV system

In this paper the implementation of a suggested stand-alone PV system, for maximum-power point tracking (MPPT), is carried out. Also, this paper presents a comparative study, through experimental work, between the conventional PI controller and the fuzzy logic controller (FLC) under different atmospheric conditions. The implemented system with both the PI controller and the FLC gives a good maximum-power operation of the PV array, but the tracking capability for different optimum operating points is better and faster for the case of using the FLC compared to the case of using the PI controller.     

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 comparative study of maximum power point tracking methods for a photovoltaic-based water pumping system

In this paper the performance of the proposed fuzzy-based maximum power point tracking (MPPT) is investigated and compared with incremental conductance and constant voltage controller for a photovoltaic (PV) pumping system. A fuzzy logic controller with a mamdani inference engine using only nine rules is designed to track the optimum power point. An induction motor has been used to drive the centrifugal pump. The system performance is analysed for different weather conditions. A detailed comparative study presenting the merits and demerits of each technique is also presented in order to develop a relative relationship. Simulation results obtained indicate better performance of the fuzzy-based MPPT algorithm for the PV pumping system.     

A maximum power point tracking for photovoltaic-SPE system using a maximum current controller

Processes to produce hydrogen from solar photovoltaic (PV)-powered water electrolysis using solid polymer electrolysis (SPE) are reported. An alternative control of maximum power point tracking (MPPT) in the PV-SPE system based on the maximum current searching methods has been designed and implemented.Based on the characteristics of voltage–current and theoretical analysis of SPE, it can be shown that the tracking of the maximum current output of DC–DC converter in SPE side will track the MPPT of photovoltaic panel simultaneously.This method uses a proportional integrator controller to control the duty factor of DC–DC converter with pulse-width modulator (PWM).The MPPT performance and hydrogen production performance of this method have been evaluated and discussed based on the results of the experiment.     

Fuzzy-PSO controller design for maximum power point tracking in photovoltaic system

Photovoltaic power generation system becomes increasingly important, highly attractive as a clean and renewable energy sources, widely used today in many applications. Recently, researchers have strongly promoted the use of solar energy as a viable source of energy due to its advantages and which it can be integrated into local and regional power supplies. The P–V curve of photovoltaic system exhibits multiple peaks under various conditions of functioning and changes in meteorological conditions which reduces the effectiveness of conventional maximum power point tracking (MPPT) methods and the Particle swarm optimization (PSO) algorithm is considered to be highly efficient for the solution of complicated problems.In this paper, the application of this approach based MPPT algorithm for Photovoltaic power generation system operating under variable conditions is proposed to optimize and to design an intelligent controller comparing to conventional one. PSO Approaches is considered to select and generate an optimal duty cycle which varies with photovoltaic parameters in order to extract the maximum Power. Simulation results show that the proposed approach can track the maximum power point faster and can improve the performance of the system compared to the conventional method.     

光伏发电的最大功率跟踪算法研究

太阳能光伏阵列的输出特性受外界环境因素的影响,为了跟踪太阳能光伏阵列输出功率最大点,实现光伏阵列和负载的匹配,常在系统中加入最大功率跟踪器。准确跟踪太阳能光伏阵列的最大输出功率点依赖于有效的搜索算法。分析了传统的扰动观察法和增量电导法的特点,并提出了一种新的变步长寻优算法。通过验证表明,这种算法能够快速准确地跟踪最大功率点。     

Robust maximum power point tracker using sliding mode controller for the three-phase grid-connected photovoltaic system

A robust maximum power point tracker (MPPT) using sliding mode controller for the three-phase grid-connected photovoltaic system has been proposed in this paper. Contrary to the previous controller, the proposed system consists of MPPT controller and current controller for tight regulation of the current. The proposed MPPT controller generates current reference directly from the solar array power information and the current controller uses the integral sliding mode for the tight control of current. The proposed system can prevent the current overshoot and provide optimal design for the system components. The structure of the proposed system is simple, and it shows robust tracking property against modeling uncertainties and parameter variations. Mathematical modeling is developed and the experimental results verify the validity of the proposed controller.     

