Maximum Power Point Tracking Capability Research Articles

A new approach to instantaneous power based control of DFIG using active disturbance rejection control

This paper presents the design and control of a wind energy converter system that uses a doubly fed induction generator. It introduces a model that incorporates instantaneous active and reactive power as state variables to represent both the stator and rotor sides of the doubly fed induction generator. Subsequently, a linear active disturbance rejection-based control regulator is proposed for the control loops. The parameters of the linear active disturbance rejection controllers (ADRC) are adjusted by two methods: the single parameter tuning approach and the genetic algorithm (GA) method. The performance of the suggested controller is ultimately compared with a tuned proportional-integral (PI) control regulator in the MATLAB environment. In order to examine the performance of the system, various test scenarios are taken into account. These scenarios include different percentages of load change in both sub-synchronous and super-synchronous modes of operation, faults with different fault periods are considered in both modes of operation. The conventional PI controller-based approach requires 35 control cycles to reach steady state under load change conditions and 50 control cycles under symmetrical fault conditions, regardless of whether the system is operating in sub synchronous or super synchronous mode. The single parameter-based tuned ADRC approach only requires 15 control cycles for load change and 20 control cycles for symmetrical fault scenarios. In contrast, for both the load change and symmetrical fault scenarios, the ADRC with GA-based parameter tuning reaches steady state in just 5 control cycles. Furthermore, a case involving wind speed variation is presented to demonstrate the maximum power point tracking capability of the proposed control structure. Similarly, for the robustness test of the control regulator, variations in resistance and inductance are introduced to observe their impact on the response of the control regulators. Finally, a real-time hardware in loop setup is presented to validate the control strategy during the load change in the sub-synchronous mode of operation of the doubly fed induction generator.

Leveraging MPPT capability for solar irradiance estimation: H-INC-IBS-based assessment of explicit models under real-world climatic conditions

This research investigates a low-cost method for estimating irradiance. The approach uses maximum power point tracking (MPPT) to easily estimate irradiance in a Photovoltaic (PV) system. Two main explicit mathematical models "IV-G" and "I-G" are examined for effective irradiance estimation. Given the requirement for MPPT, the examined PV system is powered by a hybrid-incremental conductance integral backstepping controller (H-INC-IBS), which enables proper maximum power point functioning. These models are evaluated using statistical indices such as the root mean square error (RMSE), mean absolute percentage error (MAPE), symmetrical mean absolute percentage error (SMAPE), and coefficient of correlation (R). The research tests these models using 37 climate patterns, demonstrating the influence of MPPT on model performance. In addition, the models are closely monitored in an experimental setup that includes two consecutive days of real-time climatic exposure. The experimental results show that the I-G model has the best accuracy measures, with worst MAE, MAPE, and SMAPE values of 18.81 W, 8.9039 %, and 4.7242 %, respectively. Thus, the article concludes that the I-G model is better suited for irradiance estimate in the context of MPPT. Furthermore, using evidence-based study outcomes, the paper proves that MPPT accuracy is proportional to estimating model accuracy. Given the little attention paid to this area of irradiance estimation, this work is intended to serve as a reference in the field.

An energy-efficient CMOS interface circuit with maximum power point tracking and power management capabilities for self-powered sensor node applications using 50/60 Hz transmission line magnetic field harvesters

An energy-efficient CMOS interface circuit with maximum power point tracking and power management capabilities for self-powered sensor node applications using 50/60 Hz transmission line magnetic field harvesters

Solar-Battery-Integrated Hybrid AC/DC Off-Grid System for Rural Households Based on a Novel Multioutput Converter

Solar fed off-grid system capable of catering dc and ac loads simultaneously with battery backup seems to be a propitious solution for rural electrification. However, such hybrid ac/dc off-grid systems reported in the literature have one or more of the following limitations: 1) higher number of converter stages and switch counts; 2) inadequate voltage gain; 3) use of bulky and costly low-frequency transformer; 4) lack of maximum power point tracking (MPPT) capability; 5) lack of battery charge control and/or over-charge/deep discharge protection; 6) series connection of several photo-voltaic (PV)/battery units; 7) lack of ac and/or dc load voltage regulation; and 8) use of a dedicated converter for MPPT control. A two-stage hybrid ac/dc off-grid system can be formed by integrating some of the high-frequency transformer-based four-port dc–dc converters reported in the literature. However, such dc–dc converters have higher number of control variables than required for this application thus leading to higher switch count. To overcome all these limitations of existing schemes, this article proposes a two-stage hybrid ac/dc off-grid system capable of catering ac and dc household loads simultaneously. All of the claims of this scheme are substantiated through exhaustive experimental validation carried out on a 400-W laboratory prototype.

