Proposed Maximum Power Point Tracking Scheme Research Articles

A new real-time maximum power point tracking scheme for PV-BASED microgrid STABILITY using online DEEP ridge extreme learning machine algorithm

A new deep representation-based Maximum Power Point Tracking (MPPT) controller is proposed in this paper for accurate Control references calculation in Photovoltaic (PV) based Micro Grid (MG) operation. The deep representation is obtained by two-step estimation: Data dimension reduction and MPPT Tracker towards optimal computation. The considered deep learning architecture is targeted for N number (large scale) of PV-based DGs, connected locally in the distribution system (DC link extended to AC utility). The collected data of solar irradiation (in W/m2) and PV panel temperature (in oC) profiles of local DGs are subjected to data dimensions using Extreme Learning Machine (ELM) based on Moore-Penrose inverse technique. The compressed represented PV-DG data is further communicated to the Tertiary Control side MPPT Tracker, where Ridge Regression-based ELM is presented for estimating Maximum Power Point Power (PMPP) and Voltage (VMPP) values for kth instant. The initial randomness present in the proposed Deep Representation based Ridge Regression Extreme Learning Machine (DR-RRELM) is further minimized by adopting Huber's characteristic distribution-based likelihood estimator. The proposed MPPT scheme is effectively implemented for accurate control reference in DC-DC and DC-AC converters in the MG. The proposed controller is also suitable for stability improvement at point of common coupling (PCC). Three different case studies such as past data verification, stability analysis under various operating conditions, irradiant change and source power variation. The efficacy of the proposed deep representation-based MPPT scheme is evidenced in MATLAB-based simulation. The proposed technique provides better tracking ability, faster learning and effective reference generation. The case study with irradiation change is validated in TMS320C6713 (32-bit) based Hardware-in-Loop (HIL) validation.

Design of smart battery charging circuit via photovoltaic for hybrid electric vehicle

AbstractThis paper proposes an intelligent battery charging scheme for hybrid electric vehicles (HEVs) with a fuel cell as the primary energy source and solar photovoltaic (PV) and battery as the auxiliary energy sources. While dealing with the PV, a minimized oscillation‐based improved perturb and observe (I‐P&O) maximum power point (MPP) tracking (MPPT) scheme is designed to mitigate the impact of oscillations around MPP and loss of tracking direction. The DC–DC boost and DC–DC buck power converters are connected in a cascade manner to harvest optimal power from PV and as a charging circuit for HEV, respectively. An intelligent fuzzy logic‐based proportional integral derivative (PID) (F‐PID) controller is employed for the buck converter to get the constant voltage and constant current for the effective charging of the battery. The two primary objectives of this work are (1) maximum utilization of the designed PV array via the I‐P&O MPPT scheme to enhance the system efficacy, reduce system cost, and reduce complexity. (2) To obtain minimum battery losses and an enhanced life cycle of HEV. The proposed MPPT scheme provides a maximum 99.80% tracking efficiency of the considered PV array at an insolation level of 1000 W/m2. Moreover, almost nominal voltage and current ripples have appeared in HEV's proposed intelligent battery charging circuit.

Backstepping based real twisting sliding mode control for photovoltaic system

Renewable energy sources tied to a utility grid require non-linear control algorithms to provide an efficient and stable output under different operating conditions. The maximum power point tracking (MPPT) approach is necessary for power generation due to non-linear behavior of photovoltaic (PV) power plants. In changing environmental and partial shading conditions, the standard MPPT methods may lead to abnormal results. In this paper, a backstepping based real twisting sliding mode MPPT control is proposed for the PV-battery system where maximum available power is extracted by tracking PV voltage. Moreover, a direct sliding mode control is proposed for battery-integrated buck boost converter for voltage regulation. Reference sliding surface is generated through linear interpolation based on the predicted maximum power point PV voltage. The proposed MPPT strategy is tested against variations of irradiance, temperature, and load. Simulation results highlight superior tracking performance, reduced chattering, and oscillations of this technique over existing models.

