Observe Maximum Power Point Tracking Research Articles

A regularized fourth-order adaptive method for seamless integration of charging station to the grid for EV and critical loads

ABSTRACT This paper proposes a real-time implementation and regularised fourth-order adaptive (RFOA) method of three-phase grid connectedsolar photo voltaic (SPV) array and battery-based charging station. The proposed system mainly uses a solar photovoltaic array and battery system to reduce the burden on the grid. The system feeds the surplus energy to the grid as well as operates during the outage and support the EV and home loads/critical loads. To minimise the error at various operating scenarios, the RFOA method is utilised for voltage source converter (VSC). The battery is integrated with DC link with the help of bi-directional converter. It works in boost mode when it is discharging and works in buck mode when it is charging. The perturbation & observation (P&O) maximum power point tracking (MPPT) is used to generate the reference DC link voltage. In order to improve the power quality of the charging station, the proposed system is designed to act as an active filter, load leveller, power factor corrector and reduce the harmonics to 5% as per IEEE 519 standards. The proposed charging is examined for different balanced and unbalanced load conditions and at the different environmental situations in MATLAB/Simulink based platform as well as in experimental test bed based on OPAL-RT platform.

A New Dragonfly Optimized Fuzzy Logic-based MPPT Technique for Photovoltaic Systems

Photovoltaic (PV) power systems should be operated at the maximum power point (MPP) for best solar energy utilization, which can be achieved using maximum power point tracking (MPPT) techniques. Perturb & Observe (P&O) and Fuzzy logic MPPT approaches were two of the various strategies that were suggested as effective ways to achieve Maximum Power under Continuous Irradiation. When exposed to changes in environmental conditions, these approaches perform poorly dynamically and exhibit substantial steady-state oscillations around the MPP. To overcome this problem, this paper proposes the Dragonfly optimization-based fuzzy logic MPPT approach for maximum power extraction of photovoltaic (PV) systems. The approaches for implementing FL-based MPPTs that are currently available are not adaptable to the operating point, which varies widely in real-world PV systems with operational irradiance and ambient temperature. The proposed MPPT (DAFLC-MPPT) is straightforward, accurate, and offers quicker convergence to the optimal operating point. With consideration of various operating situations at slow and fast changes in solar radiation, the efficacy and viability verifications of the proposed AFL-MPPT approach are validated. The proposed strategy outperforms the standard P&O and fuzzy logic methods.

Study of a New Wave Energy Converter with Perturb and Observe Maximum Power Point Tracking Method

Ocean waves contain the highest energy density among renewable energy sources. However, harnessing the energy from ocean waves represents a challenge because wave energy converters (WECs) must be designed to have great survivability and efficiency. The power production challenge of any WEC depends on the power take-off (PTO) system efficiency. Maximum power point tracking (MPPT) algorithms have been widely applied in renewable energy from photovoltaic and wind sources, and have subsequently been adapted to wave energy converters (WECs). Energy extraction is optimized by applying MPPT, resulting in an increase in efficiency. This study aims to address the analysis of the influence of the perturb and observe MPPT in the electrical power performance of a WEC composed of a point absorber, a hinged arm and a direct mechanical drive PTO system. The PTO is characterized by a pulley system, a counterweight, one-way bearings, a gearbox, a flywheel and an electric generator; in the present study it is considered to be a cylindrical point absorber. The linear theory and the viscous damping effect are applied to analyze the hydrodynamic behavior of the point absorber. Regarding the two generators considered in the present study, the contribution of MPPT is greater for the low power generator; the high values of the capture width ratio (CWR) occur at low values of period and wave height, showing the maximum value in the high-power generator.

PV Integrated UPQC with Intelligent Control Techniques for Power Quality Enhancement

The configuration and control of a Unified Power Quality Conditioner (UPQC) coupled with Photovoltaic (PV) system is proposed in this work. By integrating PV to UPQC, the twin advantages of decarbonized clean energy generation in addition to enhanced Power Quality (PQ) is obtained. The series and shunt compensators, which together constitute the UPQC are sequentially interfaced to the common dc-link. In addition to infusing active PV generated power, the UPQC shunt compensator diminishes the load side power quality concerns. The role of a series compensator is to ensure that both the load and source voltages are in-phase perfectly. The PV system is integrated to the UPQC through a DC/DC Interleaved Cuk converter and by regulating the duty cycle of the Interleaved Cuk converter, utmost possible power is derived from the PV using Crow Search Algorithm (CSA) assisted Perturb and Observation (P & O) Maximum Power Point Tracking (MPPT) technique. The designed hybrid MPPT technique is capable of operating at Maximum Power Point (MPP) under both Partial Shading Condition (PSC) and uniform insolation condition. A d-q theory-based control is employed with the assistance of Proportional Integral (PI) controller for controlling the working of UPQC. The dynamic working of the PV based UPQC is evaluated on the basis of simulation outcomes attained from MATLAB.

