Comparative Assessment between Five Control Techniques to Optimize the Maximum Power Point Tracking Procedure for PV Systems

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.

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&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&O simulation along with IC simulation at a steady temperature and irradiance. Findings MATLAB simulations are used to implement the P&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&O solution gave 94% performance when configured. P&O controller has a better time response process. As compared to the P&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.

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.

Currently, Photovoltaic (PV) energy is the most important energy resource in electrical power applications around the world since it is inexhaustible, clean and pollution free. As the output power from the PV arrays changing with solar irradiance and temperature, so it is necessary to operate the photovoltaic (PV) system at the maximum power point (MPP) to increase the power extraction from the solar panel. For this effective operation and maximum power extraction from a PV system, Maximum power point tracking (MPPT) algorithm plays a vital role by operating the PV energy system near the MPP. In this work, amongst several existing well established MPPT algorithms, the open voltage (OV) based algorithm is chosen for simulation of a PV system using Matlab / Simscape. As maximum power point (MPP) can be attained with a certain amount of load from the PV power system, so load matching is an important concept of MPPT algorithms. Here, the performances of this open voltage (OV) based algorithm method is evaluated for different values of solar radiation and battery was used as load to see the charging performance for the algorithm.

An MPPT (Maximum Power Point Tracking) plays a vital role in a photovoltaic(PV) power generation system. Applying the optimum MPPT is a significant way to achieve an efficient PV system. The MPPT methods’ efficiency counts on the two MPPT factors, including the perturbation period and the perturbation amplitude. Nevertheless, realizing MPPT in the photovoltaic array is very hard when the natural conditions change, especially for the temperature and light intensity. This paper proposed a new method based on Conjugate Gradient (CG) to address the problem of hard reasonable considering both dynamic and steady-state performance in some existing MPPT algorithms. Meanwhile, the presented algorithm can effectively adjust the output of PV cells by controlling the boost DC/DC converter. Finally, the experimental and simulation results show the system can quickly get the maximum power point and have performance.

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

Solar Photovoltaic (PV) energy is becoming an increasingly important part of the world's renewable energy. In order to develop technology for efficient energy conversion from a solar PV system, this paper studies typical Maximum Power Point Tracking (MPPT) control techniques used in solar PV industry and then proposes a close-loop and adaptive MPPT method for reliable and rapid extraction of solar PV power. The paper emphasizes especially on how the proposed and conventional adaptive MPPT methods perform under highly variable weather and solar irradiation conditions in a digital control environment. A computer simulation system is developed by using SimPowerSystems and Opal-RT real-time simulation technology which allows for fast and efficient investigations of the MPPT algorithms under high switching frequency conditions for power converters. A hardware experiment system is built to validate and compare the proposed and conventional MPPT techniques in a more practical condition. Advantages, disadvantages and properties of different MPPT methods are compared and studied, evaluated.

This paper presents an enhanced perturb and observe (P&O) method for reconciling the trade-off problem between the dynamic response and steady-state oscillations in maximum power point tracking (MPPT). The constraint of having to sacrifice either the dynamic response or the steady-state oscillations has been solved. The method uses the relationship between the open-circuit voltage and maximum power voltage from the fractional open-circuit voltage (FOCV) MPPT method to establish a valid, reduced, and confined search space within which an enhanced P&O via dynamic adaptive step size terminates the search for the maximum power point. The feasibility of the proposed method has been validated by comparing its performance with the conventional P&O algorithm. It was noted that the proposed method increased the operational efficiency of the PV module to 99.89%, reduced the tracking time to 1.8 ms, and preserved the good steady-state response with a power attenuation of less than 0.10 W or relative 0.16% under MATLAB environment. An experimental setup was used to collect real irradiance and temperature data which was used in real-time simulations. The enhanced P&O method was able to resist abrupt changes in irradiance and temperature as it effectively and efficiently followed the maximum power point (MPP). Finally, to appreciate the supremacy of the proposed method, it was compared to nineteen different MPPT methods from literature. The comparison showed that the enhanced P&O MPPT method is highly efficient and effective for MPPT in photovoltaic (PV) generation systems.

