Incremental Conductance Maximum Power Point Tracking Method Research Articles

A Hybrid Solar Photovoltaic and Wind Turbine Power Generation for Stand-Alone System with IoT-Based Monitoring and MPPT Control

The goal of this effort is to monitor and manage a hybrid stand-alone photovoltaic (PV) and wind energy system (WES) using the Internet of Things (IoT). The suggested hybrid system uses Incremental Conductance (INC) Maximum Power Point Tracking (MPPT) and Perturb and Observe (P&O)-based Sliding Mode Control (SMC) approaches. The cost-effective Arduino Uno board in Matlab is used to analyze the P&O and INC MPPT methods. Energy from renewable sources is stored in a battery, and the output voltage of each source is monitored using the blynk app and GSM 800c module. Simulation results validate the controller’s operation, and the performance of both MPPT algorithms is compared. Experimental outcomes demonstrate the effectiveness of the IoT-based controller and its characteristic functionalities. Overall, this proposed hybrid PV and WES configuration offers advantages such as reduced human resources, cost-effectiveness, time savings, enhanced reliability, and improved data collection and control capabilities.

Implementation of Modified Incremental Conductance MPPT A lgorithm in Grid Connected PV System Under Dynamic Climatic Conditions

Background: The main goal of the grid-connected Photo Voltaic (PV) system is to extract maximum power from the array with reduced loss by using an appropriate MPPT method. Methods: A boost converter topology with linear INCMPPT algorithm is used to provide maximum power of 100 kW from the solar PV array to the grid. The integral regulator in the modified algorithm minimizes the error and guarantees exact control of the duty cycle of the DC-DC converter to produce constant DC voltage 500V with a minimum error of 2V. This proposed methodology perfectly matches with the optimal design of the DC-AC converter (inverter) for grid integration. A three-level IGBT-based voltage source inverter and filters are designed to supply pure AC voltage to the existing 100 kW grid. Detailed simulation work is completed using MATLAB/ Simulink software to prove the effectiveness of the proposed algorithm under various temperature (25-50◦C) and irradiance (200-1000W/m2) levels. Findings: The proposed MPPT algorithm is simple and effective in reducing the error required for the duty cycle correction from 0.45 to 0.518 and eliminating the oscillations at MPP. By using this methodology, the output voltage of the boost converter is adjusted to match the reference value. The simulation results reveal the better performance of the grid-connected PV system with the modified incremental conductance MPPT method. This modified INC MPPT algorithm exactly controls the duty cycle of the boost converter to provide better settling time and low ripples in the grid parameters. Novelty: This article provides a simple and effective improved incremental conductance (INC) MPPT algorithm to minimize the tracking error (1.5%). No additional tuning and selection of parameters, computational burden and memory are required for the implementation of the proposed control algorithm. Keywords: Gridconnected photovoltaic (PV) system; Maximum power point tracking (MPPT); Voltage Source Inverter (VSI); Boost converter; Incremental conductance (INC)

Artificial Neural Network Assisted Variable Step Size Incremental Conductance MPPT Method with Adaptive Scaling Factor

In conventional adaptive variable step size (VSS) maximum power point tracking (MPPT) algorithms, a scaling factor is utilized to determine the required perturbation step. However, the performance of the adaptive VSS MPPT algorithm is essentially decided by the choice of scaling factor. In this paper, a neural network assisted variable step size (VSS) incremental conductance (IncCond) MPPT method is proposed. The proposed method utilizes a neural network to obtain an optimal scaling factor that should be used in current irradiance level for the VSS IncCond MPPT method. Only two operating points on the characteristic curve are needed to acquire the optimal scaling factor. Hence, expensive irradiance and temperature sensors are not required. By adopting a proper scaling factor, the performance of the conventional VSS IncCond method can be improved, especially under rapid varying irradiance conditions. To validate the studied algorithm, a 400 W prototyping circuit is built and experiments are carried out accordingly. Comparing with perturb and observe (P&O), α-P&O, golden section and conventional VSS IncCond MPPT methods, the proposed method can improve the tracking loss by 95.58%, 42.51%, 93.66%, and 66.14% under EN50530 testing condition, respectively.

