Maximum Power Point Tracking Efficiency Research Articles

Robust Integral Backstepping Based Nonlinear MPPT Control for a PV System

A photovoltaic system generates energy that depends on the environmental conditions such as temperature, irradiance and the variations in the load connected to it. To adapt to the consistently increasing interest of energy, the photovoltaic (PV) system must operate at maximum power point (MPP), however, it has the issue of low efficiency because of the varying climatic conditions. To increase its efficiency, a maximum power point technique is required to extract maximum power from the PV system. In this paper, a nonlinear fast and efficient maximum power point tracking (MPPT) technique is developed based on the robust integral backstepping (RIB) approach to harvest maximum power from a PV array using non-inverting DC-DC buck-boost converter. The study uses a NeuroFuzzy network to generate the reference voltage for MPPT. Asymptotic stability of the whole system is verified using Lyapunov stability criteria. The MATLAB/Simulink platform is used to test the proposed controller performance under varying meteorological conditions. The simulation results validate that the proposed controller effectively improves the MPPT in terms of tracking speed and efficiency. For further validation of the proposed controller performance, a comparative study is presented with backstepping controller, integral backstepping, robust backstepping and conventional MPPT algorithms (PID and P&O) under rapidly varying environmental conditions.

Photovoltaic Flyback Microinverter With Tertiary Winding Current Sensing

This paper presents a new low cost, non-invasive, and isolated current sensing technique for the grid-tied photovoltaic (PV) flyback microinverter. This is accomplished by using the flyback transformer itself as a current sensor, achieved by introducing a tertiary winding to the flyback transformer. The mathematical integration of the tertiary winding's open circuit voltage through a ground-clamped-integrator results in the sensing of the magnetizing current. Since the magnetizing current is a combination of both primary and secondary current, control of both grid current and maximum power point tracking (MPPT) is implemented by sensing only the magnetizing current. This allows the PV, primary, secondary, and the grid current loops to be free of any invasive current sensors. Moreover, controlling the magnetizing current provides an alternative solution to an inherent problem with continuous conduction mode (CCM), the control complexity. Linear ramping and de-ramping of the magnetizing current allows for a set–reset hysteresis control to be implemented, resulting in CCM control simplicity that is akin to the boundary and discontinuous conduction mode. A grid-tied microinverter prototype is presented for verification, achieving the following experimental result: 1.9% grid current THD, 0.9988 power factor, above 99% static MPPT efficiency and dynamic efficiency of 98.50%.

Modelling and analysis of an analogue MPPT‐based PV battery charging system utilising dc–dc boost converter

Nowadays, the research is being devoted to the development of rapid and precise maximum power point tracking (MPPT) for various photovoltaic (PV) applications. However, the constraints imposed by size, cost, efficiency, and tracking performances essentially limit the application of conventional MPPT techniques and their analysis methodologies. This study recommends a fast and robust analogue PV MPPT for the battery charging system using dc-dc boost converter. The fast dynamic performances with absolute robustness are ensured here by fast-scale stability analysis of actually switched boost converter using the concepts based on non-linear dynamics and bifurcation theory. Such concepts not only provide the information to design an efficient MPPT system under rapidly changing environmental conditions but also guarantee the system to operate either in period-1 or chaotic mode. The theoretical and mathematical analyses are experimentally verified using a prototype PV battery charging system utilising dc-dc boost converter. It is presented that operating the MPPT system in chaos not only yields the broader power spectrum with reduced spectral peaks at the multiples of converter's switching frequency but also exhibits high overall conversion efficiency.

MPPT methods for solar PV systems: a critical review based on tracking nature

An efficient maximum power point tracking (MPPT) method plays an important role to improve the efficiency of a photovoltaic (PV) generation system. This study provides an extensive review of the current status of MPPT methods for PV systems which are classified into eight categories. The categorisation is based on the tracking characteristics of the discussed methods. The novelty of this study is that it focuses on the key characteristics and eleven selection parameters of the methods to make a comprehensive analysis, which is not considered together in any review works so far. Again, the pros and cons, classification and immense comparison among them described in this study can be used as a reference to address the gaps for further research in this field. A comparative review in tabular form is also presented at the end of the discussion of each category to evaluate the performance of these methods, which will help in selecting the appropriate technique for any specific application.

