Variable Step Size Incremental Conductance Research Articles

Improved Incremental Conductance MPPT Technique Designed to Addressing Drift Problem in a Photovoltaic System

Many researchers have concentrated on improving the efficiency of photovoltaic (PV) systems by optimizing control mechanisms aimed at extracting the maximum power from PV panels. The variable step size incremental conductance control (VSS-INC) technique has been the primary focus of the majority of these studies. However, this strategy faces challenges in the form of drift when confronted with swift changes in solar irradiation, temperature variations, and resistive load fluctuations. In addressing this issue, the present study proposes an innovative VSS-INC method. It is suggested to utilize a buck-boost converter as an impedance adaptor in achieving maximum power point tracking (MPPT). This involves controlling the duty cycle and aligning its input with that of the PV module. The efficiency of the suggested approach was evaluated through MATLAB software, and the outcomes were compared with traditional algorithms across various operational scenarios. Simulation results demonstrate the notably satisfactory and efficient performance of the proposed method when compared to conventional approaches.

A new approach to MPPT hybrid incremental conductance-sliding mode control for PV grid-connected

As photovoltaic energy is clean, renewable, and less noisy, it is increasingly integrated into the grid. This integration aims to overcome energy deficits and get rid of pollution from conventional sources. In this paper, a two-stage configuration of PV energy conversion to a three-phase grid has been studied. The control of this configuration can be divided into two parts, such as DC bus control and AC bus control. The DC bus is controlled by MPPT control. The AC bus is controlled by DC link voltage control, phase-looked loop control, and voltage source inverter control. The contribution in this study aims to improve the quality of energy injected via a new hybrid approach to MPPT control. The proposed control is a combination of robust sliding-mode control and incremental inductance. Unlike conventional hybridization, the proposed control estimates correct the error upon entry of the conductance incremental control. This correction provides an adaptive incremental step for increment conductance control. The proposed control is compared with three other controls under MATLAB/Simulink. Such as incremental conductance, variable step size incremental conductance, and conventional hybrid MPPT incremental inductance-sliding mode control. The simulation results show a remarkable minimization of the ripple phenomenon and the chatter phenomenon. Thus, the quality of the energy injected into the network is improved, such as by reducing the total harmonic distortion of the current and increasing efficiency.

Optimizing Solar Energy Harvesting: Supervised Machine Learning-Driven Peak Power Point Tracking for Diverse Weather Conditions

Solar Power is one of the significant prevalent forms of clean energy due to its perceived to be pollution-free and easily accessible. The market for renewable energy was established by the rapid development in electrical energy consumption and the diminution of conventional energy resources (CER). Under varying weather condition extracted energy from solar system is not constant and maximum. This study suggests the applicability of machine learning algorithm (MLA) in Peak power point tracking (P3T) methods to maximize power of a PV arrangement under varying weather conditions. Machine learning methods optimize peak power point tracking in solar photovoltaic systems by bringing agility, data-driven decision-making, and increased accuracy. MLAs improve the overall efficiency, stability, and dependability of these systems by handling the unpredictability of solar energy production under varying weather circumstances and PSCs Because MLAs are able to learn and adjust to non-linear relationships between solar intensity and PVS output. In this study, the squared multiple squared exponential Gaussian process regression method SGPRA tested in three rapidly varying ecological conditions. The performance of ML-P3T methods is validated using Matlab/Simulink, and the simulation outcome are compared with one of the most used algorithms, the variable step size incremental conductance algorithm (VINA). The Matlab/Simulink findings show that SGPRA operates significantly better under varying weather circumstances, harnessing more peak power efficiency 90%, shorter tracking time 0.13 sec, a mean error of 0.042, and superior stability.

Fuzzy assisted optimal tilt control approach for LFC of renewable dominated micro-grid: A step towards grid decarbonization