An Advanced MPPT Scheme for PV Systems Application with Less Output Ripple Magnitude of the Boost Converter

The purpose of this paper is to enhance the performance and tracking efficiency of solar photovoltaic systems. This aim can be achieved by operating the photovoltaic array at its optimum power and reducing the output ripple problem of DC-DC converters that affect and stress sensible electronic loads. In view of that, an advanced maximum power point (MPP) tracking (MPPT) scheme, which can guarantee zero oscillation tracking of the accessible MPP and less ripple magnitude on the output side of the DC-DC boost converter, is used. Various simulations are carried out under three conditions of solar irradiance variation, namely, standard test conditions (STC), rapid, and Sin scenarios, using the MATLAB/Simulink® environment, to assess and benchmark the robustness of the tracking of the new MPPT scheme over the celebrated Increment of Conductance (INC) MPPT scheme. Based on the simulation results, the proposed scheme can significantly improve tracking accuracy and reduce the magnitude of ripples on both sides of the boost converter compared to the INC scheme. Certainly, the proposed scheme can provide a shorter time response (0.011 seconds) to locate and track the expected MPP, which is 2.55 times less than that of the INC scheme; a zero power magnitude oscillation instead of 15.9 watts of the INC scheme; and six-time minimization of the magnitude of output voltage ripples compared to the INC scheme. Furthermore, the suggested MPPT scheme has the better tracking efficiency in all scenarios; 99.86%, 99.60%, and 99.62% in the STC, rapid, and Sin scenarios, respectively, with an average value of 99.69% compared to the INC MPPT scheme, which has 94.23%, 95.28%, and 97.87% in the STC, rapid, and Sin scenarios, respectively, with a moderate average tracking efficiency of 95.79%. Finally, the accuracy and tracking performance of the proposed MPPT scheme are verified by real-time examination using the RT-LAB simulator. According to the results obtained, the proposed scheme provides the highest tracking efficiency of 99.80% and 97.77% under the STC and sudden insolation change scenarios, respectively, compared to the INC scheme, which shows, respectively, 97.8% and 96.5% under both scenarios.

Performance evaluation of improved ANOVA-tuned MPPT controlled DC–DC boost converter for SPV system

ABSTRACT This article visualises the growth of harvesting solar energy by a solar photovoltaic (SPV) system and techniques for tracking the maximal power point. An active maximal power point tracking controller is put forward to harvest the solar power named an improved analysis of variance (ANOVA)-tuned algorithm. In this configuration of the SPV system, maximal power yield is obtained from the multi photovoltaic (PV) string through the DC–DC boost converter. To obtain the maximal power from the PV string, the optimal duty cycle has to be maintained in a DC–DC boost converter. To achieve a sustained duty cycle, an improved ANOVA-tuned maximum power point tracking (MPPT) controller is proposed as an optimal controller. The performance of the proposed controller was compared with that of a conventional perturb and observe controller for steady-state and dynamic conditions. The result of the proposed MPPT scheme has maximal power and obviously a better tracking path. The simulation is carried out in the MATLAB/Simulink environment, and the experimental result shows the benefits of the proposed MPPT techniques. The supremacies of the proposed controller are a preferable tracking response, less training data time, effective steady state and dynamic performances.

Fuzzy based incremental conductance algorithm stabilized by an optimal integrator for a photovoltaic system under varying operating conditions