A hybrid MWOAL approach for fast and efficient maximum power point tracking in wind energy conversion systems

This paper proposes an efficient hybrid approach for the fast and efficient MPPT in WECS. The system consists of an MPPT based control of IPMSG consisting of a hybrid Meta-heuristic algorithm. The hybrid Meta-heuristic algorithm presented in the proposed approach is the joined execution of both WOA and the ALO algorithm named as MWOAL. In the proposed approach, the WOA is considered to resolve the optimal gain parameters of the PI controller with a minimum error objective function based on the variation of direct and quadrature current parameters. Here, the searching behavior of the whales is modified by using the efficient ALO algorithm is known as modified WOAL MWOAL. The setpoint direct axis and the quadrature axis current parameters of the WECS are determined using the MPPT technique and the loss minimization approach based on the generator speed variation. Hence, the proposed scheme has improved the efficiency of the WECS. At that point, the performance of the proposed adaptive MPPT control of WECS is executed in the MATLAB/Simulink working platform and the execution is assessed using the existing techniques.

Mitigation of Interharmonics in PV Systems With Maximum Power Point Tracking Modification

Interharmonics are emerging power quality challenges in grid-connected photovoltaic (PV) systems. Previous studies and field measurements have confirmed the evidence of interharmonic emission from PV inverters, where the maximum power point tracking (MPPT) is one of the main causes for interharmonics. In that regard, the MPPT parameters such as their sampling rate has a strong impact on the interharmonic characteristic of the PV system. In general, there is a trade-off between the interharmonic emission and the MPPT performance when selecting the sampling rate of the MPPT algorithm. More specifically, employing a faster MPPT sampling rate will improve the MPPT efficiency, but it will also increase the interharmonic emission level. To solve this issue, a new mitigating solution for interharmonics in PV systems is proposed in this paper. The proposed method modifies the MPPT algorithm in a way to randomly select the sampling rate between the fast and the slow value. By doing so, the interharmonics in the output current can be effectively reduced due to the distribution of the frequency spectrum. On the other hand, the MPPT performance of the proposed method can be maintained similar to the case when employing a fast MPPT sampling rate. The effectiveness of the proposed interharmonic mitigation has been validated experimentally on a single-phase grid-connected PV system.

An Analog BJT-Tuned Maximum Power Point Tracking Technique for PV Systems

In this brief, an analog, bipolar junction transistor (BJT)-tuned voltage reference maximum power point tracking (MPPT) method for photovoltaic modules is proposed. The conventional fixed voltage reference method is the simplest method for tracking, but it does not obtain good MPPT efficiency because the maximum power point (MPP) voltage changes at different insolation levels. In reality, an approximately linear slope is formed when connecting the MPPs measured from the highest insolation level to the lowest. Utilizing this characteristic, a BJT, which has a similar electrical property, is used to implement a variable voltage reference that improves the accuracy of the MPP voltage when the insolation changes. The proposed circuit is simple and easy to implement, and it can track the MPP very quickly without the need for a digital controller or PID controller. Hence, the circuits cost and complexity are reduced. Experimental results are given to verify the feasibility of the proposed MPPT method.

A Novel [formula omitted] feedback based control scheme using GWO tuned PID controller for efficient MPPT of PEM fuel cell

At any operating condition, there is only one maximum power point (MPP) where proton exchange membrane fuel cell (PEMFC) is desired to operate. For this task, a maximum power point tracking (MPPT) controller is generally employed. In this paper, a novel and simple dPdI feedback based control scheme, employing Grey wolf optimizer (GWO) tuned PID controller, is proposed for efficient MPPT of PEMFC. The performance of the GWO tuned PID is controller is compared with two classical techniques namely, P&O and INC and for a fair comparison of choice of optimization method, the former was also compared with PSO tuned PID Performance of the proposed MPPT scheme is assessed under varying operating conditions using root mean square power ripple and maximum power ripple as performance metrics. Presented simulation results clearly indicate superiority of the proposed technique. Therefore, it is concluded that dPdI feedback scheme based GWO tuned PID controller is a more effective MPPT technique for PEMFC.