Design and analysis of an efficient photovoltaic energy-powered electric vehicle charging station using perturb and observe MPPT algorithm

According to the current directive, we must rely on green energy for sustainable mobility. One of the green transition’s goals is to use renewable energy to charge electric vehicles (EVs). Solar energy is a form of renewable energy sources, and it is classified as being clean, available, and renewable because it is based on sunshine. Nowadays, the world is turning to EVs which have lower running costs and cleaner environments. Lithium-ion batteries are commonly utilized to store energy in EVs. This article covers the design and analysis of a photovoltaic (PV) system to charge five models of EVs such as BMW i3 2019, Volkswagen e-Golf, Fiat 500e, Mercedes EQA 250, and Hyundai Kona Electric in a DC fast charging mode by using a buck converter to minimize the output voltage and without any addition of energy storage. By applying Perturb & Observe (P&O) Maximum Power Point Tracking (MPPT), the maximum power and efficiency from PVs are obtained. The charging time is calculated for each EV of the five models in the State of Charge (SOC) area at 20–80 percent. A MATLAB program is employed to simulate the EV models by calculating the efficiency of the MPPT controller, time of charging, and characteristic of voltage and current levels for each model of these EVs. All models are tested under the condition of irradiance level from 600 W/m2 to 1000 W/m2 and temperature between 20°C and 30°C. The results showed that the PV system is effective and economical as a stand-alone to charge EVs in a rapid charge mode.

An Innovative Adaptive Perturb and Observe Maximum Power Point Tracking Method for Photovoltaic Systems Using Illuminance Level as Perturbation Signal

In solar photovoltaic (PV) system applications, one of the most important tasks is to extract maximum power from PV arrays with minimum losses. Maximum power point tracking (MPPT) is a commonly used method to maximize power extraction from PV systems under all environmental conditions. In this paper, a modified perturb and observe (P&O) tracking method using an interleaved DCDC buck converter is proposed and compared with the traditional method. The proposed method uses illuminance level as the perturb signal to control the converter’s duty cycle under varying solar radiation conditions. The results validate the speed and effectiveness of the method, which is centring illuminance level comparing its performance to the traditional P&O method.

Photovoltaic Energy Conversion Systems with Sliding Mode Control

A new sliding-mode-control-based power conversion scheme is proposed for photovoltaic energy conversion systems. The perturbation and observation (P&O) maximum power-point tracking (MPPT) approach is adopted for optimizing the power generation capabilities from solar panels. Due to the inherent nonlinear dynamics of power converters, we need to adopt a nonlinear control approach to optimize the energy conversion efficiency and tolerate the fluctuations and changes of load and sunlight irradiance. In this manuscript, novel first-and higher-order sliding mode control approaches are proposed, aiming to provide a systematic approach for the robust and optimal control of solar energy conversion, which guarantees Lyapunov stability and consistent performance in the face of external perturbations and disturbances. Moreover, to eliminate the chattering phenomenon inherent in the first-order approach, super-twisting second-order sliding mode control is developed for the buck-boost converter. Furthermore, the output of DC–DC converter supplies a voltage-oriented-control (VOC)-based space-vector pulse-width-modulated inverter to generate three-phase AC power to the grid. To demonstrate the robustness and effectiveness of the proposed scheme, computer simulations and dSPACE hardware-in-the-loop platform have been carried on for examining the proposed sliding-mode-control-based solar energy conversion system.

