Incremental Conductance Algorithm Research Articles

Design of Maximum Power Point Tracking Photovoltaic System Based on Incremental Conductance Algorithm using Arduino Uno and Boost Converter

Fossil fuel reserves are limited while the growing demand for energy utilization. It leads to an acceleration of renewable energy use. One of the renewable energy resources is solar energy, called the photovoltaic system. This paper uses a photovoltaic solar system consisting of a solar panel module, DC-DC boost converter, voltage divider, ACS712 as a current sensor, Arduino Uno, and load resistor. Maximum Power Point Tracking (MPPT) controller is implemented to track the maximum power point of the solar panel system using a boost converter based on the Incremental Conductance algorithm embedded in Arduino UNO. The PV system with MPPT controller is designed with PV 20 W. The testing of the ACS712 current sensor and voltage sensor show error values of about 1.82% and 0.83%, respectively, which are acceptable limits. Besides, the DC-DC boost converter is also tested, and its performance shows an increase in the output voltage. The test result of the PV system with MPPT control based on the Incremental Conductance algorithm shows the average value of the PV power output with resistive load at 36 Ω is about 7.34 W, while the PV system without MPPT is about 6.07 W. Thus, the Photovoltaic system using MPPT controller based on the incremental conductance algorithm can control PV power output at the maximum power point.

Step Incremental Conductance MPPT for Solar PV System Based on Fuzzy Logic Controller

Due to strong industrial expansion, the need for electrical power has increased in recent years. As more than just a by-product of this increased dependence on fossil fuels, resource depletion occurs, and renewable sources such as solar, wind, and wave energy sources have begun to operate as an electricity source and are now playing a key role. Solar energy has been widely used in power systems, particularly in the form of photovoltaic (PV) generating units. Control scheme is a technique for obtaining electricity from a solar photovoltaic system under changing environmental circumstances. The proposed research compares two control methods: incremental conductance algorithm and fuzzy logic, in order to maximise the efficiency of a solar PV system. The algorithms described above change the switching frequency of the power converter to monitor a solar PV array's global MPP. In MATLAB/Simulink, the simulation is run, and the performance is evaluated. The simulated findings imply that the fuzzy logic controller performs better than the incremental conductance technique.

Design of a maximum power point tracking-based PID controller for DC converter of stand-alone PV system

Stand-alone photovoltaic system (PV) produces a variance in the output voltage under variable irradiation and temperature, and variable load conditions, resulting in control challenges. The research scope is to maintain a constant output load voltage despite variations in input voltage or load. The use of a DC converter ensures that the output voltage of such systems remains constant regardless of changes in the production voltage and load. The control on a DC boost converter is employed to solve this problem. This paper presents the design of a maximum power point tracking-based (MPPT) DC converter controller for such a system. The MPPT-based PID has been proposed as a control approach and implemented to the system DC converter. Incremental Conductance (IC) algorithm has been employed as an MPPT in association with an optimized PID. The Particle Swarm optimization technique (PSO) has been used to optimize the proposed PID through selected cost function. The PV system with the loaded converter is modeled and simulated using the MATLAB/Simulink environment. The system performance is displayed using a family of curves under different operating conditions and disturbances.

An improved search ability of particle swarm optimization algorithm for tracking maximum power point under shading conditions

Introduction. Extracting maximum possible power from solar energy is a hot topic of the day as other sources have become costly and lead to pollution. Problem. Dependency on sunlight for power generation makes it unfeasible to extract maximum power. Environmental conditions like shading, partial shading and weak shading are the major aspect due to which the output of photovoltaic systems is greatly affected. Partial shading is the most known issue. Goal. There have been many proposed techniques and algorithms to extract maximum output from solar resources by use of photovoltaic arrays but every technique has had some shortcomings that couldn’t serve the complete purpose. Methodology. Nature inspired algorithms have proven to be good to search global maximum in a partially shaded multipeak curve which includes particle swarm optimization, artificial bee colony algorithm, and flower pollination algorithm. Methods. Particle swarm optimization algorithm is best among these in finding global peaks with less oscillation around maximum power point, less complexity, and easy to implement nature. Particle swarm optimization algorithm has the disadvantage of having a long computational time and converging speed, particularly under strong shading conditions. Originality. In this paper, an improved opposition based particle swarm optimization algorithm is proposed to track the global maximum power point of a solar photovoltaic module. Simulation studies have been carried out in MATLAB/Simulink R2018a. Practical value. Simulation studies have proved that opposition based particle swarm optimization algorithm is more efficient, less complex, more robust, and more flexible and has better convergence speed than particle swarm optimization algorithm, perturb and observe algorithm, hill climbing algorithm, and incremental conductance algorithm.

