Maximum Power Extraction Research Articles

Power Management in Three-Phase Grid-Integrated PV System with Hybrid Energy Storage System

The management of energy in distribution networks has been gathering attention in recent years. The simultaneous control of generation and demand is crucial for achieving energy savings and can further lower energy pricing. The work aims to develop a control scheme for a hybrid microgrid that can provide stability to the bus voltage and effectively manage the power flow. Solar energy is the current trend in renewable energy sources (RES). There is a surge in the installation of solar PV systems both on a large scale and on a small scale, such as rooftop PV systems. Installation of RES at residential premises has to be conducted with a proper power management scheme. The hybrid microgrid for this work consists of a PV system with a boost converter to extract maximum power, a DC-DC bi-directional converter to charge or discharge the hybrid energy-storing devices, and a three-phase AC-DC interlinking converter for exchange of energy with the utility grid. The control and power management scheme checks the voltage of each unit and maintains the power flow according to operating conditions. Disturbances are introduced in the form of load switching and irradiance variation to check the system performance. The system is tested on the MATLAB (R2021a) Simulink platform for varying its different modes of operations. An experimental set-up has been developed with hardware-in-the-loop to validate the simulation results.

Terminal Integral Synergetic Control for Wind Turbine at Region II Using a Two-Mass Model

Mechanical loads considerably impact wind turbine lifetime, and a reduction in this load is crucial while designing a controller for maximum power extraction at below-rated speed (region II). A trade-off between maximum energy extraction and minimum load on the drive train shaft is a big challenge. Some conventional controllers extract the maximum power with a cost of high fluctuations in the generator torque and transient load. Therefore, to overcome the above issues, this work proposes four different integral synergetic control schemes for a wind turbine at region II using a two-mass model with a wind speed estimator. In addition, the proposed controllers have been developed to enhance the maximum power extraction from the wind whilst reducing the control input and drive train oscillations. Moreover, a terminal manifold has been considered to improve the finite time convergence rate. The effectiveness of the proposed controllers is validated through a 600 kW Fatigue, Aerodynamics, Structures, and Turbulence simulator. Further, the proposed controllers were tested by different wind spectrums, such as Kaimal, Von Karman, Smooth-Terrain, and NWTCUP, with different turbulent intensities (10% and 20%). The overall performance of the proposed and conventional controller was examined with 24 different wind speed profiles. A detailed comparative analysis was carried out based on power extraction and reduction in mechanical loads.

Robust reconfiguration strategies for maximum output power from large-scale photovoltaic arrays under partial shading conditions

Extraction of maximum power from large scale solar photovoltaic power systems is the most challenging and demanding research in the current scenario. Solar photovoltaic panels are highly susceptible to a phenomenon known as partial shading. Partial shading increases mismatch losses and reduces the output of the solar photovoltaic system The output reduction in the partially shaded array is proportional to the shaded area, shaded panel’s placement within the array, panel connections, shade geometry, etc. There are several approaches for reducing Partial shading effects in the literature. The most efficient approach to mitigating the mismatch losses due to Partial shading in large-scale solar photovoltaic systems is the reconfiguration technique, which distributes shaded panels more evenly and increases the maximum power output. The current work utilizes a set of reconfiguration rules for selecting the location of shaded panels within an array that allows for multiple reconfiguration options. The results show that the proposed reconfiguration has obtained an improved Performance enhancement ratio of 25% in one shading pattern i.e. short wide shading, Performance enhancement ratio of 6.4% in short narrow and centre shading and Performance enhancement ratio of 5.9% in long narrow shading. The proposed reconfiguration was found to be the most suitable, simple, and cost-effective solution for large size of solar photovoltaic system under all shading conditions.

