Direct Maximum Power Point Tracking Research Articles

A Direct Backstepping Super-Twisting Algorithm Controller MPPT for a Standalone Photovoltaic Storage System: Design and Real-Time Implementation

Abstract In this paper, we introduce a novel direct maximum power point tracking (MPPT) approach that combines the backstepping controller (BSC) and the super-twisting algorithm (STA). The direct backstepping super-twisting algorithm control (BSSTAC) MPPT was developed to extract the maximum power point (MPP) produced by a photovoltaic (PV) generator connected to the battery through a boost DC-DC converter. To reduce the number of sensors required for the BSSTAC implementation, a high gain observer (HGO) was proposed to estimate the value of the state of the PV storage system from measurements of the PV generator voltage and current. The suggested technique is based on the quadratic Lyapunov function and does not employ a standard MPPT algorithm. Results show that the suggested control scheme has good tracking performance with reduced overshoot, chattering, and settling time as compared to the prevalent MPPT tracking algorithms such as perturb and observe (P&O), conventional sliding mode control (CSMC), BSC, and integral backstepping controller (IBSC). Finally, real-time findings using the dSPACE DS 1104 software indicate that the generator PV can accurately forecast the MPP, as well as the efficacy of the suggested MPPT technique. The provided approach’s effectiveness has been validated by a comprehensive comparison with different methods, resulting in the greatest efficiency of 99.88% for BSSTAC.

Earthquake Algorithm-Based Voltage Referenced MPPT Implementation through a Standardized Validation Frame

This paper presents a new direct maximum power point tracking (MPPT) with a reference voltage (Vref) based on the metaheuristic earthquake algorithm (EA) where the optimization variable is the Vref for hard-switching converters. The efficiency and performance of EA-MPPT-Vref is compared with the perturb-and-observe (P&O) counterpart technique due to the fact that it is widely used for commercial products. Static and dynamic responses for both MPPT strategies are evaluated, which correspond to steady-state oscillations when they are near the maximum power point (MPP), and the tracking-speed, respectively. The efficiency was evaluated with the EN 50530 standard. The results show that the new MPPT proposed is a competitive method using the EA to obtain the optimal voltage reference. From static results, EA-MPPT VP presented a better efficiency of 5.13% and 3.23% for European and California energy commission (CEC) efficiency, respectively. Whereas, from dynamic results, MPPT-Vref techniques presented an efficiency from 95.13% to 99.91%, and 99.01% to 99.91% of the total power of the PV system for P&O and EA strategies, respectively.

Hardware-In-the-Loop Validation of Direct MPPT Based Cuckoo Search Optimization for Partially Shaded Photovoltaic System

During partial shading conditions (PSCs), the power-voltage curve becomes more complex, having one global maximum power (GMP) and many local peaks. Traditional maximum power point tracking (MPPT) algorithms are unable to track the GMP under PSCs. Therefore, several optimization tactics based on metaheuristics or artificial intelligence have been applied to deal with GMP tracking effectively. This paper details how a direct control cuckoo search optimizer (CSO) is used to track the GMP for a photovoltaic (PV) system. The proposed CSO addresses the limitations of traditional MPPT algorithms to deal with the PSCs and the shortcomings of the particle swarm optimization (PSO) algorithm, such as low tracking efficiency, steady-state fluctuations, and tracking time. The CSO was implemented using MATLAB/Simulink for a PV array operating under PSCs and its tracking performance was compared to that of the PSO-MPPT. Experimental validation of the CSO-MPPT was performed on a boost DC/DC converter using a real-time Hardware-In-the-Loop (HIL) simulator (OPAL-RT OP4510) and dSPACE 1104. The results show that CSO is capable of tracking GMP within 0.99–1.32 s under various shading patterns. Both the simulation and experimental findings revealed that the CSO outperformed the PSO in terms of steady-state fluctuations and tracking time.

PV Energy Harvesting Under Extremely Fast Changing Irradiance: State-Plane Direct MPPT

Photovoltaic cells require maximum power point tracking (MPPT) algorithms to ensure that the amount of power extracted is maximized. True seeking, direct duty cycle control MPPT algorithms are a simple and straightforward solution that can provide high tracking efficiency. In these algorithms the duty cycle is traditionally modified to reach a new steady state prior performing a new MPPT iteration. Therefore, the MPPT update period must be larger than the converter's settling time to reach a new steady state, which limits the dynamic tracking performance. This paper proposes a novel direct duty cycle control method that does not require the converter to achieve steady state in between MPPT updates. The proposed method benefits from the natural oscillations occurring in the converter to obtain extreme dynamic tracking improvements while maintaining simple implementation with no need of employing temperature or irradiance sensors. The scheme being introduced combines MPPT concepts with large-signal geometric control to achieve a reliable, high-performance solution very suitable for applications with rapidly changing irradiance, such as wearable technology and rooftop electric vehicle (EV). The theoretical analysis is supported by detailed mathematical procedures and validated by simulations and experimental results.