Comparison of PO and INC MPPT Methods Using FPGA In-The-Loop Under Different Radiation Conditions

The Maximum Power Point Tracking (MPPT) algorithms are applied to obtain maximum efficiency under different atmospheric conditions in photovoltaic (PV) systems. Perturb&Observe (PO) and Incremental Conductance (INC) methods are the oldest algorithms used among MPPT methods. Field Programmable Gate Arrays (FPGA) are used especially in applications requiring high speed. FPGA in-the-loop feature is used to test algorithms designed in MATLAB/Simulink environment. In this study, PO and INC methods have been designed to work in FPGA environment. Both algorithms have been tested under different radiation conditions using FPGA-in-the-loop feature. The FPGA in-the-loop simulation result of PO and INC methods has been graphically shown. In this study, Altera DE2-115 development board was used to test PO and INC MPPT algorithms. On the other hand, PO and INC methods were synthesized using the Quartus-II program. Comparisons of simplicity of algorithms were made according to synthesis results. Thus, by using the FGPA in-the-loop feature and performing the synthesis process, both the algorithms were tested and the areas covered by the algorithms in the FPGA were compared.

Effect of Various Incremental Conductance MPPT Methods on the Charging of Battery Load Feed by Solar Panel

The presented work in this paper deals with various step sizes used in incremental conductance (INC) related to the maximum power point tracking (MPPT) technique. In the solar photovoltaic system, the variable step size selection method for INC is proposed and compared. The MATLAB/Simulink and hardware setup are used for assessing and analyzing step size methods. The variable step size (DVS), fixed step size (DFS) are comprehensively studied and compared. This DVS method is having a lower ON delay time (Td <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ON</sub> ) as 148 msec as regard to 164 msec in the DFS method. On the other hand, the lowest peak-peak oscillations in load current as 0.04 amp for DVS as compared to 0.5A for the DFS method, lower peak current as 1.96A for DVS as compare to 2.37A for the DFS method. In this way, the performance of the DVS method is found superior as it is analyzed and compared with the DFS algorithm.

A Comparative analysis of Maximum Power Point Tracking Techniques for Battery Operated PV Systems at Different Temperatures

This paper presents a comparative analysis of Ripple Correlation Control (RCC) with conventional Maximum Power Point Tracking (MPPT) methods such as Perturb &amp; Observe (P&amp;O) and Incremental Conductance (IC). Photovoltaic (PV) array along with the buck converter and its MPPT control have been simulated for all three MPPT methods at different solar radiation levels at 25°C and 70°C and results have been compared. From the simulation results, it can be observed that P&amp;O is much affected with slow tracking and oscillations, and IC MPPT performs better than P&amp;O in terms of tracking, but not for ripples. Simulation results verifies that RCC MPPT is capable of solving both these problems effectively and RCC performance is better than both P&amp;O and IC MPPT methods.

Explicit one-step model and adaptive maximum power point tracking algorithm for a photovoltaic module

This paper presents an accurate, simplified, explicit, and fast computing one-step model for a practical photovoltaic (PV) module without the need of heavy offline calculations, lookup tables, or iterative methods. A closed-form expression of the model shaping factor is provided, which paves the way to explicitly locate the maximum power point (MPP). Based on the obtained closed-form shaping factor expression, an adaptive maximum power point tracking (MPPT) algorithm is proposed. The proposed adaptive MPPT algorithm is implemented in a field-programmable gate array (FPGA) and verified using an FPGA-in-the-loop simulation, under rapid changes in temperature and irradiance, with comparisons to perturb and observe (P&O) and incremental conductance (InCond) MPPT methods. Moreover, two experimental case studies are discussed to highlight the validity of the proposed work.

A Modified perturb-and-observe-based Maximum Power Point Tracking Technique for Photovoltaic Energy Conversion Systems

One of the most widely used maximum power point tracking (MPPT) methods in photovoltaic systems (PVSs) is perturb and observe (PO (2) the tracking deviation under sudden change as well as gradual variation in the irradiation conditions. This paper proposes a simple modified P&O-based MPPT method for PVSs in which the perturbation size is adaptively determined in such a way that the convergence speed to the MPP is increased and the undesirable oscillations around the MPP are decreased. In addition, the direction of the perturbations is determined on the basis of incremental conductance MPPT method so that the proposed algorithm is capable to extract the maximum power from the PVS, even under sudden or gradual variation in solar irradiation. The validity and effectiveness of the proposed algorithm are investigated using time-domain simulations in the MATLAB® software environment.