Design of LQR-based FLC for the Optimal Regenerative Braking Controlling of Solar PV-based Electric Vehicle System

The article presents an analysis of the optimal control of speed and regenerative braking in an electric vehicle (EV). The presence of the continuous generating power is one of the major challenges for battery charging of electric vehicle. In order to meet the demand of continuous power, electric vehicles are driven by solar PV arrays. Initially, maximum power extraction (MPPT) is assessed from a solar photovoltaic (PV) array using the P&O method. The outputs of the solar PV array are integrated with electric vehicles. Such integration creates the problem of maintaining the power quality. The existing methods also address the issue of optimal speed and torque control with high transients and more settling time. In this article, an electric vehicle is modeled first and then operated in regenerative braking mode. To address the shortcomings of existing methods, the linear quadratic regulator (LQR) method is used; then, fuzzy logic controller (FLC)-based LQR is used for optimal speed and torque control during electric vehicle regenerative braking. In terms of reduced settling time and improved peak overshoot, optimal speed and regenerative torque of electric vehicles are better realized with LQR-based FLCs than with LQR controllers. In addition to this, stopping speed characteristics with various electrical parameters (voltage, current, and flux) have been analyzed with different methods in which LQR-based FLC shows its dominance to attain zero speed in regenerative mode with more sharp characteristics.

FPGA Based Integrated Control of Brushless DC Motor for Renewable Energy Storage System

To reduce air pollution and global warming, renewable energy technologies may generate power. Wind, solar PV, and fuel cell energy are the primary sources. Solar PV system-powered brushless direct current motor (BLDC) drives are used in the automobile industry due to their importance. In this study, Sheppard–Taylor (S-T) converter and Pulse Width Modulated (PWM) Inverter-fed BLDC provide steady voltage across the BLDC motor drive independent of solar PV system power output. When renewable energy is scarce, the proposed battery-supercapacitor hybrid energy storage system (BS-HESS) provides electricity. S-T converters may be used for load matching and power processing to create energy-efficient systems and stabilize PV panel output voltage. The variable step size open circuit voltage-Maximum Power Point Tracking (VSSOCV-MPPT) technique in S-T converter switching pulses extracts maximum power from the solar PV system. This study considers the PVSWPS control function as a Port-Controlled Hamiltonian (PCH) system to continue rural growth and reduce the greatest demand and load. MATLAB/Simulink software simulates the system’s performance, and FPGA controllers validate the controller’s real-time performance.

A ±0.5-mV-Minimum-Input DC-DC Converter With Stepwise Adiabatic Gate-Drive and Efficient Timing Control for Thermoelectric Energy Harvesting

This paper presents a step-up DC-DC converter that uses a stepwise gate-drive technique to reduce the power FET gate-drive energy by 82%, allowing positive efficiency down to an input voltage of ±0.5 mV—the lowest input voltage ever achieved for a DC-DC converter as far as we know. Below ±0.5 mV the converter automatically hibernates, reducing quiescent power consumption to just 255 pW. The converter has an efficiency of 63% at ±1 mV and 84% at ±6 mV. The input impedance is programmable from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1~\Omega $ </tex-math></inline-formula> to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$600~\Omega $ </tex-math></inline-formula> to achieve maximum power extraction. A novel delay line circuit controls the stepwise gate-drive timing, programmable input impedance, and hibernation behavior. Bipolar input voltage is supported by using a flyback converter topology with two secondary windings. A generated power good signal enables the load when the output voltage has charged above 2.7 V and disables when the output voltage has discharged below 2.5 V. The DC-DC converter was used in a thermoelectric energy harvesting system that effectively harvests energy from small indoor temperature fluctuations of less than 1°C. Also, an analytical model with unprecedented accuracy of the stepwise gate-drive energy is presented.

