A Maximum Power Point Tracking Method Based on Extension Neural Network for PV Systems

This paper reviews the existing models, connection schemes and maximum power point tracking (MPPT) methods of PV arrays. The partial shading causes significant power losses. It is very difficult to maintain uniform irradiance over the entire PV array, especially for rooftop or building-integrated PV systems. The aspects such as connection scheme of PV array, shading pattern and maximum power point tracking (MPPT) techniques, etc., decide the power generated by the PV array. The conventional MPPT methods are only capable of reaching maximum power point (MPP) in identical insolation situations. Hence, conventional MPP tracking becomes inept due to the existence of several peaks in the P-V characteristics. There are different global maximum power point (GMPP) tracking techniques available in the literature that operate in partial shading scenarios. The reconfiguration of the PV array reduces the number of multiple peaks. This reduction in several peaks makes conventional MPP tracking techniques competent even under partial shading conditions with low implementation complexity and higher tracking speed. This paper can assist scientists in choosing a precise objective-based PV module model, connection schemes and MPP tracking methods out of numerous schemes available in the literature.

In the several last years, numerous Maximum Power Point Tracking (MPPT) methods for photovoltaic (PV) systems have been proposed. An MPPT strategy is necessary to ensure the maximum power efficiency provided to the load from a PV module that is subject to external environmental perturbations such as radiance, temperature and partial shading. In this paper, a new MPPT technique is presented. Our approach has the novelty that it is a MPPT algorithm with a dynamic hysteresis model incorporated. One of the most cited Maximum Power Point Tracking methods is the Perturb and Observer algorithm since it is easily implemented. A comparison between the approach presented in this paper and the known Perturb and Observer method is evaluated. Moreover, a new PV-system platform was properly designed by employing low cost electronics, which may serve as an academical platform for further research and developments. This platform is used to show that the proposed algorithm is more efficient than the standard Perturb and Observer method.

Understanding in such way the maximum available power generated by the photovoltaic (PV) array varies with the weather is critical for improving system efficiency by encouraging the PV system to operate at that maximum power point (MPP). Therefore, to maintain optimum power functioning at all irradiance levels and temperatures, a Maximum Power Point Tracking (MPPT) system is necessary. MPPT methods have been developed and implemented in a number of studies. The accuracy, convergence speed, ease of hardware implementation, PV dependency, number of necessary sensors, which are significantly differ across these systems. The first technique to be introduced was a single MPPT technique. However, as it works independently, it was unable to achieve several of the required characteristics. Afterwards, the merger techniques of multiple MPPTs and the combination of both (single and multiple MPPTs’ techniques) due to integrate the benefits of each algorithm while removing their limitations. Comparing and surveying MPPT algorithms in general took a significant amount of time. Despite this, there is a limited literature examining the combination techniques towards the multiple MPPT techniques and the single one. This paper presents the work and uses MATLAB/Simulink platform to simulate it. It is based on a study that contrasts single MPPT techniques with different combinations, namely the constant voltage (CV) method, the perturb and observe (P&O) method and the combination of both (CV+P&O), in order to validate MPPT's better performance.

Implementation of a modified incremental conductance MPPT algorithm with direct control based on a fuzzy duty cycle change estimator using dSPACE

태양전지의 출력 특성은 비선형이고 온도와 일사량에 많은 영향을 받는다. 최대전력점 추종 제어는 태양광 발전의 출력을 최대로 하기 위해 사용되는 제어기법이다. 태양광발전 시스템의 출력 및 효율을 증가시키기 위해 더욱 우수한 최대전력점 추종 제어기법이 필요하다. 본 논문에서는 태양광 발전 시스템의 효율을 개선하기 위해 일사량을 고려한 새로운 최대전력점 추종 제어 알고리즘을 제시한다. 제시한 알고리즘은 종래의 P&O방법과 CV 방법을 혼합한 것이며, PSIM 시뮬레이터를 통하여 종래의 MPPT 알고리즘과 다양한 일사량 조건에서 성능시험을 비교하였다.<BR> 제시한 알고리즘은 종래의 알고리즘에 비해 출력의 자려진동없이 다양한 일사량에서 우수한 성능을 나타냈다. 이로서 본 논문에서 제시한 HB 방법의 최대전력점 추종 제어 알고리즘의 타당성을 입증하였다.

For maximum utilization of solar energy, photovoltaic (PV) power systems should be operated at the maximum power point (MPP) which can be achieved using maximum power point tracking (MPPT) methods. However, the occurrence of multi-peak on P-V curve of a PV array due to the changing environmental conditions such as being partially shaded increases the complexity of the tracking process. The global MPP cannot always be achieved by the conventional MPPT methods. Therefore a novel MPPT method for PV systems using flower pollination (FP) algorithm is proposed in this paper and the Levy flight is used to improve the convergence of FP algorithm. MPPT model of the PV system is established in MATLAB to verify the effectiveness of the proposed method, and the proposed method is compared with two well established MPPT methods. The simulation results indicate that the proposed MPPT method can quickly track the changes in external environment and effectively handle the partially shaded condition.

Improved particle swarm optimization for maximum power point tracking in photovoltaic module arrays

Recently, many Maximum power point tracking (MPPT) techniques are proposed in the Photovoltaic (PV) systems. However, a comprehensive comparison of various MPPT techniques especially the dynamic tracking performance has not been made quantitatively for different working conditions. By reviewing different methods, the day-by-day operating evaluation method with practical meteorological data is used in this paper. Furthermore, three typical MPPT techniques including fixed step size P&O method, variable step size incremental conductance method, and hybrid step size Beta method, are selected in the performance evaluation. In order to improve the experimental repeatability and minimize the effect of random environmental factor such as partial shading, an indoor test system that consists of a DC-DC boost converter, a PV emulator and a dSPACE is used. The practical meteorological data are used for the evaluation these typical MPPT techniques and main experimental results are presented.