Comparative study of the most efficient maximum power point tracking techniques for a photovoltaic system

<span>In Photovoltaic (PV) systems, maximum power point tracking (MPPT) is an important challenge which faces this system. In this paper, a comparative study between two high efficient MPPT control techniques is presented. These techniques are based on the incremental conductance (IC) method. The first technique is based on optimized PI-controller gains and the other is based on Fuzzy Logic Control (FLC). The comparison between the algorithms is investigated under different environmental conditions. The comparison criteria which are taken into consideration are: the percentage tracking factor (%TF), the tracking time, the ripple voltage in the steady-state, the dynamic response, and the complexity of implementation.</span>

Analysis, Design, and Implementation of a Static Conductance-Based MPPT Method

This paper introduces a maximum power point tracking (MPPT) method based on a power ( P ) versus static conductance ( G ) curve of a photovoltaic (PV) array. The maximum power point (MPP) is tracked by comparing the PV array instantaneous power to a varying power reference generated by the MPPT algorithm. The comparison error is used to reduce or increase the conductance at which the PV array is forced to operate until the MPP is reached. Simultaneously, the error is used to change the power reference until the trajectory of this reference in the P–G curve enters a limit cycle around the MPP. The P–G curve is derived from a piecewise linear approximation of the current versus voltage ( I–V ) curve, which facilitates the analytical description of the tracking operation. The technique reported can also be implemented by means of simple analog or digital circuitry and requires two sensors to measure the instantaneous PV array current and voltage. It uses only four tuning parameters, which are selected depending on the maximum value of the derivative of the power with respect to the conductance. The theoretical predictions are verified with simulations and experimental results. The latter shows that the procedure performs well enough to be favorably compared with the most efficient MPPT methods.

Novel bio-inspired memetic salp swarm algorithm and application to MPPT for PV systems considering partial shading condition

This paper proposes a novel bio-inspired optimization method named memetic salp swarm algorithm (MSSA). It is developed by extending the original salp swarm algorithm (SSA) with multiple independent salp chains, thus it can implement a wider exploration and a deeper exploitation under the memetic computing framework. In order to enhance the convergence stability, a virtual population based regroup operation is used for the global coordination between different salp chains. Due to partial shading condition (PSC) and fast time-varying weather conditions, photovoltaic (PV) systems may not be able to generate the global maximum power. Hence, MSSA is applied for an effective and efficient maximum power point tracking (MPPT) of PV systems under PSC. To evaluate the MPPT performance of the proposed algorithm, four case studies are undertaken using Matlab/Simulink, e.g., start-up test, step change of solar irradiation, ramp change of solar irradiation and temperature, and field atmospheric data of Hong Kong. The obtained PV system responses are compared to that of eight existing MPPT algorithms, such as incremental conductance (INC), genetic algorithm (GA), particle swarm optimization (PSO), artificial bees colony (ABC), cuckoo search algorithm (CSA), grey wolf optimizer (GWO), SSA, and teaching-learning-based optimization (TLBO), respectively. Simulation results demonstrate that the output energy generated by MSSA in Spring in HongKong is 118.57%, 100.73%, 100.96%, 100.87%, 101.35%, 100.36%, 100.81%, and 100.22% to that of INC, GA, PSO, ABC, CSA, GWO, SSA, and TLBO, respectively. Lastly, a hardware-in-the-loop (HIL) experiment using dSpace platform is undertaken to further validate the implementation feasibility of MSSA.

Variable step size P&O MPPT algorithm for optimal power extraction of multi-phase PMSG based wind generation system

To eradicate limitations of conventional fixed step-size perturb and observe (P&O) maximum power point tracking (MPPT) based on the variable speed - wind energy conversion system (VS-WECS), this article proposes a fast and an efficient MPPT modular sectors algorithm. The variable-step perturb and observe (VS-PO) MPPT algorithm is implemented to divide the power-speed (P-ω) curve into modular sectors each with specific step-size. The modular sectors are established by comparing a special synthesized ratio, that associates with the theoretical power, with a specified ratio corresponding the required power accuracy. Hence, the proper step-size is selected according to the operating sector location. For the sectors near the maximum power point (MPP), a small step-size is applied. Otherwise, a large step-size is used. To calculate the theoretical power, a wind speed estimation algorithm is utilized for evaluating the wind speed. The system configuration involves a 1.5 MW five-phase permanent magnet synchronous generator (PMSG), and a back-to-back frequency converter with the dc-link capacitor for the grid integration. The simulation results illustrate the VS-PO superiority over both the conventional P&O (CPO) and modified P&O (MPO) techniques. The VS-PO improves the initial speed tracking and minimizes the steady state oscillations. The performance of the proposed control schemes is validated using MATLAB/SIMULINK environment.