Grid decarbonization is very crucial for the energy transition. The massive penetration of renewables in conventional power networks is the essential step for decarbonization but at the cost of complex control architecture. Due to the stochastic behaviour of renewables, load frequency control (LFC) is a very tedious task. This paper addresses the LFC issue in a standalone micro-grid (S-μG) via wild horse optimizer (WHO) assisted intelligent fuzzy tilt integral derivative with filter – one plus integral (FTIDF-(1 + I)) controller. The proposed S-μG consists of a solar photovoltaic (PV), wind turbine (WT) generator (WTG), and diesel engine generator (DEG) as power generating units and a flywheel as the energy storage unit (ESU). A nonlinear WTG model is used to extract the power from varying wind speeds, and a variable step size incremental conductance (V-InC) maximum power point (MPP) tracking (MPPT) technique is considered to harvest the optimal power from PV. To replicate the practical scenarios, nonlinearities of the governor, turbine, and flywheel are also considered in this work. The proposed intelligent WHO-FTIDF-(1 + I) controller can handle huge uncertainties and nonlinearities of the considered μG. FTIDF-(1 + I) controller prominence has been established over TIDF and FTIDF controllers. The effectiveness of WHO has been demonstrated over particle swarm optimization (PSO) and grey wolf optimization (GWO). From the obtained results, it is perceived that the reduction in maximum frequency deviation Δf with the proposed controller as compared to WHO-TIDF, WHO-FTIDF, PSO-FTIDF-(1 + I), and GWO-FTIDF-(1 + I) are 99.75%, 97.71%, 94.87% and 33.34% respectively. Finally, detailed robustness analysis, stability evaluation and real-power system validation via the IEEE 39 bus system of the proposed controller are also performed.

Evaluation of a comprehensive power management system with maximum power point tracking algorithm for multiple microbial fuel cell energy harvesting

This study presents a comprehensive power management system (PMS) capable of tracking the maximum power point (MPP) and harvesting the energy from up to five microbial fuel cells (MFCs). The harvested energy from the MFCs was used to power the electronics, and in cases where this power was insufficient, alternative backup power options can be used. The voltage can be increased up to 3.3 V, and a hysteresis-based control approach was utilised to regulate the output voltage. The MPP of each MFC was determined using a variable step size incremental conductance algorithm that controls the duty cycle of the synchronous boost converters. No additional electronic components are necessary for the operation of the N and P-channel MOSFETs. The efficiency of the PMS relies on the target output voltage and the power output characteristics of the MFCs. Efficiencies of up to 87 % were achieved by combining the outputs of each MFC boost converter. To save energy, some electronic components are disabled when not in use, and the maximum power consumption of the PCB is below 5.8 mW at an output voltage of 3.3 V. The PMS is applied to simulated and real tubular MFCs under various operating conditions.

Modeling and Simulation of Modified MPPT Techniques under Varying Operating Climatic Conditions

Enhancing the performance of photovoltaic (PV) systems has recently become a key concern because of the market demand for green energy. To obtain the most possible power from the solar module, it is imperative to allow the PV system to operate at its maximum power point (MPP) regardless of the climatic conditions. In this study, a comparison of distinctive Maximum Power-Point Tracking (MPPT) techniques is provided, which are Perturb and Observe (P&O) and Modified Variable Step-Size P&O, as well as Incremental Conductance (INC) and Modified Variable Step-Size INC, using a boost converter for two types of solar panels. Using MATLAB software, simulations have been performed to assess the efficiency of the solar module under several environmental conditions, standard test conditions (STCs), and sudden and ramp variations in both solar irradiance and temperature. The output power efficiency, time response, and steady-state power oscillations have all been taken into account in this study. The simulation results of the improved algorithms demonstrate an enhancement in the PV module performance over conventional algorithms in many factors including steady-state conditions, tracking time, and converter efficiency. Furthermore, a boost in the dynamic response in monitoring the MPP is observed in a variety of climatical circumstances. Moreover, the proposed P&O MPPT algorithm is implemented in a hardware system and the experimental results verified the effectiveness, regarding both fast-tracking speed and lower oscillations, of the proposed Variable Step-Size P&O algorithm and its superiority over the conventional P&O technique.

Maximum power extraction and DC-Bus voltage regulation in grid-connected PV/BES system using modified incremental inductance with a novel inverter control

Low ripples and variations in the DC-Bus voltage in single-phase Photovoltaic/Battery Energy Storage (PV/BES) grid-connected systems may cause significant harmonics distortion, instability, and reduction in power factor. The use of short-life electrolytic capacitor on the DC-Bus is considered a standard way for reducing these ripples and variations because of its large capacitance but results in short lifetime of the inverter. Replacing large electrolytic capacitors with small film capacitors can extend the lifetime of a PV/BES grid-connected system because small film capacitors have longer lifetime than large electrolytic capacitors. These film capacitors have low capacitance, which causes severe oscillations in the output current, and voltage drop due to huge ripples on the DC-Bus voltage. In this research, the main goal is to eliminate the output current ripples and voltage fluctuations associated with employing film capacitors. First, a modified incremental conductance (MIC) technique is proposed for tracking the maximum power by controlling the duty ratio of the DC-DC boost converter. Second, for the first time, a simple and novel d-q current regulation technique, which employs flowchart decision logic, is used in the DC-Bus control system for both the PV power system and the state of charge (SOC) of the BES. In this case, the DC-Bus controller is characterized by a cost-effective implementation because of its low sampling frequency. Although the presented approaches are successful in eliminating voltage distortion and fluctuations, they have unacceptable dynamic performance. Therefore, to improve the dynamic performance, BES was used to maintain a reliable and stable harvest from PV modules for varying loads while also increasing the dynamic performance of the overall system. The proposed PV/BES grid-connected systems, which employs a small 10-µF bus capacitor, is simulated and connected to the grid (230 V, 50 Hz). The DC-Bus voltage overshoot, undershoot and the total harmonics distortion (THD) of the output current for the proposed MIC are (1 V), (2.5 V) and (less than 5%), respectively. The average time response under rising radiation to track the global peak for MIC, traditional incremental conductance and variable step size incremental conductance are 1.403 s, 1.501 s and 1.113 s respectively. The obtained findings demonstrated the efficacy and superiority of the proposed d-q current control and MIC technique.