Design and analysis of a novel adaptive learning control scheme for performance promotion of grid-connected PV systems

This paper addresses a hybrid adaptive iterative learning control strategy for controlling power converters that are used in photovoltaic systems to enhance maximum power point tracking capability in the presence of variable atmospheric conditions. The adaptation of the controller to the fast-changing environmental conditions is provided by a fractional-order proportional-integral type learning control mechanism. The developed control scheme is integrated into a grid-connected current-source flyback inverter to highlight the improvements in performance criteria such as convergence speed during transients, tracking accuracy, steady-state oscillations, and robustness. The performance analyses are carried out under various scenarios. The obtained results reveal that the dynamic response of the system is considerably increased under erratic atmospheric conditions while steady-state oscillations are decreased for stable operation conditions. The maximum absolute error that indicates the robustness of the proposed controller is decreased from 2.3704 to 2.1920. In addition, the error deviations of the proposed control algorithm are below 10%. The variance of the error, which shows steady-state stability, is reduced from 2.5123 to 1.6152. Also, the proposed controller reduces the amount of control energy by 20% when compared to the PI controller. Furthermore, the values of IAE and ISE are reported 10% lower in the proposed controller.

Enhanced model based algorithm to reinforce PV system with dynamic MPPT capability

<p>Photovoltaic (PV) power has emerged as the most attractive resource in form of a clean and green energy. However, one major challenge associated with PV interfacing is its intermittent output characteristic which varies dramatically with the operating conditions. Thus designing an effective maximum power point tracking (MPPT) algorithm is a key aspect for optimizing PV system performance. Numerous MPPT algorithms have been proposed earlier having their own specific advantages. However, these are found to have two major limitations which have to be essentially addressed. Firstly, they become ineffective in the dynamic conditions where there is rapid change in environmental parameters like insolation and temperature. Secondly, they fail to discriminate between global and local peaks under partial shading conditions. Therefore, to achieve a reliable and efficient system operation, this paper presents an enhanced model-based (MB) algorithm that overcomes both these deficiencies. Based on new governing equations and precised estimation technique, it predetermines the MPP analytically. First simulated results are obtained where it is tested for dynamic variations of all the three parameters. Then the experimental validation is carried out on a 2 KW installed panel where real time data is recorded through CR1000 data logger and environmental parameters are sensed with elements like pyranometer and humidity sensor. A large number of experimental results are obtained for tracked MPP in the dynamic conditions, which are then summarized in tabular forms. These are finally plotted and compared with simulated results to illustrate the effectiveness of proposed MB algorithm.</p>

Backpack Energy Harvesting System With Maximum Power Point Tracking Capability

A backpack energy harvester converts mechanical energy associated with the oscillation of the backpack during human walking, into electric energy. It can be a very promising solution for supplying portable devices, especially in outdoor activities, disaster relief, and military applications. In this article, a backpack energy harvesting system that is able to self-adapt its operating condition to maximize the extracted power while supplying a dc load is presented and studied, analytically and experimentally. It is based on a mechanical motion rectifier that converts the up-and-down oscillation of the backpack into a unidirectional rotation of a dc generator. The generator output voltage is regulated by a power electronic interface implementing a maximum power point tracking technique to maximize the extracted power. Experimental results confirm the tracking ability of the proposed system and show the advantages with respect to other wearable energy harvesting systems published in the literature.

Development and performance analysis of intelligent fault ride through control scheme in the dynamic behaviour of grid connected DFIG based wind systems

As the penetration of wind power increases, the fault ride through requirements imposed by grid code is important in grid connected wind systems. The wind systems should remain connected to the grid during grid faults satisfying the grid code which ensures grid stability during fault and post fault conditions. This paper proposes an intelligent fault ride through strategy for Doubly Fed Induction Generators (DFIG) based Wind Energy Conversion Systems (WECS) to achieve real and reactive power control during grid faults. The transient behaviour of the system is investigated under normal conditions and during grid faults. A fuzzy based wind speed estimation method in Maximum Power Point Tracking (MPPT) mode under normal conditions and coordinated Genetic Algorithm based Real-Reactive (GA-PQ) controller with DC chopper in Fault Ride Through (FRT) mode during grid faults is developed in this work. The proposed control scheme provides smooth operation of DFIG during grid faults by controlling the rotor and grid side converters, providing reactive power support to the grid and relieving stress on power converters thereby achieving system stability. The proposed strategy maintains the system parameters during the grid faults by suppressing the rotor and stator over current, dc link voltage overshoot, power oscillations and support the grid voltage under both balanced and unbalanced grid fault conditions with different voltage dips at PCC. Computer simulations in time-domain are performed by verifying the MPPT and FRT capability of the proposed strategy for 6.5MW grid connected DFIG based WECS in MATLAB/SIMULINK 2018b. The proposed coordinated intelligent PQ and DC chopper FRT strategy is compared against existing FRT schemes like crowbar, SDBR, DC Chopper, PQ controller and its hybrid combinations which yields satisfactory results. The proposed scheme is also validated in Opal-RT hardware for LLG fault at 75% dip in voltage. The simulation and real time results observed in the work station demonstrates the effectiveness of the proposed strategy in enhancing the FRT capability of the system.