Enhanced auto-scaling incremental conductance MPPT method, implemented on low-cost microcontroller and SEPIC converter

This paper proposes a new maximum power point tracking (MPPT) algorithm for photovoltaic (PV) systems, which is tested in simulations and practical implementations. In the proposed PV-MPPT system, a new control strategy is applied to create two operating areas. In each area, the step-size is different in the function of the closeness to the MPP. Because of this strategy, some drawbacks of the conventional incremental conductance (IncCond) methods are eliminated. A single-ended primary-inductor converter (SEPIC) DC–DC converter is controlled with the proposed MPPT technique. The modified IncCond method is validated under simulation with test data, real data and real scenarios of solar irradiation. The results of the proposed approach show higher MPPT efficiencies and shorter convergence times than the conventional IncCond method even in rapidly changing conditions of solar radiation.

Modeling and Optimisation of a Solar Energy Harvesting System for Wireless Sensor Network Nodes

The Wireless Sensor Networks (WSN) are the basic building blocks of today’s modern internet of Things (IoT) infrastructure in smart buildings, smart parking, and smart cities. The WSN nodes suffer from a major design constraint in that their battery energy is limited and can only work for a few days depending upon the duty cycle of operation. The main contribution of this research article is to propose an efficient solar energy harvesting solution to the limited battery energy problem of WSN nodes by utilizing ambient solar photovoltaic energy. Ideally, the Optimized Solar Energy Harvesting Wireless Sensor Network (SEH-WSN) nodes should operate for an infinite network lifetime (in years). In this paper, we propose a novel and efficient solar energy harvesting system with pulse width modulation (PWM) and maximum power point tracking (MPPT) for WSN nodes. The research focus is to increase the overall harvesting system efficiency, which further depends upon solar panel efficiency, PWM efficiency, and MPPT efficiency. Several models for solar energy harvester system have been designed and iterative simulations were performed in MATLAB/SIMULINK for solar powered DC-DC converters with PWM and MPPT to achieve optimum results. From the simulation results, it is shown that our designed solar energy harvesting system has 87% efficiency using PWM control and 96% efficiency ( η s y s ) by using the MPPT control technique. Finally, an experiment for PWM controlled SEH-WSN is performed using Scientech 2311 WSN trainer kit and a Generic LM2575 DC-DC buck converter based solar energy harvesting module for validation of simulation results.

An Efficient and Cost-Effective Hybrid MPPT Method for a Photovoltaic Flyback Microinverter

This paper presents a grid-connected photovoltaic (PV) flyback inverter operating in discontinuous conduction mode (DCM) and controlled through an efficient, reliable, and cost-effective hybrid maximum power point tracking (MPPT) method. Although the proposed method can be applied to any grid-connected inverter topology, in this paper, it is applied on a modified flyback inverter circuit. Moreover, the proposed MPPT method is a two-stage scheme and hence, a hybrid solution, as it consists of a combination of fractional short-circuit current and hill climbing perturb and observe (P $\&$ O) method reformulated. The change in weather condition is accurately detected using the current limit technique such that the difference in short-circuit current and photovoltaic current is monitored continuously. It is demonstrated that the use of current limit enables the system to swiftly track the maximum power point (MPP) in abruptly changing environmental conditions. The proposed MPPT method needs only two sensors for current and voltage measurements and is, therefore, cost effective and reliable. The system is tested through simulations and real-time setup using dSPACE DS1104. The results prove the effectiveness of the proposed hybrid MPPT compared with the P $\&$ O method under uniform and dynamic weather conditions.

Integrated structure and maximum power point tracking control design for wind turbines based on degree of controllability

A linearization model is obtained for a three-bladed horizontal-axis wind turbine (HAWT) consisting of blades and a drive-train. Sensitivity analysis of the degree of controllability (DOC) and maximum power point tracking (MPPT) efficiency with respect to the structural parameters of wind turbines is discussed by numerical simulations. It is observed from the simulation results that higher MPPT efficiency can be achieved with the increase of DOC. Based on the observation, this paper proposes a new integrated design method based on DOC to design and optimize the structural parameters of a HAWT. The designed turbine is tested by the commercial simulation software of wind turbines named Bladed. It is observed from simulations that when using the identical MPPT control strategy, the wind turbine whose structural parameters are optimized for a larger value of DOC can achieve higher MPPT performance.