As a sustainable energy source, the use of solar photovoltaic (PV) systems has significantly increased. Environmental elements, especially partial shadowing circumstances, have a considerable impact on how well solar PV systems function. In such cases, the various local maxima in the power-voltage curve make it difficult for conventional Maximum Power Point Tracking (MPPT) methods to maintain peak efficiency. Heuristic Maximum Power Point Tracking (MPPT) system for solar photovoltaic (PV) applications, employing the cuckoo search algorithm. The primary objective of the research is to enhance the efficiency and reliability of solar PV systems by optimizing the MPPT process, which is crucial for maximizing energy extraction under varying environmental conditions. The model is used to simulate the performance of the system under various environmental conditions, such as changes in temperature and irradiance levels. The simulation results are then statistically analyzed to evaluate the effectiveness of the cuckoo search algorithm in tracking the maximum power point accurately and rapidly. The algorithm demonstrates a robust ability to converge to the maximum power point efficiently, thereby enhancing the overall energy yield of the solar PV system.. The performance of the hybrid PSO-CSA MPPT algorithm in contrast to traditional MPPT techniques is assessed through simulations and tests under various shading circumstances. The findings show that the hybrid strategy regularly outperforms conventional methods by enhancing the total energy production of partially shadowed solar PV installations through faster convergence, less oscillations, and greater tracking accuracy. The proposed hybrid algorithm also demonstrates stability and flexibility in real-world settings, making it a potential option for boosting the dependability and efficiency of solar PV systems when shade is present. This study advances the field of renewable energy and prepares the path for the use of sophisticated optimization methods to the problems of solar PV power generation under changing environmental circumstances.

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.

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.

Robust maximum power point tracking scheme for PV systems based on attractive ellipsoid method

Simulation and experimental design of adaptive-based maximum power point tracking methods for photovoltaic systems

Photovoltaic (PV) systems are broadly utilized, especially for remote electrification. It is easier for installation and is free of greenhouse gases, so the impacts on the environment are reduced. The temperature and irradiance change during the day, and the circumstances are more dynamic on cloudy days. Hence, attaining maximum power under some environmental conditions is complex and also requires individual techniques for tracking the maximum available power. These approaches are named maximum power point tracking (MPPT) methods. These are designed through power electronic converters, which supply the PV power to the load. In recent years, meta-heuristic-based algorithms have emerged because of their local optima avoidance ability and flexibility. However, the maximum power point (MPP) will not be tracked efficiently due to the constraint factors between some circuit parameters. This limitation has to be solved in this study. Here, MPPT constraint conditions of the PV system with an inverter are found by analyzing its integrated mathematical model. The MPP of a PV system is tracked by diverse techniques. Though these approaches differ in complexity, effectiveness, and convergence speed, cost and sensors are required. With the effect of these challenges, the main intention of this paper is to design and develop a new modified MPPT algorithm for enhancing the efficiency of the power grid connected with a DC-AC single-phase full-bridge inverter and a proportional integral derivative (PID) controller. Here, the parameters of the PID controller are tuned or optimized by the newly improved meta-heuristic algorithm termed modified tunicate swarm algorithm with new condition (MTSA-NC) thus maximizing the energy extraction of the PV system. The search process for newly improved MTSA-NC works well to adapt the MPPT to cope with a "grid-connected" inverter by attaining a faster convergence rate. Here, MTSA-NC is adopted by introducing the fitness-based solutions for updating the swarm behavior of tunicates to maximize the energy efficiency of "grid-connected" inverter systems for PV arrays. In MTSA-NC, the optimal fitness value is known as a food source, which is used for determining the solution updating. Finally, the experimental tests validate the success of the designed scheme in a PV system during uniform irradiance and partial shading conditions.

Energy crises and the growth of the energy demand have increased the interest in utilizing unconventional power sources. Thus, renewable energy sources have become a topic of interest to mitigate rising energy concerns and cope with increased electricity demand. With remarkable merits including cleanness and abundance, photovoltaic (PV) solar energy systems are a key to solving these issues. The employed inverters should effectively utilize the maximum available power from the PV solar system and transfer this power to the utility grid without posing any further limitations. However, the unequal power generation of different PV systems caused by partial shading (PS) and other PV panel degradation factors leads to a reduction in generation capacity. One of the relatively new solutions to mitigate the mismatch concerns between the PV modules and sub-modules is to extract the maximum power of each sub-module individually. The main objective of this paper is to present a comprehensive review of such PV grid-connected inverters topologies associated with sub-module connection and control. It will classify the PV grid-tied inverters in accordance with the level where the maximum power point tracking (MPPT) system is implemented. A special focus has been placed on sub-module microinverters (MI) in terms of circuit topologies, conversion efficiency, and controller design. This paper provides a comprehensive analysis of employing the distributed MPPT (DMPPT) approach to maximize the power generation of PV systems by mitigating the mismatch issues inside the PV module. The circuit topology, PV system configuration, and MPPT algorithms used for applying DMPPT solutions in PV SMs are discussed in detail in this study.