New Control Scheme for Solar Power Systems under Varying Solar Radiation and Partial Shading Conditions

The traditional perturbation and observation (P&O) maximum power point tracking (MPPT) algorithm of a structure is simple and low-cost. However, the P&O algorithm is prone to divergence under solar radiation when the latter varies rapidly and the P&O algorithm cannot track the maximum power point (MPP) under partial shading conditions (PSCs). This study proposes an algorithm from the P&O algorithm combined with the solar radiation value detection scheme, where the solar radiation value detection is based on the solar photovoltaic (SPV) module equivalent conductance threshold control (CTC). While the proposed algorithm can immediately judge solar radiation, it also has suitable control strategies to achieve the high efficiency of MPPT especially for the rapid change in solar radiation and PSCs. In the actual test of the proposed algorithm and the P&O algorithm, the MPPT efficiency of the proposed algorithm could reach 99% under solar radiation, which varies rapidly, and under PSCs. However, in the P&O algorithm, the MPPT efficiency was 96% under solar radiation, which varies rapidly, while the MPPT efficiency was only 80% under PSCs. Furthermore, in verifying the experimental results, the proposed algorithm’s performance was higher than the P&O algorithm.

2-D lookup table based MPPT: Another choice of improving the generating capacity of a wave power system

Although the fixed-step Perturbation and Observation Maximum Power Point Tracking (P&O MPPT) is a commonly applied algorithm for wave power generation, its tracking performance is weakened in irregular waves. To overcome the disadvantage, this paper proposes a novel 2-D lookup table based (2DLTB) MPPT scheme. It utilizes a 2-D optimal-duty-cycle table and real-time wave data to tune the duty cycle of pulse-width-modulation (PWM) signal. Two tuning methods are introduced. The first one is called single-wave-period regulation (SWPR), which adjusts the duty cycle wave by wave. The second one named multiple-wave-period regulation (MWPR) tunes the duty cycle at intervals of multiple wave periods. Both 2DLTB MPPT and the fixed-step P&O MPPT are simulated and compared in different irregular waves generated from the real sea states. Results show that 2DLTB MPPT is insensitive to the number of waves. However, the fixed-step P&O MPPT is sensitive to both update duration and step size. Meanwhile, 2DLTB MPPT has the stronger power tracking performance than the fixed-step P&O MPPT. In addition, SWPR outperforms MWPR in the short time window, while MWPR performs better in the long time window. In general, as a simple, reliable and excellent MPPT algorithm, 2DLTB MPPT is worthy of promotion.

A Novel High-Gain Soft-Switching DC-DC Converter With Improved P&O MPPT for Photovoltaic Applications

This paper proposes a novel high voltage gain structure of DC-DC converter with soft-switching ability for photovoltaic (PV) applications. A small size coupled inductor with one magnet core is utilized to improve the voltage conversion ratio in the proposed converter. The converter has one active MOSFET with low conducting resistance ( $R_{DS}-_{ON}$ ), which in turn reduces the conduction losses and complexity of the control section. Due to the low input current ripple, the lifetime of the input PV panel is increased, and the maximum power point (MPP) of the PV panel can be easily tracked. The MOSFET’s zero-voltage and zero-current switching and diodes are the other countenance of the proposed converter, which improve its efficiency. Additionally, an improved Perturb and Observe MPP tracking (IP&O MPPT) algorithm is introduced to boost the extracted power of the input PV sources. To validate the performance of this converter, the operation modes principle, steady-state and efficiency survey, and comparison results with other same family converters are carried out. Finally, an experiential prototype is built with 20 V input, 200 V output, power rate of 200 W, and 50 kHz operating frequency to validate the mathematical analysis and effectiveness of the proposed structure. The efficiency of the proposed converter was estimated by over 95% at various power levels.

Design and Control of Medium-Voltage Multilevel Converter for Direct Grid Integration of Photovoltaic System

This paper deals with the design and control of a medium voltage cascaded H-bridge (CHB) multilevel converter for the direct grid integration of a large photovoltaic (PV) system. It presents the design considerations for selecting an optimum number of levels in the multilevel converter, which are to be both efficient and economical. This system is designed for medium voltage, 11 kV, and hence it can be directly interfaced with the grid without a step-up transformer. It contributes large cost savings in the installation, operation and maintenance of the large solar plant. With the increased number of levels, the converter output voltage waveform is a good approximation to the sine waveform. Therefore, the total harmonic distortions (THDs) of the output AC converter voltage and the grid current are reduced, which significantly improves the power quality of the output voltage waveform reducing the size and hence the cost of the filter. The effect of an increased number of levels on THDs is also studied. The control employed is a decoupled control with the synchronous reference frame—phase-locked loop (SRF-PLL), and a 19-level cascaded converter is operating at the low switching frequency. The separate improved perturb and observation (P&O) maximum power point tracking (MPPT) algorithm is used for tracking the maximum power from each array of the multistring solar photovoltaic (SPV) system. Both steady-state and dynamic performances of the system are simulated in MATLAB/ Simulink environment and validated in accordance with the IEEE-519 standard. A substantial reduction in THDs of the output AC converter voltage and the grid current, with increased number of levels, is observed in this system.