ABSTRACT In renewable system control engineering, Maximum Power Point Tracking (MPPT) techniques are considered as one of the key steps in photovoltaic (PV) system development. Indeed, some MPPT techniques provide high performance under uniform irradiation and temperature conditions. However, their performance significantly degrades when the two preceding climatic conditions suddenly change. Therefore, this paper proposes a new voltage regulation based on Fuzzy Logic Control (FLC) strategy and small-signal model of DC–DC booster converter. The proposed control scheme is mainly based on the indirect incremental conductance (Inc) technique, equipped with an optimal integrator controller (OIC). It is implemented in a PV system, consisting of a DC–DC boost converter connected to a resistive load, with the main objective of ensuring a good MPP tracking behavior for variable operating conditions. To achieve this objective, the proposed MPPT strategy is designed around two stages. First, the smooth reference voltage is ensured by a Single-Input Single-Output (SISO) fuzzy logic controller using the Inc technique based on the MPPT approach. Then, the optimal integrator controller stabilizing the closed-loop system is integrated with optimization of its parameter according to Routh’s criterion for resistive load variations. Simulation results confirm the effectiveness of the proposed MPPT technique compared to some commonly used MPPT approaches. The superiority of the proposal is proven by using efficiency ratio, which rises more than 98% in all case studies. These objectives are ensured for both uniform and critical sudden change in weather conditions, regardless of resistive load variations.

MPPT Algorithm Based on Artificial Bee Colony for PV System

Energy structures from non-conventional energy source has become highly demanded nowadays. In this way, the maximum power extraction from photovoltaic (PV) systems has attracted the attention, therefore an optimization technique is necessary to improve the performance of solar systems. This article proposes the use of ABC (artificial bee colony) algorithm for the maximum power point tracking (MPPT) of a PV system using a DC-DC converter. The procedure of the ABC MPPT algorithm is using data values from PV module, the P-V characteristic is identified and the optimal voltage is selected. Then, the MPPT strategy is applied to obtain the voltage reference for the outer PI control loop, which in turn provides the current reference to the predictive digital current programmed control. A real-time and high-speed simulator (PLECS RT Box 1) and a digital signal controller (DSC) are used to implement the hardware-in-the-loop system to obtain the results. The general system does not have a high computational cost and can be implemented in a commercial low-cost DSC (TI 28069M). The proposed MPPT strategy is compared to the conventional perturb and observe method, results show the proposed method archives a much superior performance.

MPPT integrated DC–DC boost converter for RF energy harvester

This study proposes a design of a maximum power point tracking (MPPT)-based DC–DC boost converter for an radio frequency (RF) energy harvester. The MPPT technique has been implemented in the converter using an adaptable load tracking mechanism with variable input RF power to meet the supply voltage tolerance limits. The proposed MPPT scheme is implemented using a sample-and-hold circuit in the tracking loop of the DC–DC boost converter. The complete energy harvester system prototype has been realised in a 130 nm standard complementary metal-oxide-semiconductor (CMOS) process. The footprint of the proposed converter circuit is much smaller compared to similar designs reported in the literature making it applicable for wearable and implantable biomedical applications.

Backstepping Based Super-Twisting Sliding Mode MPPT Control with Differential Flatness Oriented Observer Design for Photovoltaic System

The formulation of a maximum power point tracking (MPPT) control strategy plays a vital role in enhancing the inherent low conversion efficiency of a photovoltaic (PV) module. Keeping in view the nonlinear electrical characteristics of the PV module as well as the power electronic interface, in this paper, a hybrid nonlinear sensorless observer based robust backstepping super-twisting sliding mode control (BSTSMC) MPPT strategy is formulated to optimize the electric power extraction from a standalone PV array, connected to a resistive load through a non-inverting DC–DC buck-boost power converter. The reference peak power voltage is generated via the Gaussian process regression (GPR) based probabilistic machine learning approach that is adequately tracked by the proposed MPPT scheme. A generalized super-twisting algorithm (GSTA) based differential flatness approach (DFA) is used to retrieve all the missing system states. The Lyapunov stability theory is used for guaranteeing the stability of the proposed closed-loop MPPT technique. The Matlab/Simulink platform is used for simulation, testing and performance validation of the proposed MPPT strategy under different weather conditions. Its MPPT performance is further compared with the recently proposed benchmark backstepping based MPPT control strategy and the conventional MPPT strategies, namely, sliding mode control (SMC), proportional integral derivative (PID) control and the perturb-and-observe (P&O) algorithm. The proposed technique is found to have a superior tracking performance in terms of offering a fast dynamic response, finite-time convergence, minute chattering, higher tracking accuracy and having more robustness against plant parametric uncertainties, load disturbances and certain time-varying sinusoidal faults occurring in the system.