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.

Multi-Objective Grasshopper Optimization Based MPPT and VSC Control of Grid-Tied PV-Battery System

This article presents the control of a three-phase three-wire (3P-3W) dual-stage grid-tied PV-battery storage system using a multi-objective grass-hopper optimization (MOGHO) algorithm. The voltage source converter (VSC) control of the presented system is implemented with adaptive kernel width sixth-order maximum correntropy criteria (AKWSOMCC) and maximum power point tracking (MPPT) control is accomplished using the variable step-size incremental conductance (VSS-InC) technique. The proposed VSC control offers lower mean square error and better accuracy, convergence rate and speed as compared to peer adaptive algorithms, i.e., least mean square (LMS), least mean fourth (LMF), maximum correntropy criteria (MCC), etc. The adaptive Gaussian kernel width is a function of the error signal, which changes to accommodate and filter Gaussian and non-Gaussian noise signals in each iteration. The VSS-InC based MPPT is provided with a MOGHO based modulation factor for better and faster tracking of the maximum power point during changing solar irradiation. Similarly, an optimized gain conventional PI controller regulates the DC bus to improve the power quality, and DC link stability during dynamic conditions. The optimized DC-link generates an accurate loss component of current, which further improves the VSC capability of fundamental load current component extraction. The VSC is designed to perform multi-functional operations, i.e., harmonics elimination, reactive power compensation, load balancing and power balancing at point of common coupling during diverse dynamic conditions. The MOSHO based VSS-InC, and DC bus performance is compared to particle swarm optimization (PSO) and genetic algorithm (GA). The proposed system operates satisfactorily as per IEEE519 standards in the MATLAB simulation environment.

Modified Variable Step-Size Incremental Conductance MPPT Technique for Photovoltaic Systems

A highly efficient photovoltaic (PV) system requires a maximum power point tracker to extract peak power from PV modules. The conventional variable step-size incremental conductance (INC) maximum power point tracking (MPPT) technique has two main drawbacks. First, it uses a pre-set scaling factor, which requires manual tuning under different irradiance levels. Second, it adapts the slope of the PV characteristics curve to vary the step-size, which means any small changes in PV module voltage will significantly increase the overall step-size. Subsequently, it deviates the operating point away from the actual reference. In this paper, a new modified variable step-size INC algorithm is proposed to address the aforementioned problems. The proposed algorithm consists of two parts, namely autonomous scaling factor and slope angle variation algorithm. The autonomous scaling factor continuously adjusts the step-size without using a pre-set constant to control the trade-off between convergence speed and tracking precision. The slope angle variation algorithm mitigates the impact of PV voltage change, especially during variable irradiance conditions to improve the MPPT efficiency. The theoretical investigations of the new technique are carried out while its practicability is confirmed by simulation and experimental results.

Intelligent control of induction motor for photovoltaic water pumping system

This work aims to improve the performance of direct torque control (DTC) technique for induction motor based photovoltaic (PV) water pumping system (PVWPS). The innovative aspect of this work consists in introducing the adaptive fuzzy logic control and the fuzzy logic control techniques as alternative approaches to conventional DTC to control the PVWPS. To ensure a good operation of the PV array, a variable step size incremental conductance (VSS INC) is implemented. Simulation studies of the proposed topology based on intelligent approaches will be investigated using Matlab/Simulink under various operating conditions to validate the suitability of the proposed PVWPS. From the obtained results, the proposed control strategies appear to be very convenient for water pumping applications.Article HighlightsAn intelligent control based on the advanced techniques is proposed for PV water pumping system.An adaptive fuzzy logic PID approach and optimal fuzzy rules are proposed for better operation of PV system.The suggested PV water pumping system achieves better performance, in particular minimization of torque and flux ripples, reduction of torque overshoot and high dynamic response.