Long-term field test of solar PV power generation using one-axis 3-position sun tracker

The 1 axis-3 position (1A-3P) sun tracking PV was built and tested to measure the daily and long-term power generation of the solar PV system. A comparative test using a fixed PV and a 1A-3P tracking PV was carried out with two identical stand-alone solar-powered LED lighting systems. The field test in the particular days shows that the 1A-3P tracking PV can generate 35.8% more electricity than the fixed PV in a partly-cloudy weather with daily-total solar irradiation H_T = 11.7 MJ/m² day, or 35.6% in clear weather with H_T = 18.5 MJ/m² day. This indicates that the present 1A-3P tracking PV can perform very close to a dual-axis continuous tracking PV (Kacira et al., 2004). The long-term outdoor test results have shown that the increase of daily power generation of 1A-3P tracking PV increases with increasing daily-total solar irradiation. The increase of monthly-total power generation for 1A-3P sun tracking PV is between 18.5-28.0%. The total power generation increase in the test period from March 1, 2010 to March 31, 2011, is 23.6% in Taipei (an area of low solar energy resource). The long-term performance of the present 1X-3P tracking PV is shown very close to the 1-axis continuous tracking PV in Taiwan (Chang, 2009). If the 1A-3P tracking PV is used in the area of high solar energy resource with yearly-average H_T > 17 MJ/m² day, the increase of total long-term power generation with respect to fixed PV will be higher than 37.5%. This is very close to that of dual-axis continuous tracking PV.The 1A-3P tracker can be easily mounted on the wall of a building. The cost of the whole tracker is about the same as the regular mounting cost of a conventional rooftop PV system. This means that there is no extra cost for 1A-3P PV mounted on buildings. The 1A-3P PV is quite suitable for building-integrated applications.     

ANN based peak power tracking for PV supplied DC motors

This paper presents an application of an Artificial Neural Network (ANN) for the identification of the optimal operating point of a PV supplied separately excited dc motor driving two different load torques. A gradient descent algorithm is used to train the ANN controller for the identification of the maximum power point of the Solar Cell Array (SCA) and gross mechanical energy operation of the combined system. The algorithm is developed based on matching of the SCA to the motor load through a buck-boost power converter so that the combined system can operate at the optimum point. The input parameter to the neural network is solar insolation and the output parameter is the converter chopping ratio corresponding to the maximum power output of the SCA or gross mechanical energy output of the combined PV system. The converter chopping ratios at different solar insolations are obtained from the ANN controller for two different load torques and are compared with computed values.     

Adaptive fuzzy gain scheduling PID controller for maximum power point tracking of photovoltaic system

This paper proposes a methodology of designing a Maximum Power Point Tracking (MPPT) controller for photovoltaic systems (PV) using a Fuzzy Gain Scheduling of Proportional-Integral-Derivative (PID) type controller (FGS-PID) with adaptation of scaling factors (SF) for the input signals of FGS. The proposed adaptive FGS-PID method is based on a two-level control system architecture, which combines the advantages of fuzzy logic and conventional PID control. The initial values of the PID's gains are determined by the Ziegler–Nichols tuning method. During transient and steady states, the PID's gains are adapted by the FGS-PID to damp out the transient oscillations, to reduce settling time and to guarantee system stability and accuracy. Also, the conditioned input signals of the FGS-PID are tuned dynamically by gain factors which are based on fuzzy logic system (FLS). The FLS is characterized by a set of fuzzy rules which are fuzzy conditional statements expressing the relationship between inputs (error and change of error) and outputs. This approach creates an adaptive MPPT controller and achieves better overall system performance. The simulation results demonstrate the effectiveness of the proposed adaptive FGS-PID and show that this approach can achieve a good maximum power operation under any conditions such as different levels of solar radiation and PV cell temperature for varying PV sources. Compared to conventional methods (PID, perturb and observe method P&O), this method shows a considerable high tracking performance.     