Finite-Time Fast Dynamic Terminal Sliding Mode Maximum Power Point Tracking Control Paradigm for Permanent Magnet Synchronous Generator-Based Wind Energy Conversion System

Due to the intermittent nature of wind, there exists a major disparity between the power generation from the wind and the demand of electricity. Hence, a sophisticated maximum power point tracking (MPPT) control paradigm must be formulated for maximizing the power extraction from the wind. This research article focuses on the formulation of a nonlinear fast dynamic terminal sliding mode control (FDTSMC)-based MPPT strategy for optimizing the power extraction from a 3kW, variable speed, fixed-pitch wind energy conversion system equipped with a permanent magnet synchronous generator. The proposed MPPT strategy is compared with the benchmark fast terminal sliding mode control, conventional sliding mode control, feedback linearization control and proportional integral derivative control-based MPPT strategies under a stochastic wind speed profile. The proposed paradigm has been found superior in its tracking performance by converging the output tracking error to zero in a finite time, realizing a high precision performance, offering fast dynamic response, reducing the chattering to a minute level and guaranteeing global robustness. The superior performance and effectiveness of the proposed FDTSMC-based MPPT control paradigm is tested and validated through extensive MATLAB/Simulink simulations.

Nonlinear robust integral backstepping based MPPT control for stand-alone photovoltaic system.

PV (Photovoltaic) cells have nonlinear current-voltage (I − V) and power-voltage (P − V) characteristics with a distinct maximum power point (MPP) that entirely depends on the ambient meteorological conditions (i.e. solar irradiance and temperature). Hence, to continuously extract and deliver the maximum possible power from the PV system, under given meteorological conditions, the maximum power point tracking (MPPT) control strategy needs to be formulated that continuously operates the PV system at its MPP. To achieve this goal, a hybrid nonlinear, very fast and efficient MPPT control strategy, based on the robust integral backstepping (RIB) control, is formulated in this research article. The simulation testbed comprises a standalone PV array, a non-inverting buck-boost (NIBB) DC-DC power converter, a purely resistive and a dynamic load (sound system). The proposed MPPT control scheme consists of two loops, where the first loop generates the real-time offline reference peak power voltage through an adaptive neuro-fuzzy inference system (ANFIS) network, which is then utilized in the second loop as a set-point value for generating a control signal and then forcing the PV system to be operated at this set-point by continuously adjusting the duty ratio of the power converter. This control strategy exhibits no overshoot, fast convergence, good transient response, fast rising and settling times and minimum output tracking error. The MATLAB/Simulink platform is used to test the performance of the proposed MPPT strategy against varying meteorological conditions, plant current and voltage faults and plant parametric uncertainties. To validate the superiority of the proposed control strategy, a comparative analysis of the proposed control strategy is presented with the nonlinear backstepping (B), integral backstepping controller (IB) and conventional PID and P&O based MPPT controllers.

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.

A Generic Power Management Circuit for Energy Harvesters With Shared Components Between the MPPT and Regulator