Direct Fixed-Step Maximum Power Point Tracking Algorithms with Adaptive Perturbation Frequency

Owing to the good trade-off between implementation and performance, fixed-step direct maximum power point tracking techniques (e.g., perturb and observe and incremental conductance algorithms) have gained popularity over the years. In order to optimize their performance, perturbation frequency and perturbation step size are usually determined a priori. While the first mentioned design parameter is typically dictated by the worst-case settling time of the combined energy conversion system, the latter must be high enough to both differentiate the system response from that caused by irradiation variation and match the finite resolution of the analog-to-digital converter in case of digital implementation. Well-established design guidelines, however, aim to optimize steady-state algorithm performance while leaving transients nearly untreated. To improve transient behavior while keeping the steady-state operation unaltered, variable step direct maximum power point tracking algorithms based on adaptive perturbation step size were proposed. This paper proposes a concept of utilizing adaptive perturbation frequency rather than variable step size, based on recently revised guidelines for designing fixed-step direct maximum power point tracking techniques. Preliminary results demonstrate the superiority of the proposed method over adaptive perturbation step size operation during transients, without compromising the steady state performance.

A Direct Maximum Power Point Tracking Method for Single-Phase Grid-Connected PV Inverters

A direct maximum power point tracking (MPPT) method for PV systems has been proposed in this work. This method solves two of the main drawbacks of the perturb and observe MPPT, namely: 1) the tradeoff between the speed and the oscillations in steady-state and 2) the poor effectiveness in dynamic conditions, especially in low irradiance when the measurement of signals becomes more sensitive to noise. The proposed MPPT is designed for single-phase single-stage grid-connected PV inverters and is based on estimating the ripple of the instantaneous PV power and voltage, using a second-order generalized integrator-based quadrature signal generator. We analyzed the global stability of the closed-loop control system and validated the proposed algorithm through simulation and experiments on an inverter test platform according to the EN 50530 standard. The experimental results confirm the performance of the proposed method in terms of both speed and tracking efficiency.

Design Guidelines for Multiloop Perturbative Maximum Power Point Tracking Algorithms

Due to relatively good performance and simple implementation, fixed-step direct maximum power point tracking (MPPT) techniques such as perturb and observe and incremental conductance are the most popular algorithms aimed to maximize the energy yield of photovoltaic energy conversion systems. In order to optimize the MPPT process performance, two design parameters—perturbation frequency and perturbation step size—need to be set a priori , taking into account the properties of both interfacing power converter and photovoltaic generator. While perturbation frequency is limited by the combined energy conversion system settling time, perturbation step size must be high enough to differentiate system response from that caused by irradiation variation. Recent studies have provided explicit design guidelines for single-loop MPPT structures only, where the algorithm directly sets the interfacing converter duty cycle. It was shown that dynamic resistance of the photovoltaic generator, which is both operation point and environmental conditions dependent, significantly affects the combined energy conversion system settling time. On the other hand, no design guidelines were explicitly given for multiloop MPPT structures, where the algorithm sets the reference signal for photovoltaic generator (PVG) voltage and inner-voltage controller performs the regulation task. This paper introduces perturbation frequency and perturbation step size design guidelines for such systems. It is shown that while perturbation step size design is similar to that of single-loop structures, perturbation frequency design is quite different. It is revealed that once the inner-voltage loop is properly closed, the influence of PVG dynamic resistance on settling time (and thus on perturbation frequency design) is negligible. Experimental results are provided to verify the proposed guidelines validity.

Distributed Fast Maximum Power Point Tracking Technique for Mismatched Module Application

<p>This paper propose distributed fast maximum power point tracking (DFMPPT) technique to achieve maximum power point tracking (MPPT). This paper implements the algorithm in distributed MPPT (DMPPT) architecture for mismatched condition with single module, and string connection. The MPPT method uses indirect and direct MPPT method by fractional open-circuit voltage (FOCV) with incremental conductance (INC) for high-speed maximum energy harvesting. This method is proven to be fast for tracking maximum power point (MPP) which achieves the peak power less in 1.7ms via for a single module with efficiency of 99.7% compared to the recent MPPT technique to reach MPP in 1.75ms with 95.8% efficiency. While for string configuration, the efficiency of the whole system is rated by 85.583% by taking 8.675ms to reach global MPP.</p>

A maximum power point tracking method with variable weather parameters based on input resistance for photovoltaic system

In order to greatly improve the maximum power point tracking (MPPT) speed and adaptability to the varying weather conditions for photovoltaic (PV) system, in this paper, a MPPT method with variable weather parameters (VWP) considered specially from input resistance standpoint is proposed. As well as other VWP methods, it can also track the maximum power point (MPP) as quickly as possible. In this method, the approximate relationship between control signal and PV cell parameters (Vm and Im) is firstly built by studying the input resistance of PV system deeply, then the relationship between VWP and Vm,Im is found by the curve fitting technique. Through these relationships, the bridge between control signal and VWP is built successfully, which is the key work to implement the direct MPPT control. Finally, some simulation experiments show that the proposed method is feasible and available to track the MPP successfully and has better MPPT rapidity, accuracy, stability and adaptability than conventional perturbation and observation (P&O) method and fuzzy control method.