A Framework of Reduced Sensor Rooftop SPV System Using Parabolic Curve Fitting MPPT Technology for Household Consumers

In this paper, a novel Parabolic Curve-fitting based Hill Climbing (PCHC) MPPT (Maximum Power Point Tracking) algorithm is developed to extract maximum power from solar photovoltaic (PV) panels under dynamic environmental conditions for household consumers. Moreover, this developed PCHC algorithm is integrated with a novel reduced sensor-based approach, where only a single current sensor is used to complete the solar-powered battery charging process. The ease of implementation with a simple controller and reduced sensor approach makes it economical for residential rooftop SPV. In the proposed PCHC methodology, two consecutive points on the Power-Voltage (P-V) characteristic of PV are used to detect the Maximum point region quickly. Moreover, the parabolic nature of the P-V characteristic near the Maximum Power Point (MPP) zone is explored to calculate the approx value of voltage corresponding to the optimum power. Here in every iteration, the size of the perturbation in duty is reduced by fifty percent. It overcomes the trade-off between tracking speed and oscillations near the MPP of conventional MPPT techniques such as perturb and observe, incremental conductance. These oscillations affect the connected consumers’ load working efficiency and lifetime. Moreover, it also improves the dynamic performance by taking different step sizes for sudden and slow changes in irradiation levels. The boost converter has been used to realize the performance of the proposed PCHC MPPT technique. The performance of the PCHC MPPT algorithm has been validated on different types of irradiation patterns and obtained results that fulfill the motive of the work.

Effect of the Sampling Parameters in FOCV-MPPT Circuits for Fast-Varying EH Sources

The fractional open-circuit voltage (FOCV) method is extensively used in low-power energy harvesting (EH) sources to extract maximum power. For fast-varying EH sources, a fast sampling rate is required. This work theoretically analyzes the influence of the sampling time and period on the harvested power of sinusoidal EH sources. In addition, the circuit limitations to achieve a fast sampling rate are presented and circuits to deal with them proposed and implemented. Furthermore, one of the circuits is based on a novel pseudoFOCV method and achieves the fastest sampling rate. Experimental tests are performed with a 2 Hz, 1 to 3 V sinusoidal source having an output resistance of 127 Ω, and the results are shown to agree with theoretical predictions. It is shown that the harvested power increases with the sampling rate when the sampling time is negligible (sampling 15 times faster than the source frequency extracts around 99% of the maximum), and for fixed sampling times, there is an optimum sampling rate where the harvested power is maximum. The first result is generic and valid for methods other than the FOCV. Tests were also performed with a small-scale wave energy converter placed in a linear shaker emulating a sea environment. Harvested power increases by 25% with respect using a commercial FOCV unit with a low sampling rate.

Independent MPPT and voltage regulation of dual input DC - DC converter with a voltage multiplier cell

ABSTRACT A dual input boost DC–DC converter (DIBC) with combined voltage multiplier cell, the larger duty ratio (greater than 0.5), and the overlapping switching signal are required to obtain high voltage gain. This paper investigates the independent maximum power point tracking (MPPT) implementation on two solar photovoltaic (PV) energy sources along with the output voltage regulation of the DIBC during load and input voltage disturbances. For maximal power extraction, a single ended primary-inductance converter (SEPIC) is designed at each input, one with the perturb and observe (P and O) approach and the other with the incremental conductance algorithm. The small-signal transfer function model is used to design the voltage regulator. The MPPT algorithms for maximum power extraction as well as the inner current-loop and outer voltage-loop control approach have been implemented simultaneously. Duty ratio of the DIBC MOSFETs as a function of the converter output voltage and duty ratio of the SEPIC MOSFET as a function of MPPT are used to generate the switching signals. An experimental two 100W PV sources are developed using real-time solar simulator with the 200 W DIBC and controller is designed using XILINX SPARTAN-6 FPGA board. MATLAB simulation and experimental results ensure the active current sharing among the sources, reference output voltage (156.6 V) tracking, voltage regulation (below 5%) under different scenarios, and independent MPPT simultaneously.