Ingenious golden section search MPPT algorithm for PEM fuel cell power system

Among several types of fuel cells available in the market, proton exchange membrane fuel cell (PEMFC) is characterized by low operating temperature, high efficiency and long lifetime. These advantages have prompted the PEM fuel cell to enter into several applications such as vehicle power sources, portable power and backup power applications. However, the PEM fuel cell faces several challenges due to the dependency of the output power on the operating condition like cell temperature and membrane water content. Under changing operating conditions, there is only one unique operating point for the fuel cell system with maximum output. Therefore, for better operation and optimal exploitation, the extraction of maximum power from PEM fuel cell is indispensable. This paper deals with the development golden section search (GSS)-based maximum power point tracking (MPPT) controller for PEMFC power system. To our knowledge, this paper is a first, if modest, attempt to develop a fuel cell MPPT controller based on golden section algorithm. The proposed GSS-based MPPT has been implemented and validated on fuel cell power system composed of 7 kW PEMFC supplying a resistive load via a DC/DC boost converter controlled using the proposed MPPT. Simulation results obtained using MATLAB/Simulink show that the proposed GSS MPPT outperforms the variable step size incremental conductance one in all test cases including cell temperature and membrane water content variations in terms of static as well as dynamic performances regarding all used metrics reducing by the way the response time by 34.33%, the overshoot and ripple by around 100% and with neglect oscillation around MPP improving as a consequence the fuel cell efficiency.

Comparative study of MPPT techniques for solar PV-based system

Electrical power generated from solar power plant is growing enormously due to rapidly growing demand, increasing usage of green and environment friendly energy sources and insufficiency of conventional energy resources like coal, gas and fossil fuels, etc. The relevance of renewable like wind and solar photo voltaic (PV) energy is rapidly growing. Renewable resources of energy are helpful in cutting the environment pollution. Because of irregular nature of renewable energy sources, the parametric control is needed in distributed generation (DG). This manuscript aims to enhance the sum of generated power from the solar PV arrangement. In a projected study, solar PV is used as source for generation of electrical power. The comparative studies for optimisation of the energy conversion efficiency of perturb and observe (P&O) and variable step size incremental conductance (VSS-IC)-based optimisation techniques are investigated on a MATLAB simulation-based system. The efficiency for this system without MPPT method is 83.76% and the output power for VSS-IC controller is 1,256 watts and P&O method is 1,113 watts with the efficiency of VSS-IC is 96.61% and P&O is 85.61%. Simulation investigation and results of PV arrangement are made to get its characteristics.

Comparative study of MPPT techniques for solar PV-based system

Electrical power generated from solar power plant is growing enormously due to rapidly growing demand, increasing usage of green and environment friendly energy sources and insufficiency of conventional energy resources like coal, gas and fossil fuels, etc. The relevance of renewable like wind and solar photo voltaic (PV) energy is rapidly growing. Renewable resources of energy are helpful in cutting the environment pollution. Because of irregular nature of renewable energy sources, the parametric control is needed in distributed generation (DG). This manuscript aims to enhance the sum of generated power from the solar PV arrangement. In a projected study, solar PV is used as source for generation of electrical power. The comparative studies for optimisation of the energy conversion efficiency of perturb and observe (P&O) and variable step size incremental conductance (VSS-IC)-based optimisation techniques are investigated on a MATLAB simulation-based system. The efficiency for this system without MPPT method is 83.76% and the output power for VSS-IC controller is 1,256 watts and P&O method is 1,113 watts with the efficiency of VSS-IC is 96.61% and P&O is 85.61%. Simulation investigation and results of PV arrangement are made to get its characteristics.

Application of Modified MPPT Algorithms: A Comparative Study between Different Types of Solar Cells

Due to the broad needs for energy as market demands, searching on how to improve the efficiency of the PV systems is an essential concern for researchers to worry about. So, it is crucial to force the PV system to work at its peak power point in order to get the maximum available power from the photovoltaic panel. This paper presents a comprehensive comparison between four Maximum Power Point Tracking (MPPT) Algorithms; Perturb and Observe (P&O), Incremental Conductance (INC), Modified Variable Step Size Perturb and Observe (M-VSS-P&O) and Modified Variable Step Size Incremental Conductance (M-VSS-INC) by using of the DC-DC boost converter for three different kinds of solar cells. These cells are polycrystalline KC200GT cell, monocrystalline shell SQ85 cell and thin film shell ST40 cell. Simulations have been performed using MATLAB-SIMULINK for the three types of solar cells to investigate their performance under both standard test conditions (STC) and slowly varying and sudden changes in solar irradiance. The study has considered the response time, output power efficiency and steady-state-oscillations. The simulation results of the modified algorithms show an improvement in the cell performance in steady state conditions, tracking time and boost converter efficiency as well as an enhancement in the dynamic response in tracking the maximum power point (MPP) in varying climatic conditions over conventional algorithms.