A maximum power point tracker for PV systems using a high performance boost converter

This work deals with the design and experimental implementation of a MPP-tracker for photovoltaic systems, which is a high efficiency dc/dc boost converter operating in continuous conduction mode (CCM). The converter is able to draw maximum power from the PV panel for a given solar radiation level and environment temperature by adjusting the duty cycle of the converter. Additionally, a passive nondissipative turn-on turn-off snubber is used, so that high efficiency and reduced electromagnetic interference (EMI) levels due to the soft switching operation can be obtained. The snubber improves the converter efficiency since the energy that would be dissipated during turning on and turning off is transferred to the load. The control technique, implemented with a single-chip microcontroller 80C51, is based on the perturbation and observation method, where the maximum power point is tracked with periodical calculation of the panel output power. Simulation and experimental results describe the performance of the proposed MPP-tracker.     

Simulation model for sizing of stand-alone solar PV system with interconnected array

Solar PV arrays made of interconnected modules are comparatively less susceptible to shadow problem and power degradation resulting from the aging of solar cells. This paper presents a simulation model for the sizing of stand-alone solar PV systems with interconnected arrays. It considers the electricity generation in the array and its storage in the battery bank serving the fluctuating load demand. The loss of power supply probability (LPSP) is used to connote the risk of not satisfying the load demand. The non-tracking (e.g., fixed and tilted) and single-axis tracking aperture arrays having cross-connected modules of single crystalline silicon solar cells in a (6×6) modular configuration are considered. The simulation results are illustrated with the help of a numerical example wherein the load demand is assumed to follow uniform probabilistic distribution. For a given load, the numbers of solar PV modules and batteries corresponding to zero values of LPSP on diurnal basis during the year round cycle of operation are presented. The results corresponding to the surplus and deficit of energy as a function of LPSP are also presented and discussed to assess the engineering design trade offs in the system components.Furthermore, a simple cost analysis has also been carried out, which indicates that for Delhi the stand-alone solar PV systems with fixed and tilted aperture arrays are better option than those with single-axis tracking aperture (with north–south oriented tracking axis) arrays.     

Practical values of various parameters for PV system design

In order to reasonably design a PV system, it is important to use appropriate parameter values. Few papers, however, describe design parameters that are defined systematically. The authors have been entrusted by the New Energy and Industrial Technology Development Organization (NEDO) with research and development of PV system evaluation since 1990 in order to establish optimum design and operation methods of various kinds of PV systems which are expected to be put into commercial use in the future.In this research, which is based on the data obtained from test facilities which were constructed at Hamamatsu site, various design parameters were calculated and reported as primary values provisionally estimated. This paper presents practical values of various parameters for PV system design as a table, revised with design parameter values studied later on. In particular, cell temperature factor was studied in view of regional differences and module mounting.The authors will confirm reasonable design of PV system by using such various design parameter values.     

A photovoltaic powered electrolysis converter system with maximum power point tracking control

One of the main problems for renewable and other innovative energy sources is the storage of energy for sustainability. This study focuses on two different scenarios to benefit from solar energy more efficiently. Photovoltaic (PV) energy is converted to the desired voltage level using a buck converter for generating hydrogen with electrolysis process. A maximum power point tracking (MPPT) algorithm is used to benefit from the photovoltaic sources more efficiently. The basic electrolysis load for hydrogen production needs low voltage and high current and controlled sensitively to supply these conditions. The photovoltaic powered buck converter for electrolysis load was simulated in MATLAB/Simulink software using a perturb and observe (P and O) MPPT algorithm and PI controller. The simulation results show that in normal, short circuit and open circuit working conditions the PV and load voltages are stabilized. The efficiency of the proposed system is reached more than 90% for high irradiance levels.