A Variable Step Size Incremental Conductance Direct MPPT Method for Stand-Alone PV Systems

This paper presents a variable step size incrementalconductance direct Maximum Power Point Tracking (MPPT) method using fuzzy membership for a standalone photovoltaic (PV) system under rapidly changing irradiation. MPPT techniques have been widely applied in PV systems to make a PV array generate maximum power, which depends on solar irradiation. In most applications of MPPT technologies, MPPT algorithm design methods are performed and tested under slowly changing atmospheric conditions such as irradiation and temperature. The short-term effect under rapidly changing irradiation should be considered, however, to improve the dynamic performance of PV system. Our proposed MPPT method is based on an incremental conductance algorithm with a direct control scheme that can directly adjust the duty cycle for the PI controller. A fuzzy membership function is adopted to determine the variable step size according to rapidly changing irradiation. The proposed methods thus has not only faster dynamic performance but also high tracking accuracy. In order to show the effect of the proposed method, the simulation model and proposed MPPT is designed with MATLAB/Simpower and simulated with MATLAB/Stateflow.

Special Issue on Advanced Intelligent Systems

The 12th International Symposium on Advanced Intelligent Systems (ISIS 2011) held at La Vie DfOr Resort, Suwon, Korea, on September 28 to October 1, 2011, featured presentations by researchers, engineers and practitioners on the latest accomplishments, innovations and applications in artificial intelligence, intelligent systems, and information technology. The 152 papers consisted of 110 regular papers, 39 organized session papers and 3 invited papers were contributed to the conference. The Program Committee requested ISIS 2011 reviewers to select papers for a special issue of the Journal of Advanced Computational Intelligence & Intelligent Informatics (JACIII), of which about 10 were accepted for publication in a twopart ISIS 2011 special issue, Vol.16, No.7, containing 5 papers. Part II will feature about 5 papers. A brief review of Part I covers 5 papers: First paper proposes a quantitative model for assessing the collision risk in maritime waterway traffic. The method proposes recent maritime traffic characteristics in time-variant CPA waterway environments and models a dynamic causation factor as a risk indicator. Second paper proposes multiagent query refinement realizing personalized query refinement by three strategies ? knowledge-based query expansion, user-device-based query and weighted query expansion strategy. These approaches determine the domain that the initial query belongs to and expand the query by comprehensively considering user interests. Third paper presents variable-step-size incremental conductance direct maximum power point tracking using fuzzy membership for a standalone photovoltaic system under rapidly changing irradiation. Fourth paper applies a natural actor-critic (NAC) and natural evolution strategies (NES) from natural-gradient-based machine learning to path-tracking control problems for autonomous vehicles. Fifth paper presents features for authenticating painting style, specifically that of Piet Mondrain. It demonstrates meaningful features using two supervised learning algorithms ? decision tree induction algorithm C4.5 and the feature generating machine (FGM) ? selecting important features in the course of learning. We thank the reviewers for their time and effort in making this special issue available so quickly. We are also grateful to the JACIII editorial office for invaluable assistance and advice in putting the issue together.

Comparison of direct maximum power point tracking algorithms using EN 50530 dynamic test procedure

Three direct maximum power point tracking (MPPT) algorithms with non-adaptive voltage step are evaluated in the light of their performance for photovoltaic systems under dynamic conditions for a resistive load. A microcontroller-based buck–boost DC–DC converter platform is used to implement and compare the algorithms. Dynamic test procedures from a new standard for inverter efficiency determination EN 50530 were implemented to evaluate dynamic MPPT algorithms’ efficiency and their dependence.Experimental results show that MPPT algorithms’ regulating frequency and regulating voltage step play a crucial role in the dynamic performance of direct algorithms. A range of regulating frequencies and voltage steps were examined. If proper parameter values are chosen, all algorithms perform well and close to each other. Detailed evaluation was performed with determining partial MPPT efficiency under different irradiance slopes. Results show that at least 10 Hz should be used to satisfy the 99% tracking efficiency over all slopes in the range from 0.5 to 100 W/m2/s as specified by EN 50530 standard. Further increase of regulating frequency would result in higher slope efficiency only at dynamic conditions.

T-S Fuzzy Maximum Power Point Tracking Control of Solar Power Generation Systems

This paper presents maximum power point tracking (MPPT) control for stand-alone solar power generation systems via the Takagi–Sugeno (T-S) fuzzy-model-based approach. In detail, we consider a dc/dc buck converter to regulate the output power of the photovoltaic panel array. First, the system is represented by the T-S fuzzy model. Next, in order to reduce the number of measured signals, a T-S fuzzy observer is developed for state feedback. Then, a fuzzy direct MPPT controller is proposed to achieve asymptotic MPPT control, in which the observer and controller gains are obtained by separately solving two sets of linear matrix inequalities. Different from the traditional MPPT approaches, the proposed T-S fuzzy controller directly drives the system to the maximum power point without searching the maximum power point and measuring insolation. Furthermore, when considering disturbance and uncertainty, robust MPPT is guaranteed by advanced gain design. Therefore, the proposed method provides an easier implementation form under strict stability analysis. Finally, the control performance is shown from the numerical simulation and experimental results.