High-Performance Standalone Photovoltaic Water Pumping System Using Induction Motor

This work is aimed at achieving a simple and reduced-cost configuration of photovoltaic (PV) water pumping system (PVWPS) using an induction motor with high efficiency. The proposed PV system is composed of two stages of converters which the first one ensures the maximum power point by controlling the duty ratio of boost converter using variable step size incremental conductance (VSS INC) technique. Fuzzy logic control based on direct torque control is proposed to serve the purpose of operating an induction motor. Moreover, the combining of these proposed control strategies has been never discussed. The proposed control scheme is modeled and simulated in detail under MATLAB/Simulink software to evaluate its performance under fast variations of irradiance and daily climatic profile. The obtained simulation results using the suggested control strategies are compared to those using the most used method in the literature (variable step size perturb and observe (VSS P&O) algorithm). The simulation results indicate that the proposed PVWPS performed best in terms of the time of response; pumped water, flux ripples, and the stator currents are reduced.

A Novel Variable Step Size Incremental Conductance Method with an Adaptive Scaling Factor

In this paper, a novel variable step size (VSS) incremental conductance (INC) method with an adaptive scaling factor is proposed. The proposed technique utilizes the model-based state estimation method to calculate the irradiance level and then determine an appropriate scaling factor accordingly to enhance the capability of maximum power point tracking (MPPT). The fast and accurate tracking can be achieved by the presented method without the need for extra irradiance and temperature sensors. Only the voltage-and-current sets of any two operating points on the characteristic curve are needed to estimate the irradiance level. By choosing a proper scaling factor, the performance of the conventional VSS INC method can be improved. To validate the studied algorithm, a 600 W prototyping circuit is constructed and the performances are demonstrated experimentally. Compared to conventional VSS INC methods under the tested conditions, the tracking time is shortened by 31.8%. The tracking accuracy is also improved by 2.1% and 3.5%, respectively. Besides, tracking energy loss is reduced by 43.9% and 29.9%, respectively.

Stopping the Drift Problem in the Tracking of Maximum Power Point for Photovoltaic System by Using Modified Variable Step Size Incremental Conductance Method

Stopping the Drift Problem in the Tracking of Maximum Power Point for Photovoltaic System by Using Modified Variable Step Size Incremental Conductance Method

Single Stage Autonomous Solar Water Pumping System Using PMSM Drive

This article presents a single stage standalone solar photovoltaic (SPV) array fed water pumping system using a permanent magnet synchronous motor (PMSM). The vital contribution of this work includes: 1) development of the novel modified vector control, which improves the torque response of the system, 2) development of a novel single stage variable step size incremental conductance technique, which provides a fast maximum power point tracking and eliminates the need of intermediate stage dc–dc converter, and 3) introduction of SPV power feed-forward term, which accelerates the overall response of the system under dynamic conditions. This system includes a SPV array, a three-phase voltage source inverter (VSI), a PMSM and a pump. The SPV array converts solar energy into electrical energy. The VSI acts as power processing unit, which supplies desired currents to drive the PMSM. As the PMSM rotates, the pump coupled to the motor accomplishes the objective of water pumping. This system is modeled and simulated using MATLAB/Simulink with available simpower system toolbox and the behavior of the system under varying atmospheric conditions are validated experimentally on a developed prototype in the laboratory.

Study and comparison results of the field oriented control for photovoltaic water pumping system applied on two cities in Morocco

In this papier, a low-cost solar photovoltaic water pumping system based on an induction motor without the use of chemical energy storage is presented. In literature, we can find several Maximum Power Point Tracking Algorithms, the choice of the algorithm is according to the nature of application. In this article, Variable Step Size Incremental Conductance MPPT method has been developed since it is fast and has less oscillations. The studied photovoltaic pumping system contains a centrifugal pump which is driven by a three-phase asynchronous motor. To control the water flow, the field-oriented control has been implemented. The control system is applied on two cities with different climatic conditions to evaluate their performance. The photovoltaic pumping system is developed using the MATLAB/Simulink software to discuss the results obtained. Consequently, the proposed MPPT based on the incremental conductance variable step shows good performances in terms of efficiency and tracking speed.