Design, analysis and experimental verification of a high voltage gain and high‐efficiency DC–DC converter for photovoltaic applications

With the rapid development of photovoltaic systems, high step-up dc–dc converters draw significant attention, which shows the design challenges for simple topology, high efficiency, reduce voltage stress, and long lifespan. This study proposes a new high voltage gain converter that utilises the primary boost conversion cell and integrates with both switched-capacitor and coupled-inductor techniques. The proposed topology is modular and extendable for ultra-high step-up voltage gain. The leakage energy is recycled by a clamp circuit to minimise the switch voltage stress and power loss. One distinctive feature is that the voltage stress on the diodes and switch becomes low as well as constant against the variation of the duty cycle. Furthermore, the coupled inductor alleviates the diodes reverse recovery losses. The steady-state analyses, operation principles, and design guidelines are presented comprehensively. A prototype circuit is constructed to test the maximum power point tracking operation with voltage conversion from 30 to 380 V at 300 W. Experimental results substantiate the theoretical analysis and claimed advantages. The proposed converter demonstrates maximum power point tracking capability and high conversion efficiency over a wide range of power. The prototype shows the weighted efficiency of 96.3% according to the EU standard.

Maximum Power Point Tracking for Wind Turbine Using Integrated Generator–Rectifier Systems

Offshore wind is a rapidly growing renewable energy resource. Harvesting offshore energy requires multimegawatt wind turbines and high efficiency, high power density, and reliable power conversion systems to achieve a competitive levelized cost of electricity. An integrated system utilizing one active and multiple passive rectifiers with a multiport permanent magnet synchronous generator is a promising alternative for an electromechanical power conversion system. Deployment of the integrated systems in offshore wind energy requires maximum power point tracking (MPPT) capability, which is challenging due to the presence of numerous uncontrolled passive rectifiers. This article shows feasibility of MPPT based on a finding that the active-rectifier d-axis current can control the total system output power. The MPPT capability opens up opportunities for the integrated systems in offshore wind applications.

Novel high step‐up DC–DC converter with increased voltage gain per devices and continuous input current suitable for DC microgrid applications

SummaryThis paper suggests a nonisolated noncoupled inductor‐based topology for direct current (DC)–DC converters for DC microgrids. The proposed configuration profits from advantages like high step‐up capability, continuous input current, simple structure, reduced normalized standing voltage (NSV) on switches/diodes, large gain per devices, common ground point between source‐load, and maximum power point tracking (MPPT) capability. Both the switches (T1, T2) are turned on/off simultaneously, which minimizes the number of operational modes and simplifies the control strategy. These properties lead to a more compact, less expensive, and lighter topology. The operational modes and steady‐state analysis as well as design considerations have been presented in detail. According to comparative analysis, the voltage conversion ratio per number of devices in suggested topology is higher than that of other similar topologies addressed in literature. The simulation results extracted from PSCAD/EMTDC software and the experimental outcomes obtained from laboratory‐scale prototype confirm the effectiveness and correct performance of proposed topology.

New control paradigm for both islanded and grid‐connected operation of PMSG‐based wind turbine

This article proposes a new control paradigm for the seamless operation of a permanent magnet synchronous generator (PMSG) based wind energy conversion system (WECS) in both islanded and grid-connected modes. Conventionally, grid-connected WECS are controlled to extract the maximum power from the wind, known as maximum power point tracking (MPPT). However, in islanded operation, the objective is to control the power generated from the WECS to match the load demand, which here is called load following power generation (LFPG). This article proposes a power management system (PMS) which integrates the MPPT and LFPG capabilities of the WECS into a single-control paradigm. This enables the WECS to seamlessly achieve MPPT in grid operation, LFPG in islanded mode and low-voltage ride-through (LVRT) during fault. The proposed scheme is validated using MATLAB/SIMULINK simulations.