Maximum Power Point Tracking of PV Systems Based On a Novel Adaptive Variable Step Size INC MPPT Method

In the future solar energy will become a very important green energy. Maximum power point (MPP) tracking (MPPT) technology is widely used in solar photovoltaic (PV) systems to generate peak power for PV arrays that depend on solar irradiation and ambient temperature. Literature[1] shows that the maximum power point tracking (MPPT) technology can improve the efficiency of photoelectric conversion by more than 20% and the economic cost is relatively low. Based on PROTUES, the output characteristics of PV arrays under different shadow conditions are simulated and the rule between local maximum power point and open circuit voltage is obtained. Among all the MPPT strategies, the incremental conductance (INC) algorithm and perturb and observe (P&O) algorithm are widely used due to the high tracking accuracy at steady state and easy implementation.In this paper, a novel adaptive variable step size INC MPPT method is proposed according to the above rule. This algorithm not only has the advantage of INC, but also can automatically adjust the step size to track the maximum power point of PV arrays. Compared with the adaptive perturb and observe (P&O) algorithm, the proposed approach can effectively improve the MPPT steady-state response speed and accuracy simultaneously. The theoretical analysis and design principle of the proposed algorithm are presented in this paper. The simulation results show that the algorithm can accurately track the maximum power point (MPP) with shadow. The average tracking time is only 0.13 seconds, and the power tracking efficiency reaches 98%.

Comparative Analysis of Reduced-Rule Compressed Fuzzy Logic Control and Incremental Conductance MPPT Methods

Photovoltaic (PV) power generation has been widely used in recent years, with techniques for increasing the power efficiency representing one of the most important issues. The available maximum power of a PV panel is dependent on environmental conditions such as solar irradiance and temperature. To extract the maximum available power from a PV panel, various maximum-power-point tracking (MPPT) methods are used. In this work, two different MPPT methods were implemented for a 150-W PV panel. The first method, known as incremental conductance (Inc. Cond.) MPPT, determines the maximum power by measuring the derivative of the PV voltage and current. The other method is based on reduced-rule compressed fuzzy logic control (RR-FLC), using which it is relatively easier to determine the maximum power because a single input variable is used to reduce computing loads. In this study, a 150-W PV panel system model was realized using these MPPT methods in MATLAB and the results compared. According to the simulation results, the proposed RR-FLC-based MPPT could increase the response rate and tracking accuracy by 4.66% under standard test conditions.

Performance Analysis of Incremental Conductance MPPT with Simple Moving Voltage Average Method for Distributed PV System

In order to harvest photovoltaic energy efficiently, several methods exist, yet most of them failed to address the issues related to extract the maximum power under rapidly changing solar irradiance conditions. In conventional incremental conductance, large step size reduces tracking time but oscillation remains around maximum power point (MPP). However, small step size reduces the oscillation but results in slower tracking speed. This paper proposes a simple moving voltage average (SMVA) technique in conjunction with fixed step direct control incremental conductance (INC) maximum power point tracking (MPPT) method in order to reduce the photovoltaic (PV) generated voltage (VPV) fluctuation and power losses under mismatching solar irradiance conditions in distributed PV system. Theoretical analysis and the simulation results revealed that the proposed SMVA technique provides fast and accurate tracking under mismatching irradiance conditions. Also, it significantly improves the voltage stability because of extremely small |dP/dV| around MPP as compared to the conventional fixed step direct control incremental conductance MPPT method. Finally, results show that the proposed method is suitable for distributed PV system under intermittent weather conditions not only in terms of voltage stability but also in overall system efficiency.

Modified Particle Swarm Optimization technique based Maximum Power Point Tracking for uniform and under partial shading condition

Generation of electricity from solar energy has gained worldwide acceptance due to its abundant availability and eco-friendly nature. Even though the power generated from solar looks to be attractive; its availability is subjected to variation owing to many factors such as change in irradiation, temperature, shadow etc. Hence, extraction of maximum power from solar PV using Maximum Power Point Tracking (MPPT) method was the subject of study in the recent past. Among many methods proposed, Hill Climbing and Incremental Conductance MPPT methods were popular in reaching Maximum Power under constant irradiation. However, these methods show large steady state oscillations around MPP and poor dynamic performance when subjected to change in environmental conditions. On the other hand, bio-inspired algorithms showed excellent characteristics when dealing with non-linear, non-differentiable and stochastic optimization problems without involving excessive mathematical computations. Hence, in this paper an attempt is made by applying modifications to Particle Swarm Optimization technique, with emphasis on initial value selection, for Maximum Power Point Tracking. The key features of this method include ability to track the global peak power accurately under change in environmental condition with almost zero steady state oscillations, faster dynamic response and easy implementation. Systematic evaluation has been carried out for different partial shading conditions and finally the results obtained are compared with existing methods. In addition, simulations results are validated via built-in hardware prototype.