This paper presents a novel power management circuit (PMC) for harvesting the energy from the ambient. The proposed PMC comprises an energy harvester, a startup, a dc–dc boost converter, and a dc–dc buck converter. The PMC is capable of working with various low-power energy harvesters and can track the maximum power point after every 4.5 s. To achieve the maximum power point tracking (MPPT), an open-circuit-voltage-based method is used to transfer the maximum power from the energy harvester to the power optimized boost converter. The proposed MPPT scheme works for a wide range of equivalent source resistance of the energy harvester in the range of $20~\Omega $ –1 $\text{M}\Omega $ . An auxiliary energy harvester is used for the startup to avoid any external supply. Regulated voltage across a load is provided by the buck converter which features sharing the switches and inductor with the boost converter. The complete circuit is designed, optimized, and simulated in 180-nm mixed-mode CMOS technology using three different types of energy harvesters, which are precisely characterized and modeled. Post-layout simulated results are presented for the input power ranging from 150 nW to $500~\mu \text{W}$ for different values of source resistances ranging from $20~\Omega $ to 1 $\text{M}\Omega $ . For a source resistance of 100 $\text{k}\Omega $ , the efficiency of the boost converter is 39.91% and 89.91% at available power of 156 nW and 2.5 $\mu \text{W}$ , respectively. The buck converter is able to regulate the load voltage to 1 V across the load resistance ranging from $100~\Omega $ to 2 $\text{k}\Omega $ .

A Simple, Efficient, and Novel Standalone Photovoltaic Inverter Configuration With Reduced Harmonic Distortion

This paper is put forward a novel photovoltaic (PV) inverter topology for maximum solar power utilization, which incorporates a new maximum power point tracking (MPPT) scheme based on shading pattern identification using the artificial neural network, single-input and multi-output (SIMO) converter, and multilevel inverter (MLI). The performance of the proposed MPPT scheme is benchmarked under partially shaded conditions. In continuation, the PV voltage is fed to the SIMO converter, where the converter produces four independent (V1, V2, V3 and V4) voltages with different magnitudes. The MLI converts the dc output voltage of the SIMO converter into ac to feed the utility, with reduced harmonic distortion. This MLI consists of eight switching devices and produces thirty one level ac output voltage with very less harmonic distortion. The salient feature associated with the proposed topology is that the proposed MPPT scheme extracts utmost power in any weather conditions and MLI feeds the utility. An experimental prototype is designed and developed to verify the performance of the proposed PV inverter topology. FPGA Spartan trainer kit is used to program pulses required for the MLI and converter of the proposed topology.

Angular speed control of an induction motor via a solar powered boost converter-voltage source inverter combination

This paper proposes a maximum power point tracking (MPPT) algorithm for the development of a three-phase induction motor angular speed drive. A Dc-to-Dc boost power converter, powered by photovoltaic (PV) panels, feeds the three-phase power inverter. The MPPT algorithm is based on the Exact Static Error Dynamics Passive Output Feedback Controller (ESEDPOF) technique together with an Algebraic Estimator of the impedance. The estimated value is the equivalent impedance that exists between the boost converter and the three-phase inverter, and then this value is used in real-time to generate the desired reference variables of the MPPT algorithm. The angular speed-tracking controller for the induction motor is based on the well-known Field-Oriented Control (FOC) technique. An Experimental set-up was developed using an array of two PV panels. Then, a realistic scenario is carried out, and real-time results at low-speed, with and without load, are presented in order to show the effectiveness and robustness of the proposed MPPT scheme. Under this scenario, the boost converter achieves an electric power efficiency of 80%, when a nominal load torque is applied to the induction motor shaft.

Maximum Power Point Tracking for Cascaded PV-Converter Modules Using Two-Stage Particle Swarm Optimization

The paper presents a novel two-stage particle swarm optimization (PSO) for the maximum power point tracking (MPPT) control of a PV system consisting of cascaded PV-converter modules, under partial shading conditions (PSCs). In this scheme, the grouping method of the shuffled frog leaping algorithm (SFLA) is incorporated with the basic PSO algorithm, ensuring fast and accurate searching of the global extremum. An adaptive speed factor is also introduced to improve its convergence speed. A PWM algorithm enabling permuted switching of the PV sources is applied. The method enables this PV system to achieve the maximum power generation for any number of PV and converter modules. Simulation studies of the proposed MPPT scheme are performed on a system having two chained PV buck-converter modules and a dc-ac H-bridge connected at its terminals for supplying an AC load. The results show that this type of PV system allows each module to achieve the maximum power generation according its illumination level without affecting the others, and the proposed new control method gives significantly higher power output compared with the conventional P&O and PSO methods.