Detailed modeling of a thermoelectric generator for maximum power point tracking

Thermoelectric generators (TEGs) are used in small power applications to generate electrical energy from waste heats. Maximum power is obtained when the connected load to the ends of TEGs matches their internal resistance. However, impedance matching cannot always be ensured. Therefore, TEGs operate at lower efficiency. For this reason, maximum power point tracking (MPPT) algorithms are utilized. In this study, both TEGs and a boost converter with MPPT were modeled together. Detailed modeling, simulation, and verification of TEGs depending on the Seebeck coefficient, the hot/cold side temperatures, and the number of modules in MATLAB/Simulink were carried out. In addition, a boost converter having a perturb and observation (P & O) MPPT algorithm was added to the TEG modeling. After the TEG output equations were determined, the TEG modeling was performed based on manufacturer data sheets. Thanks to the TEG model and the boost converter with P & O MPPT, the maximum power was tracked with a value of 98.64 % and the power derived from the TEG was nearly unaffected by the load changes. The power outputs obtained from the system with and without MPPT were compared to emphasize the importance of MPPT. These simulation values were verified by using an experimental setup. Ultimately, the proposed modeling provides a system of TEGs and a boost converter having P & O MPPT.

Critical Assessment of a PV Utility Tied System using P&O MPPT Technique under Dynamic Loaded Conditions

This paper discusses the modelling and simulation of a Solar Photovoltaic (SPV) grid integrated system using parallel topology to accomplish load demand. Maximum Power Point Tracking (MPPT) control is employed for the determination of maximum power level under variable solar radiation and ambient temperature levels. Proportional Integral (PI) type voltage and current controllers have been employed for generating a required switching control signal. Under changing environmental conditions, Perturb & Observe (P&O) MPPT algorithm tracks the DC reference signal and controls the current regulator to obtain the maximum power from SPV array. It has been found that MPPT control tracks the maximum DC link voltage around reference value even under dynamic conditions. Voltage and current measurements have been performed at various Point of Common Couplings (PCCs) under changing environmental conditions. Voltage Source Converter (VSC) and utility grid values have also been compared. MATLAB results obtained through two case studies justify the implementation of our proposed system which is beneficial for research engineers working in various power quality assessment studies.

Adaptive multi-variable step size P&O MPPT for high tracking-speed and accuracy

Improvement of the output power under different weather conditions is one of the major concerns for photovoltaic (PV) system design. The perturbation and observation (P&O) maximum power point tracking (MPPT) algorithm is the most commonly used technique in practice due to its simplicity and ease of implementation in low-cost hardware. However, the conventional fixed-step P&O tracking method uses a fixed iteration step size based on the requirements of the steady - state accuracy and the speed of the algorithm. In addition, it is very hard to specify the variable step-size scaling factor (M) under fast ripped change of insolation. This paper presents an adaptative multi-variable step-size to solve the trade-off between the speed of the algorithm and efficiency at steady-state. Computer simulation is carried out on MATLAB/Simulink to validate the performance of the proposed algorithm. By using multi-variable step-size algorithm, MPPT response speed and accuracy can be significantly enhanced under rapid change of irradiance compared to one scaling variable step-size P&O method.

Solar PV based Permanent Magnet Synchronous Motor Drive for Water Pumping Application

In remote and hilly areas water pumping for domestic usage can induce heavy cost due to high cost of power transmission to those areas. The utilization of solar photo voltaic (SPV) energy is progressive at these areas. The conversion efficiency of SPV is increased efficiently by improving Maximum power-point tracking (MPPT) techniques which are easier, low cost and can be implemented on existing SPV systems. Moreover, using PMSM drive for water pumping will reduce the size requirement of SPV compared to Induction motors (IM) and brushed DC motors and also PMSM provides almost no maintenance. Keeping in view the present requirement, this project proposes an SPV powered PMSM water pumping drive with Perturb&Observe(P&O) and Incremental-Conductance (INC) MPPT techniques for optimizing the efficiency of SPV.