Implementation of a modified incremental conductance MPPT algorithm with direct control based on a fuzzy duty cycle change estimator using dSPACE

Maximum power point tracking (MPPT) is a necessary function in all photovoltaic (PV) systems. The classic incremental conductance (IC) MPPT algorithm is widely used in the literature. However, when large changes occur in the irradiance, the performance of this algorithm is degraded. To eliminate all of the disadvantages of the classic IC algorithm, we developed a new IC controller based on a fuzzy duty cycle change estimator with direct control. A fuzzy logic estimator (FLE) is used to estimate the new duty cycle used to track the PV array maximum power point. Compared with the fixed step IC MPPT method with direct control, the proposed algorithm reaches the MPP more accurately and faster during dynamic and steady-state conditions. A controlled Cuk DC–DC converter was implemented and connected to a SunTech STP085B PV panel to verify the accuracy of the proposed method. Matlab/Simulink was used for the simulation studies. Additionally, the algorithms were digitally implemented on the dSPACE ACE1104 platform. The results obtained confirm the advantages of the proposed algorithm.

퍼지 PI 제어기를 이용한 태양광 발전시스템의 MPPT 제어

This paper proposes the fuzzy PI controller for maximum power point tracking(MPPT) control of photovoltaic system. The output characteristics of the solar cell are a nonlinear and affected by a temperature, the solar radiation. The MPPT control is a very important technique in order to increase an output and efficiency of the photovoltaic system. The conventional perturbation and observation(PO) and incremental conductance(IC) are the method which finding maximum power point(MPP) by the continued self-excitation vibration, and uses the fixed step size. If the fixed step size is a large, the tracking speed of maximum power point is faster, but the tracking accuracy in the steady state is decreased. On the contrary, when the fixed step size is a small, the tracking accuracy is increased and the tracking speed is slower. Therefore, this paper proposes the MPPT control using the fuzzy PI controller that can be improve a MPPT control performance. The fuzzy PI controller is adjusted a input of PI controller by fuzzy control and compensated a cumulative error of fuzzy control by PI controller. The fuzzy PI MPPT control is compared to conventional PO and IC MPPT method for various temperature and radiation condition. This paper proves the validity of the fuzzy PI controller using these results.

Modified Asymmetrical Variable Step Size Incremental Conductance Maximum Power Point Tracking Method for Photovoltaic Systems

The power?voltage (P?V) characteristic of a photovoltaic (PV) array is nonlinear and time varying with the change in atmospheric conditions. As a result, the maximum power point tracking (MPPT) technique must be applied in PV systems to maximize the generated energy. The incremental conductance (INC) algorithm, one of the MPPT strategies, is widely used for its high tracking accuracy, good adaptability to rapidly changing atmospheric conditions, and easy implementation. This paper presents a modified asymmetrical variable step size INC MPPT method that is based on the asymmetrical feature of the P?V curve. Compared with conventional fixed or variable step size method, the proposed method can effectively improve tracking accuracy and speed. The theoretical foundation and design principle of the proposed approach are validated by the simulation and experimental results.

A Maximum Power Point Tracker with Automatic Step Size Tuning Scheme for Photovoltaic Systems

The purpose of this paper is to study on a novel maximum power point tracking (MPPT) method for photovoltaic (PV) systems. First, the simulation environment for PV systems is constructed by using PSIM software package. A 516 W PV system established with Kyocera KC40T photovoltaic modules is used as an example to finish the simulation of the proposed MPPT method. When using incremental conductance (INC) MPPT method, it usually should consider the tradeoff between the dynamic response and the steady-state oscillation, whereas the proposed modified incremental conductance method based on extension theory can automatically adjust the step size to track the maximum power point (MPP) of PV array and effectively improve the dynamic response and steady-state performance of the PV systems, simultaneously. Some simulation and experimental results are made to verify that the proposed extension maximum power point tracking method can provide a good dynamic response and steady-state performance for a photovoltaic power generation system.

A Single-Stage Three-Phase Grid-Connected Photovoltaic System With Modified MPPT Method and Reactive Power Compensation

Single-stage grid-connected photovoltaic (PV) systems have advantages such as simple topology, high efficiency, etc. However, since all the control objectives such as the maximum power point tracking (MPPT), synchronization with the utility voltage, and harmonics reduction for output current need to be considered simultaneously, the complexity of the control scheme is much increased. This paper presents the implementation of a single-stage three-phase grid-connected PV system. In addition to realize the aforementioned control objectives, the proposed control can also remarkably improve the stability of the MPPT method with a modified incremental conductance MPPT method. The reactive power compensation for local load is also realized, so as to alleviate grid burden. A DSP is employed to implement the proposed MPPT controller and reactive power compensation unit. Simulation and experimental results show the high stability and high efficiency of this single-stage three-phase grid-connected PV system.