Purpose Silicon photovoltaics technology has drawbacks of high cost and power conversion efficiency. In order to extract the maximum output power of the module, maximum power point (MPP) is used by implying the nonlinear behavior of I-V characteristics. Different techniques are used regarding maximum power point tracking (MPPT). The paper aims to review the techniques of MPPT used in PV systems and review the comparison between Perturb and Observe (P&amp;O) method and incremental conductance (IC) method that are used to track the maximum power and gives a comparative review of all those techniques. Design/methodology/approach A study of MPPT techniques for photovoltaic (PV) systems is presented. Matlab Simulink is used to find the MPP using P&amp;O simulation along with IC simulation at a steady temperature and irradiance. Findings MATLAB simulations are used to implement the P&amp;O method and IC method, which includes a PV cell connected to an MPPT-controlled boost converter. The simulation results demonstrate the accuracy of the PV model as well as the functional value of the algorithms, which has improved tracking efficiency and dynamic characteristics. P&amp;O solution gave 94% performance when configured. P&amp;O controller has a better time response process. As compared to the P&amp;O method of tracking, the incremental conductance response rate was significantly slower. Originality/value In PV systems, MPPT techniques are used to optimize the PV array output power by continuously tracking the MPP under a variety of operating conditions, including cell temperature and irradiation level.

This paper presents a new maximum power point tracking (MPPT) method based on an incremental conductance (IC) algorithm, constant voltage, and look-up table approach. Convergence time, one of the indicators of MPPT quality, is considered for improving MPPT performance of photovoltaic (PV) modules. In this context, a novel hybrid MPPT approach has been proposed. This proposed method consists of three stages. In the first stage, the value of load resistance is calculated. Then the initial operation point of the PV module is determined by using the constant voltage method or look-up table approach. An IC algorithm is used in order to increase MPPT accuracy in the last stage. One of the novelties of this proposed approach is the determination criterion related to sample numbers of PV module current or solar irradiance. With the help of this approach, the initial operation point of the PV module is optimized before MPPT starts. Thus, convergence time is reduced. In this paper, a DC--DC boost converter has been designed to show the performance of the proposed approach. Then the proposed approach is compared with an IC algorithm. Experimental results show that the performance of the proposed approach is better than that of the IC algorithm in terms of convergence time. On the other hand, since the proposed approach is convenient for reducing convergence time, it can be used instead of variable step size algorithms. Furthermore, there are no topological constraints in the proposed approach. Therefore, this method can be easily applied to other converter topologies for low power or microconverter (module-based converter)-based applications.

To mitigate problems like energy shortage and environmental degradation caused by conventional energy sources, it needs to shift from conventional energy to non-conventional energy sources. The solar photovoltaic (PV) technology emerges as one of the leading non-conventional energy sources. To operate a PV system at its maximum efficiency, it requires the operating module at maximum power output point (MPP). There are many conventional as well as advanced maximum power point tracking (MPPT) techniques developed and implemented for a solar PV system. This work provides a comparative analysis of the conventional and fuzzy logic controller (FLC)-based MPPT techniques for a solar PV system. In this study, performance of two conventional techniques is considered, i.e., perturb and observe (P & O) and incremental conductance (IC) MPPT technique. The analysis of the PV system is performed for different solar irradiance levels. The comparative study is evaluated for complexity, tracking time, efficiency, range of power, voltage, and current oscillations. The DC-DC boost converter is used for operation of the proposed PV system at MPP. The implementation of the entire system and control algorithms has been modeled in MATLAB Simulink.

Implementation of Solar thermal energy as a source of renewable electricity is currently being developed. The main problem with photovoltaic systems is the result of power efficiency is low. The maximum power point tracking (MPPT) method can increase the efficiency of photovoltaic output power. This research will use the MPPT method with an artificial bee colony (ABC) algorithm. MPPT design will be simulated using Power Simulation (PSIM) software. Simulation results will be compared with no MPPT and MPPT human psychology optimization (HPO) algorithm. The results show MPPT ABC gets the best average accuracy from the average accuracy without MPPT and MPPT HPO, which is 99.95%. And the MPPT ABC has a response time of MPP tracking faster than MPPT HPO, during irradiation 800 W/m 2 , 900 W/m 2 , 1000 W/m 2 .

Novel standalone hybrid solar/wind/fuel cell power generation system for remote areas

This paper presents an improved reinitialisation condition for time invariant maximum power point tracking (MPPT) methods used in photovoltaic (PV) systems experiencing partial shading conditions (PSC). Time invariant (MPPT) methods, such as Particle Swarm Optimisation (PSO), overcome the limitations of existing MPPT by tracking the global maximum power point (GMPP) of a PV system operating under PSC. However, due to the time invariant structure of these MPPT methods, they also require a reinitialisation condition to be defined for when a change in irradiance or temperature occurs. Testing was performed using simulations of a model built in Matlab/ Simulink, where the performance of existing and developed conditions was evaluated using test cases with changes in solar irradiance. Limitations of existing conditions were identified and a more robust reinitialisation condition developed. The developed reinitialisation condition used sentry particles to monitor the PV voltage range for changes in the measured power of any sentry. The developed condition had a 96 % rate of successful detection, as compared to as low as 68 % successful detection for existing methods, demonstrating improved performance and robustness.

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