A High Efficiency Boost Converter with MPPT Scheme for Low Voltage Thermoelectric Energy Harvesting

Using thermoelectric elements to harvest energy from heat has been of great interest during the last decade. This paper presents a direct current–direct current (DC-DC) boost converter with a maximum power point tracking (MPPT) scheme for low input voltage thermoelectric energy harvesting applications. Zero current switch technique is applied in the proposed MPPT scheme. Theoretical analysis on the converter circuits is explored to derive the equations for parameters needed in the design of the boost converter. Simulations and experiments are carried out to verify the theoretical analysis and equations. A prototype of the designed converter is built using discrete components and a low-power microcontroller. The results show that the designed converter can achieve a high efficiency at low input voltage. The experimental efficiency of the designed converter is compared with a commercial converter solution. It is shown that the designed converter has a higher efficiency than the commercial solution in the considered voltage range.

Novel fast dynamic MPPT (maximum power point tracking) technique with the capability of very high accurate power tracking

In this paper, a novel maximum power point tracking (MPPT) technique is proposed to track the maximum power point (MPP) of photovoltaic (PV) systems. The proposed MPPT scheme concurrently uses PV voltage and current deviations to find the MPP of a PV module/array/panel under every condition. A PV system has been built to implement the proposed MPPT technique as a MPPT controller, and experimental results obtained under standard test condition (STC), uniform and non-uniform shading conditions, and partial shading conditions are presented that explicitly validate theoretical results. A comparative study together with real experimental results obtained under STC verify that the proposed MPPT technique has a dynamic response with the shortest convergence time of 12 ms and the highest MPPT efficiency more than 99.6% compared to other MPPT techniques. Static-dynamic response obtained experimentally under uniform and non-uniform shading conditions again verifies that the method has a very fast high accurate dynamic response with the MPPT efficiency more than 99.6%. It is also experimentally shown that the proposed technique high accurately tracks the global maximum power point (GMPP) under partial shading conditions, so that, the MPPT efficiency is again more than 99.6%, and the convergence time is less than 140 ms.

A MPPT control strategy with variable weather parameter and no DC/DC converter for photovoltaic systems

In this paper, a unified model of three basic DC/DC converters is firstly proposed under certain conditions. This model is named as inductance–capacitor–diode (LCD) circuit and consisted of an inductance, a capacitor and a diode. Based on LCD circuit, a maximum power point tracking (MPPT) control strategy with variable weather parameter is proposed for photovoltaic (PV) generation systems with DC bus. In this strategy, through using LCD circuit instead of DC/DC converter, the MPPT performance of PV system is not influenced by the choice of different DC/DC converter topologies and the configuration of PV system is simplified, which makes the overall cost lower and the system integration, modularization and miniaturization more convenient. Finally, the accuracy of LCD model, and the feasibility and availability of proposed MPPT control strategy are verified by some simulated experiments conducted under random weather conditions; the effect of non-uniform weather on proposed MPPT strategy is tested by some experiments under non-uniform weather conditions; the output transient-state performance of proposed MPPT strategy is analyzed by one experiment under a varying irradiance condition and the performance comparison with conventional P&O method is made by another experiment under a given weather condition.

An Adaptive Maximum Power Point Tracking Scheme Based on a Variable Scaling Factor for Photovoltaic Systems

An adaptive maximum power point tracking (MPPT) scheme employing a variable scaling factor is presented. An MPPT control loop was constructed analytically and the magnitude variation in the MPPT loop gain according to the operating point of the PV array was identified due to the nonlinear characteristics of the PV array output. To make the crossover frequency of the MPPT loop consistent, the variable scaling factor was determined using an approximate curve-fitted polynomial equation about linear expression of the error. Therefore, a desirable dynamic response and the stability of the MPPT scheme were maintained across the entire MPPT voltage range. The simulation and experimental results obtained from a 3-kW rated prototype demonstrated the effectiveness of the proposed MPPT scheme.