A model predictive control-based hybrid MPPT method for boost converters

ABSTRACTIn this study, Perturb and Observe Maximum Power Point Tracking algorithm and Model Predictive Control (MPC) algorithm are combined to improve the dynamic performance of the control structure of boost converters used in renewable energy systems. For this purpose, a digital control method that does not need any comparator is developed. The maximum power point current value is determined from the Maximum Power Point Tracking (MPPT) algorithm and it is used as the reference for current control operation in the MPC algorithm. Dynamic capability and tracking performance of the proposed control method is validated by simulation and experimentally. The dynamic behaviour of the control algorithm is analysed by carrying out step change tests. Results show that the control method has excellent dynamic performance thanks to its feature of reference tracking in only one switching period. Furthermore, overshoots and undershoots are successfully eliminated.

A Novel Grid Integrated Perturb and Observe Maximum Power Point Tracking Controlled Photovoltaic Power Plant for Power Enhancement

Solar Photovoltaic power generation shows considerable growth in the past decades. In the grid integrated PV system require MPPT controller to improve the efficiency of the power harvested from the plant due to nonlinearity nature of PV module. Among many MPPT Technique P&O has adaptive tracking, reduced oscillation around MPP. In this paper the Perturbation and Observation based MPPT algorithm with adaptive duty ratio generation is used. In this Paper in addition to PV power generation it is used for the power correction of the utility grid by injecting the power to balance the system during unbalanced load condition. Simulation of the proposed concept is run in the MATLAB 2018/Simulink environment.

DC-Microgrid System Design, Control, and Analysis

Recently direct current (DC) microgrids have drawn more consideration because of the expanding use of direct current (DC) energy sources, energy storages, and loads in power systems. Design and analysis of a standalone solar photovoltaic (PV) system with DC microgrid has been proposed to supply power for both DC and alternating current (AC) loads. The proposed system comprises of a solar PV system with boost DC/DC converter, Incremental conductance (IncCond) maximum power point tracking (MPPT), bi-directional DC/DC converter (BDC), DC-AC inverter and batteries. The proposed bi-directional DC/DC converter (BDC) lessens the component losses and upsurges the efficiency of the complete system after many trials for its components’ selection. Additionally, the IncCond MPPT is replaced by Perturb & Observe (P&O) MPPT, and a particle swarm optimization (PSO) one. The three proposed techniques’ comparison shows the ranking of the best choice in terms of the achieved maximum power and fast—dynamic response. Furthermore, a stability analysis of the DC microgrid system is investigated with a boost converter and a bidirectional DC-DC converter with the Lyapunov function for the system has been proposed. The complete system is designed and executed in a MATLAB/SIMULINK environment and validated utilizing an OPAL real-time simulator.

Current correction and fuzzy logic optimizations of Perturb & Observe MPPT technique in photovoltaic panel

This paper presents a two-way optimization of the Perturb & Observe (P&O) maximum power point tracking (MPPT) technique using current correction and fuzzy logic techniques. In fact, photovoltaic (PV) energy has become more and more coveted today. In the future, it will become a necessity. To ensure its optimization, maximum operating point tracking method is considered as a technological key in PV systems. One of the most used MPPT methods is the P&O technique. In this paper, we will focus on optimizing this method based on two techniques. A first attempt has been made to estimate a current correction of the P&O algorithm in case of illumination variation. Then, fuzzy logic optimization attempt had been highlighted to improve power loss. It is shown that both proposed techniques are very effective and allow considerable improvement of accuracy and are less affected by sudden variation of climatic parameters. The proposed approaches are tested via Matlab software and compared the classical P&O algorithm. Through applications, we could conclude that the two optimized proposed methods offer a remarkable improvement concerning power losses.

A Fuzzy Logical-Based Variable Step Size P&O MPPT Algorithm for Photovoltaic System

This paper presents a Modified Perturb & Observe (P&O) Maximum power point tracking (MPPT) algorithm using fuzzy logic-based variable step size to overcome some of the limitations associated with the conventional P&O MPPT tracking method to improve the transient response and reduce the steady-state terminal voltage oscillations. The proposed MPPT algorithm was implemented and tested on an indoor emulated PV source that is constructed from a conventional solar panel and a DC power supply, a boost DC-DC converter and a dSPACE-based MPPT controller. The advantage of implementing this testing platform for MPPT is easy implementation and indoor testing of MPPT algorithms and DC-DC power converters. Thus, dependency on atmospheric conditions such as irradiance level can be avoided. Details of the emulated PV source mathematical model and electrical characteristics, the proposed MPPT algorithm via dSPACE, simulation and test results were presented in the paper.