MPPT in PV systems under partial shading conditions using artificial vision

Maximum power point tracking (MPPT) algorithms should track and extract the maximum power from photovoltaic (PV) systems under any environmental conditions. Most of conventional MPPT methods are able to reach the maximum point when there is only one peak in the P–V characteristic curve but they fail when the solar cells are affected by partial shading conditions due to the fact that multiple peaks appear in the P–V curve. Thus, a local maximum may be reached instead of the global peak. In this work, a new method to accomplish the maximum power point (MPP) under partial shading conditions using artificial vision is presented. The artificial vision uses a webcam to identify in real time the shadow irradiance and provide the reference voltage that supplies the maximum power, regardless of the number of peaks that the P–V curve presents. Then, the reference voltage is used by a robust and non-linear control, the backstepping controller, to regulate the DC/DC converter input voltage and to guarantee the PV modules maximum energy extraction. Experimental tests carried out outdoor validate the proposed method, obtaining a MPP tracking efficiency that ranges from 98.1% to 99.6%.

Comparison of MPPT Systems in Error Optimization using PID, Fuzzy and Hybrid Fuzzy in Multivariable Environment

Recent surveys conducted in the field of Power Control and Engineering show that photovoltaic (PV) systems are currently being discussed worldwide and research on the same is being carried globally. It is necessary to optimize the expanding use of photovoltaic systems through error detection in Maximum Power Point Tracking (MPPT) systems. Through this paper, an attempt is made to develop an efficient photovoltaic MPPT system using hybrid fuzzy technique to extract maximum power under a multivariable environment (changing temperature and irradiance). The MPPT system using Hybrid Controller (combining PID & FLC) has an increased efficiency and optimized output in comparison to the MPPT system using PID and Fuzzy individually. The system has explored a concept of computing academic performance indices with three MPPT models for future research based on global MPP calculation. Citation: Sharma, C., and Jain, A. (2018). Comparison of MPPT Systems in Error Optimization using PID, Fuzzy and Hybrid Fuzzy in Multivariable Environment. Trends in Renewable Energy, 4, 8-21. DOI: 10.17737/tre.2018.4.3.0046

Adaptive Feedback Linearization Based NeuroFuzzy Maximum Power Point Tracking for a Photovoltaic System

In the current smart grid scenario, the evolution of a proficient and robust maximum power point tracking (MPPT) algorithm for a PV subsystem has become imperative due to the fluctuating meteorological conditions. In this paper, an adaptive feedback linearization-based NeuroFuzzy MPPT (AFBLNF-MPPT) algorithm for a photovoltaic (PV) subsystem in a grid-integrated hybrid renewable energy system (HRES) is proposed. The performance of the stated (AFBLNF-MPPT) control strategy is approved through a comprehensive grid-tied HRES test-bed established in MATLAB/Simulink. It outperforms the incremental conductance (IC) based adaptive indirect NeuroFuzzy (IC-AIndir-NF) control scheme, IC-based adaptive direct NeuroFuzzy (IC-ADir-NF) control system, IC-based adaptive proportional-integral-derivative (IC-AdapPID) control scheme, and conventional IC algorithm for a PV subsystem in both transient as well as steady-state modes for varying temperature and irradiance profiles. The comparative analyses were carried out on the basis of performance indexes and efficiency of MPPT.

Optimal design and analysis of hybrid photovoltaic-fuel cell power generation system for an advanced converter technologies

Nowadays, the entire world is concentrated on alternative energy sources (AES) or renewable energy sources (RES) for developing the power in economical cost and the sources like tidal power, solar energy, geothermal energy, wind energy, biomass, fuel cells etc. Among all those sources solar energy and fuel cells are chosen for developing the hybrid power generation (HPG) system. The photovoltaic (PV) module is designed with an efficient maximum power point tracking (MPPT) technique of neuro-fuzzy (NF) tracking controller is developed to extract the maximum power and fed to boost DC-DC converter. In the meanwhile, air breathe fuel cell (ABFC) is designed and fed to the high step-up DC-DC converter with lesser duty cycle. The main concentration of this paper is to design the efficient HPG system for a competitive multilevel inverter (MLI) topology with less device count is the merit of this topology which is called packed U cell (PUC). In addition, this paper describes the mathematical analysis, design and operation of PV module, neuro-fuzzy (NF) MPPT controller based boost converter, ABFC, high step-up converter and PUC inverter. The P-V, I-V characteristics of PV module and ABFC stack effects on hydrogen pressure changes and temperature is examined. And also, the performance of HPG based PV-FC fed MLI is sifted for different load conditions. The overall performance is checked in terms of total harmonic distortion (THD) for phase voltages (Vph) and phase currents (Iph) which are accomplished through FFT analysis for each load case. The whole simulations are carried out in MATLAB/Simulink environment.