Intelligent Control Schemes for Maximum Power Extraction from Photovoltaic Arrays under Faults

Investigation of power output from PV arrays under different fault conditions is an essential task to enhance performance of a photovoltaic system under all operating conditions. Significant reduction in power output can occur during various PV faults such as module disconnection, bypass diode failure, bridge fault, and short circuit fault under non-uniform shading conditions. These PV faults may cause several peaks in the characteristics curve of PV arrays, which can lead to failure of the MPPT control strategy. In fact, impact of a fault can differ depending on the type of PV array, and it can make the control of the system more complex. Therefore, consideration of suitable PV arrays with an effective control design is necessary for maximum power output from a PV system. For this purpose, the proposed study presents a comparative study of two intelligent control schemes, i.e., fuzzy logic (FL) and particle swarm optimization (PSO), with a conventional control scheme known as perturb and observe (P&amp;O) for power extraction from a PV system. The comparative analysis is based on the performance of the control strategies under several faults and the types of PV modules, i.e., monocrystalline and thin-film PV arrays. In this study, numerical analysis for complex fault scenarios like multiple faults under partial shading have also been performed. Different from the previous literature, this study will reveal the performance of FL-, PSO-, and P&amp;O-based MPPT strategies to track maximum peak power during multiple severe fault conditions while considering the accuracy and fast-tracking efficiencies of the control techniques. A thorough analysis along with in-depth quantitative data are presented, confirming the superiority of intelligent control techniques under multiple faults and different PV types.

A review of PV array reconfiguration techniques for maximum power extraction under partial shading conditions

Partial shading is a significant obstacle to the effective use of photovoltaic (PV) systems because it reduces output power significantly. The output power reduction is not proportional to the shaded area but rather depends on the PV array configuration/reconfiguration and shadowing pattern. PV array reconfiguration is one of the most effective solutions for overcoming the adverse effects of partial shading in PV systems. The main objective of PV array reconfiguration strategies is to disperse shades consistently over the entire area of the PV array to reduce the adverse impact of partial shading situations. This paper provides an in-depth examination of the significant existing PV array reconfiguration methods used to address the problem of partial shading. The various methods are evaluated and compared based on their techniques, benefits, and drawbacks. This work is an interesting reference for researchers in the field and a simple guide for beginners on PV array reconfiguration.

Hill-climbing search (HCS) MPPT algorithm for hydrokinetic energy harnessing

Hydrokinetic turbines based on rivers are environmentally friendly technology that has increased interest in advanced scientific research during the last decade. The kinetic energy formed from the water stream can be harnessed as long as the water is flowing. Nevertheless, the variation and fluctuation of water current speed and turbulence flow in a river is the main issue, especially in designing a control system that can harness the maximum output with high efficiency. Various methods and techniques have been applied in hydrokinetic energy conversion systems to extract maximum power. This paper presents the performance of the Hill Climbing Search (HCS) MPPT Algorithm in hydrokinetic energy harnessing in terms of steady-state oscillation, time tracking, and efficiency. The model of hydrokinetic energy harnessing is developed using MATLAB/Simulink that comprises a water turbine, permanent magnet synchronous generator (PMSG), passive rectifier, and DC boost converter. The MPPT algorithm can be employed in the DC boost converter by regulating the ratio of the duty cycle. The results show the HCS MPPT algorithm reduced the steady-state oscillation, rapid time tracking and improved 93.75% of efficiency.

Study on the power extraction performance of a flapping airfoil power generator using jet flow method

Flapping airfoil power generator (FAPG) is becoming popular due to high-power extraction with low noise. However, the effect of a combined jet of suction and blowing on the power extraction performance of the flapping airfoil is not fully explored. The present study presents a flapping airfoil model with a compound jet of suction and blowing, and the jet parameters were optimized using the Taguchi method and CFD approach for the maximum power extraction efficiency of the airfoil. It was found that the power extraction efficiency of the flapping airfoil can be improved by applying the compound jet to the trailing edge of the airfoil. Compared to the baseline NACA0015 airfoil, the optimized jet parameters lead to the maximum improvement in efficiency by 38.14%. The analysis of flow field characteristics of the flapping airfoil reveals that the optimal jet parameters can not only enhance the strength of the vortex on airfoil but also improve the vortex motion mechanism, which results in a greater lift of airfoil and better synergy between the lift and the plunging velocity.