Comparative evaluation of multilevel DC link inverter using symmetrical and asymmetrical DC sources

Abstract This paper presents a comparative evaluation of multilevel DC link inverter of photovoltaic (PV) renewable energy system using either symmetrical or asymmetrical dc sources. The four units of dc source can have the same dc voltage level, ie 81.32 V, resulting in symmetrical dc sources. The asymmetrical dc sources consist of input dc voltages in binary sequence, 21.68 V, 43.37 V, 86.74 V and 173.48 V. The boost converters with maximum power point tracking (MPPT) capability which is regulated by perturb and observe (P&O) based control are connected between the PV panels and the four dc sources. The varying dc voltages from the PV panels are regulated to track the maximum power available regardless of the irradiance and temperature conditions. The symmetrical dc sources will facilitate the generation of 9 levels of staircase ac waveform rms of 230 V after the H-bridge inverter. Whereas, the asymmetrical dc sources are able to produce 31 levels of staircase ac waveform also with rated rms 230 V. Detailed analysis and comparison on the powers, ac output voltage, output current, total harmonic distortions, and MPPT achievement are described.

High Step-Up Quasi-Z Source DC–DC Converter

In this paper, a high step-up quasi- Z Source (QZS) dc–dc converter is proposed. This converter uses a hybrid switched-capacitors switched-inductor method in order to achieve high voltage gains. The proposed converter have resolved the voltage gain limitation of the basic QZS dc–dc converter while keeping its main advantages, such as continuous input current and low voltage stress on capacitors. Compared to the basic converter, the duty cycle is not limited, and the voltage stress on the diodes and switch is not increased. In addition to these features, the proposed converter has a flexible structure, and extra stages could be added to it in order to achieve even higher voltage gains without increasing the voltage stress on devices or limiting the duty cycle. The operation principle of the converter and related relationships and waveforms are presented in the paper. Also, a comprehensive comparison between the proposed and other QZS based dc–dc converters is provided which confirms the superiority of the proposed converter. Simulations are done in power systems computer aided design (PSCAD) in order to investigate the maximum power point tracking (MPPT) capability of the converter. In addition, the valid performance and practicality of the converter are studied through the results obtained from the laboratory built prototype.

A Time-Interleave-Based Power Management System with Maximum Power Extraction and Health Protection Algorithm for Multiple Microbial Fuel Cells for Internet of Things Smart Nodes

Microbial Fuel Cell (MFC) technology is a novel Energy Harvesting (EH) source that can transform organic substrates in wastewater into electricity through a bioelectrochemical process. However, its limited output power available per liter is in the range of a few milliwatts, which results very limited to be used by an Internet of Things (IoT) smart node that could require power in the order of hundreds of milliwatts when in full operation. One way to reach a usable power output is to connect several MFCs in series or parallel; nevertheless, the high output characteristic resistance of MFCs and differences in output voltage from multiple MFCs, dramatically worsens its power efficiency for both series and parallel arrangements. In this paper, a Power Management System (PMS) is proposed to allow maximum power harvesting from multiple MFCs while providing a regulated output voltage. To enable a more efficient and reliable power-harvesting process from multiple MFCs that considers the biochemical limitations of the bacteria to extend its lifetime, a power ranking and MFC health-protection algorithm using an interleaved EH operation was implemented in a PIC24F16KA102 microcontroller. A power extraction sub-block of the system includes an ultra-low-power BQ25505 step-up DC-DC converter, which integrates Maximum Power Point Tracking (MPPT) capabilities. The maximum efficiency measured of the PMS was ~50.7%. The energy harvesting technique presented in this work was tested to power an internet-enabled temperature-sensing smart node.

Dynamic Reconfiguration of Thermoelectric Generators for Vehicle Radiators Energy Harvesting Under Location-Dependent Temperature Variations

Conventional internal combustion engine vehicles generally have less than a 30% of fuel efficiency, and the most wasted energy is dissipated in the form of heat energy. The excessive heat dissipation is a primary reason of poor fuel efficiency, but reclamation of the heat energy has not been a main focus of vehicle design. Thanks to thermoelectric generators (TEGs), wasted heat energy can be directly converted to electric energy. All the heat exchangers, including vehicle radiators, gradually cool down the coolant or gas from the inlet to outlet. TEG modules are commonly mounted throughout the heat exchanger to fulfill the required power density and voltage. Each TEG module has a different hot-side temperature by the mounting location (distance from the inlet) and thus different maximum power point (MPP) voltage and current. Nevertheless, TEG modules are commonly connected in series and parallel, where both the ends are connected to a single power converter. As a result, the whole TEG module array exhibits a significant efficiency degradation even if the power converter has the MPP tracking capability. Although material and device researchers have been putting a lot of effort in enhancing TEG efficiency, such system-level issue has not been deeply investigated. This paper proposes a cross-layer, system-level solution to enhance TEG array efficiency introducing online reconfiguration of TEG modules. The proposed method is useful for any sort of TEG arrays to reclaim wasted heat energy, because heat exchangers generally have different inlet and outlet temperature values. This paper also introduces a complete design and implementation showcase of a reconfigurable TEG module building block. Experimental results show up to a 34% enhancement using the proposed method compared with a fixed array structure, which is a common practice.