Advanced three-stage photovoltaic system phasor model for grid integration dynamic studies

As the penetration of photovoltaic (PV) generation increases at different system voltage levels, their impact on the power grid operation and control is more important to analyze. Hence, suitable PV models must be developed with which it is possible to carry out dynamic analysis for fair-sized electrical networks. This is a demanding task, computationally-wise, for detailed switching-based PV models using small numerical integration steps required by the associated power electronic devices. In this sense, an advanced three-stage PV system phasor model is proposed in this paper whose hallmark resides in the proper characterization of the PV arrays and DC/DC converter through a nonlinear potential regression technique in combination with the generatrix method. As a result, the PV operating surfaces, as function of irradiance and temperature, can be determined and used for the calculation of virtual resistances relating to the PV optimal operation and internal power losses. The virtual resistances are seamlessly combined with a developed AC/DC converter phasor model for efficient dynamic simulations of electrical networks.The new PV model has been thoroughly validated using Simscape Electrical of Simulink where an electrical network with one PV system is dynamically simulated. The outcomes of the developed model are compared to those obtained from switching-based PV models based on different maximum power tracking strategies, i.e., the incremental conductance (IC) and perturbation and observation (P&O) algorithms. The impact of the PV system on the power grid operation and the accuracy of results are assessed, demonstrating that the proposed model favorably agrees with the benchmark switching-based PV models as errors inferior to 2 % are obtained. Furthermore, it is confirmed that the new PV system model enables faster dynamic simulations than what it is possible to achieve with switching-based models since it is 28.82 times faster than the PV model based on the IC algorithm and 31.80 times faster than that using the P&O technique.

Benefits of Fuzzy Logic on MPPT and PI Controllers in the Chain of Photovoltaic Control Systems

This paper presents a comparative study between two maximum power point tracking (MPPT) algorithms, the incremental conductance algorithm (InC) and the fuzzy logic controller (FLC). The two algorithms were applied to a low photovoltaic power conversion system, and they both use different PI controllers and grid synchronization techniques. Moreover, both InC and FLC methods have Clarke and Park Transformation. To some extent, the incremental conductance and fuzzy logic controller approaches are similar, but their control loops are different. Therefore, the InC has classic Proportional Integrative (PI) controllers with simple phase-locked loops (PLL). At the same time, the FLC works with fuzzy logic PI controllers linked with the Second Order Generalized Integrator (SOGI). The proposed techniques examine the solar energy conversion performance of the photovoltaic (PV) system under possible irradiance changes and constant temperature conditions. Finally, a performance comparison has been made between InC and FLC, which demonstrates the effectiveness of the fuzzy controller over the incremental conductance algorithm. FLC turns to convert photovoltaic power easily, decreasing fluctuations, and it offers a quick response to the variation of solar irradiance (shading effect). The simulation results show a superior performance of the controller with fuzzy logic, which helps the inverter convert over 99% of the power generated by the photovoltaic panels. In comparison, the incremental conductance algorithm converts around 80%.

Linear Quadratic Regulator and Fuzzy Control for Grid-Connected Photovoltaic Systems

This work presents a control scheme to control a grid-connected single-phase photovoltaic (PV) system. The considered system has four 250 W solar panels, a non-inverting buck-boost DC-DC converter, and a DC-AC inverter with an inductor-capacitor-inductor (LCL) filter. The control system aims to track and operate at the maximum power point (MPP) of the PV panels, regulate the voltage of the DC link, and supply the grid with a unity power factor. To achieve these goals, the proposed control system consists of three parts: an MPP tracking controller module with a fuzzy-based modified incremental conductance (INC) algorithm, a DC-link voltage regulator with a hybrid fuzzy proportional-integral (PI) controller, and a current controller module using a linear quadratic regulator (LQR) for grid-connected power. Based on fuzzy control and an LQR, this work introduces a full control solution for grid-connected single-phase PV systems. The key novelty of this research is to analyze and prove that the newly proposed method is more successful in numerous aspects by comparing and evaluating previous and present control methods. The designed control system settles quickly, which is critical for output stability. In addition, as compared to the backstepping approach used in our past study, the LQR technique is more resistant to sudden changes and disturbances. Furthermore, the backstepping method produces a larger overshoot, which has a detrimental impact on efficiency. Simulation findings under various weather conditions were compared to theoretical ones to indicate that the system can deal with variations in weather parameters.