Fault Diagnosis Strategy for a Standalone Photovoltaic System: A Residual Formation Approach

The search for sustainability and green energy, in electricity production, has lead many researchers to study and improve photovoltaic (PV) systems. The PV systems, being a combination of power electronic modules and PV array, have high tendency of faults in sensors, switches, and passive devices. Thus, a reliable fault diagnosis (FD) scheme plays a significant role in protecting PV systems. In this article, a sliding mode observer (SMO)-based FD scheme is presented to figure out the sensor faults in a standalone PV system. The proposed FD scheme makes use of residual formation which in turn helps in detection of faults on the basis of a defined threshold. In addition to the functionality of fault detection, the SMO provides the benefit of reduction in number of sensors required in the PV system. This feature can be utilized as software redundancy in fault-tolerant control (FTC). The test bench, standalone PV system, is equipped with a buck–boost converter for maximum power transfer (MPT) to the connected load. Moreover, the FD scheme is backed by a back-stepping (BS) analogy-based control scheme for extraction of maximum power from the PV panel. The simulations are performed in the MATLAB/Simulink platform under varying environmental conditions (temperature and irradiance) and resistive load. These simulations, subjected to varying operating conditions, confirm the efficacy, in terms of robustness, chattering (oscillations about the reference), and steady-state error, of the proposed scheme.

A multi-objective honey badger approach for energy efficiency enhancement of the hybrid pressure retarded osmosis and photovoltaic thermal system

The pressure retarded osmosis process is emerging as one of the most promising technologies for extracting renewable energy from salinity gradient resources. The hybrid system of the pressure retarded osmosis and photovoltaic/thermal systems is capable of effectively improving overall energy efficiency. The prime research focus of hybrid energy systems is to produce environment-friendly solutions by minimizing energy consumption and improving energy efficiency. Due to the increasing demand for intelligent computing, the challenges of maximum power extraction and efficient energy management have attracted the attention of researchers around the world. Thus, a Honey Badger Approach based energy management strategy is proposed to solve the problem of performance enhancement in the pressure retarded osmosis and photovoltaic/thermal system by maximizing the multi-variable functions. The Honey badger approach uses global sight to tackle the optimization of multiple objectives and to achieve optimal solutions. The proposed energy management method is tested with various types of operational environments, including variations in the operational temperature, solar irradiance and ambient temperature in regard to detrimental effects. The practical hourly data of Perth for a year is utilized to simulate the actual operating conditions. The simulation results indicate that the proposed energy management method overwhelms other competing approaches with better energy efficiency, thereby ensuring the continuity of energy supply and improving the reliability of the system.

Integrated Duty Cycle Control for Multiple Renewable Energy Sources in a Grid Connected System

Due to their abundance, affordability, and clean energy production, Renewable Energy Sources (RESs) have emerged as crucial sources of electricity production. As a result, considerable effort has been made to integrate renewable energy sources into the grid to help it meet energy demands. One of the challenges is the Maximum Power Extraction (MPE), where the maximum power needs to be extracted from each RES. The cost of implementation rises linearly with the number of RESs if the MPE arrangements are being made for each RES individually. Additionally, the MPE through multiple RES systems gets more challenging, especially when several PhotoVoltaic (PV) strings are connected and each PV string receive non-uniform irradiance. This paper proposes an integrated MPE control system for a multi-RES grid-connected system. The proposed solution uses a single microcontroller to maximize power from all sources to overcome the linearly growing cost problem. Moreover, we propose an improved Multi-Dimensional Cuckoo (MDC) algorithm for MPE to tackle the non-uniform irradiation problem with multi-string PV, in contrast to prior works with grid-connected multiple sources. The proposed technique is first put up against the individual MPE control system, and then it is put up against the Jaya algorithm that is documented in the literature for a typical one-dimensional MPE.