Control of Wind Energy Conversion Systems Based on the Modular Multilevel Matrix Converter

The nominal power of single wind energy conversion systems (WECS) has been steadily increasing, now reaching power ratings close to 10 MW. In the power conversion stage, medium-voltage power converters are replacing the conventional low-voltage back-to-back topology. Modular multilevel converters have appeared as a promising solution for multi-MW WECSs, due to their modularity and the capability to reach high nominal voltages. This paper discusses the application of the modular multilevel matrix converter to drive multi-MW WECSs. The modeling and control systems required for this application are extensively analyzed and discussed in this paper. The proposed control strategies enable decoupled operation of the converter, provide maximum power point tracking capability at the generator side, grid code compliance at the grid side (including low-voltage ride-through control) and good steady state and dynamic performance for balancing the capacitor voltages in all the clusters. Finally, the effectiveness of the proposed control strategy is validated using simulation and through experimental results obtained with a 27-power-cell prototype.

Improving maximum power point tracking of partially shaded photovoltaic system by using IPSO-BELBIC

Solar photovoltaic (PV) arrays in remote applications are often related to the rapid changes in the partial shading pattern. Rapid changes of the partial shading pattern make the tracking of maximum power point (MPP) of the global peak through the local ones too difficult. An essential need to make a fast and efficient algorithm to detect the peaks values which always vary as the sun irradiance changes. This paper presents two algorithms based on the improved particle swarm optimization technique one of them with PID controller (IPSO-PID), and the other one with Brain Emotional Learning Based Intelligent Controller (IPSO-BELBIC). These techniques improve the maximum power point (MPP) tracking capabilities for photovoltaic (PV) system under partial shading circumstances. The main aim of these improved algorithms is to accelerate the velocity of IPSO to reach to (MPP) and increase its efficiency. These algorithms also improve the tracking time under complex irradiance conditions. Based on these conditions, the tracking time of these presented techniques improves to 2 msec, with an efficiency of 100%.

Distributed Maximum Power Point Tracking Using Model Predictive Control for Photovoltaic Energy Harvesting Architectures Based on Cascaded Power Optimizers

Mismatching and partial shading in photovoltaic (PV) energy harvesting systems are the main causes for performance degradation and efficiency drop. A power electronic energy harvesting topology based on cascaded power optimizers that use distributed maximum power point tracking (MPPT) is believed to be one of the promising solutions to address these issues. In this scheme, each PV module is interfaced to the energy system through a separate dc/dc converter with maximum power point tracking capability. This paper presents application of the model predictive control technique to a distributed maximum power point tracking algorithm for maximizing the energy harvest performance of a cascaded power optimizer based system under dynamic weather conditions. The developed technique employs two control loops: a submodule maximum power point tracking model predictive control loop for each converter and a supervisory maximum power point tracking loop for power optimization of all cascaded PV modules. The provided experimental results confirm high energy capture, fast dynamic response, and negligible oscillations around MPP using the proposed method.

A Comparison Study between Two MPPT Control Methods for a Large Variable-Speed Wind Turbine under Different Wind Speed Characteristics

Variable speed wind turbines (VSWTs) usually adopt a maximum power point tracking (MPPT) method to optimize energy capture performance. Nevertheless, obtained performance offered by different MPPT methods may be affected by the impact of wind turbine (WT)’s inertia and wind speed characteristics and it needs to be clarified. In this paper, the tip speed ratio (TSR) and optimal torque (OT) methods are investigated in terms of their performance under different wind speed characteristics on a 1.5 MW wind turbine model. To this end, the TSR control method based on an effective wind speed estimator and the OT control method are firstly presented. Then, their performance is investigated and compared through simulation test results under different wind speeds using Bladed software. Comparison results show that the TSR control method can capture slightly more wind energy at the cost of high component loads than the other one under all wind conditions. Furthermore, it is found that both control methods present similar trends of power reduction that is relevant to mean wind speed and turbulence intensity. From the obtained results, we demonstrate that, to further improve MPPT capability of large VSWTs, other advanced control methods using wind speed prediction information need to be addressed.