Real-Time Control and Power Management Strategies of PV/Battery Standalone System

In this paper, novel control and power management strategies based on the fuzzy logic of an autonomous PV/battery system suitable to water pumping applications is proposed and experimentally validated. The PV panel provides the steady-state energy demand according to the climatic conditions and the battery ensures the energy balance at the load level (PMDC motor unit). The system includes two converters, a unidirectional DC-DC converter, and a bidirectional DC-DC converter, which are used as intermediaries between the DC bus, the PV, and the battery respectively. The maximum power extraction (MPP) is ensured via a feed-forward neural network-based MPPT, generating the appropriate duty cycle for the primary converter. The power management system and the control strategy allow the generation of reference currents within the limits of the battery's state of charge. Experimental studies on a prototype system have been performed to verify the effectiveness of the proposed approaches.

Stable Maximum Power Extraction and DC Link Voltage Regulation for PMVG-Based WECS

This study discusses the power maximization and dc-link voltage regulation problems of a permanent magnet vernier generator (PMVG)-based wind energy conversion system. To do this, first, the dynamical model of PMVG-based wind turbine is developed and presented. Then, the overall control structure is configured utilizing a back-to-back converter with a machine-side converter (MSC) and a grid-side converter (GSC). At this time, the sliding-mode control scheme with the modified enhanced exponential reaching law is proposed for both MSC and GSC control to achieve maximum power extraction and stable dc link voltage, respectively. Furthermore, the sliding manifold’s stability condition is derived using the Lyapunov function, which guarantees a better transient performance and tracking accuracy. Finally, the proposed control scheme’s superiority and efficiency are demonstrated using theoretical simulations on 5 kW PMVG-based and 1.5 MW permanent magnet synchronous generator-based wind turbine systems and empirical findings derived from a grid-connected 5 kW PMVG-based wind turbine in the experimental setup.

Maximum Power Extraction for PMVG-Based WECS Using Q-Learning MPPT Algorithm With Finite-Time Control Scheme

This study is concerned with the problem of maximum power extraction for a permanent magnet vernier generator (PMVG)-based wind energy conversion system (WECS) using the Q-learning maximum power point tracking (MPPT) algorithm with the finite-time control (FTC) scheme. To do this, the model-free sensorless reinforcement Q-learning algorithm-based MPPT method is firstly proposed. At this time, the reward and learning rate are updated by the Q-values for each state-action pair. Next, the proposed learning algorithm is used to construct an optimal speed–power curve for achieving the fast and steady MPPT operation for the WECS using the learned action values. Besides, the wind-speed change detection algorithm is added to the proposed method so that the PMVG-based WECS can work in various wind speed conditions. And then, the FTC method is proposed to track the reference speed of PMVG which support to achieving the maximum power extraction, and Lyapunov stability theory is derived to ensure the overall system's stability. Finally, the simulation and experimental results from the 5 kW PMVG-based WECS are presented to demonstrate the applicability and superiority of the proposed control method.

An Improved Angular Stator Flux Frequency Computation Method for Robust MPPT Operation of DFIG Under Unbalanced Grid Voltage

Maximum power extraction and constant power generation in a smooth and uninterrupted manner are challenging control tasks for the robust operation of DFIG under grid voltage dips, owing to severe power and torque pulsations. Thus, necessitating tailored power control strategies while curtailing the undesirable effects on DFIG performance under voltage dips. The crux of this paper is to compute the angular stator flux frequency for precise reference power generation and control of DFIG subjected to grid voltage unbalance especially during MPPT operation. The angular frequency of stator flux is computed with the stator voltage and current components in the positive sequence stationary <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">α-β</i> reference frame without the need for a PLL and differentiation of stator voltage vector. Further, the computed stator flux frequency signal is employed for rotor speed computation, and reference power generation for maximum power extraction from DFIG. The efficacy of the proposed method in enabling precise power control of DFIG under unbalanced grid voltage is demonstrated using simulations in PSCAD/EMTDC and further through test results on a 3 hp DFIG test set up. The overall results show enhanced performance of DFIG under MPPT with the proposed scheme.