Optimizing of the installed capacity of hybrid renewable energy with a modified MPPT model

The lack of wind speed capacity and the emission of photons from sunlight are the problem in a hybrid system of photovoltaic (PV) panels and wind turbines. To overcome this shortcoming, the incremental conductance (IC) algorithm is applied that could control the converter work cycle and the switching of the buck boost therefore maximum efficiency of maximum power point tracking (MPPT) is reached. The operation of the PV-wind hybrid system, consisting of a 100 W PV array device and a 400 W wind subsystem, 12 V/100 Ah battery energy storage and LED, the PV-wind system requires a hybrid controller for battery charging and usage and load lamp and it’s conducted in experimental setup. The experimental has shown that an average increase in power generated was 38.8% compared to a single system of PV panels or a single wind turbine sub-system. Therefore, the potential opportunities for increasing power production in the tropics wheather could be carried out and applied with this model.

Maximum power harvesting from a PV system using an improved two-stage MPPT scheme based on incremental conductance algorithm and integral controller

Maximum power harvesting from a PV system using an improved two-stage MPPT scheme based on incremental conductance algorithm and integral controller

Maximum power harvesting from a PV system using an improved two-stage MPPT scheme based on incremental conductance algorithm and integral controller

Maximum power harvesting from a PV system using an improved two-stage MPPT scheme based on incremental conductance algorithm and integral controller

Flatness based Control of Single Phase Grid Connected Photovoltaic System Associated with a Shunt Active Power Filter

The present paper proposes a new controller design method based on the flatness approach of single-phase full bridge shunt active power filter (SAPF) connected to photovoltaic system. The main control objective is threefold: (i) extracting the maximum active power in the output photovoltaic panel using an appropriate maximum power point tracking (MPPT) algorithm; (ii) regulation of the voltage of the DC link capacitor with the MPPT requirement to ensure the power exchanged between PV source and AC power grid; (iii) compensation for undesired harmonic and reactive currents caused by the non-linearity of electronic power loads, i.e. power factor correction (PFC). In this paper, the problem is dealt with designing a new two-loop cascaded controller in which the inner loop is constructed using a flatness approach to ensure the unity power factor. The outer loop consists mainly of filtered proportional-integral (PI) regulator, that assures a tight regulation of the voltage across the photovoltaic panel with an incremental conductance (IC) algorithm to meet MPPT requirement. The theoretical model and its controller are validated by numerical simulation within the MATLAB/SimPowerSystems environment.

Maximum Power Point Tracking Using the Incremental Conductance Algorithm for PV Systems Operating in Rapidly Changing Environmental Conditions

Maximum Power Point Tracking Using the Incremental Conductance Algorithm for PV Systems Operating in Rapidly Changing Environmental Conditions

A Total-Cross-Tied-Based Dynamic Photovoltaic Array Reconfiguration for Water Pumping System

Most Photo-voltaic (PV) applications require a shadow-free area for the installation of the PV panels. However, shading is inevitable in a few applications like building-integrated PV pumping systems (BIPVPS). Partial shading occurs due to soiling, clouds, shades of nearby trees, buildings, current, and telephone poles. During this partial shading condition, the PV array output power decreases, reducing the efficiency of the BIPVPS. In this paper, a novel dynamic array reconfiguration technique is proposed to enhance the power output from the PV array. The proposed system uses a boost converter with an incremental conductance algorithm for operating enhanced power at the maximum. Sinusoidal Pulse Width Modulation (SPWM) technique based on <inline-formula> <tex-math notation="LaTeX">$V/f$ </tex-math></inline-formula> control operates the induction motor. Thus, the proposed algorithm and maximum power point technique (MPPT) enhance the power output from the PV array and track the global power. The PI and <inline-formula> <tex-math notation="LaTeX">$V/f$ </tex-math></inline-formula> control regulate the dc-link voltage and speed of the Induction motor. Simulations and experimental studies are performed to show the effectiveness of the proposed algorithm. The proposed system results in additional 234 W PV power extraction compared to the conventional system. Thus, making the proposed BIPVPS efficient.

A grid interconnected nested neutral point clamped inverter with voltage synchronization using synchronous reference frame controller

&lt;p&gt;&lt;span lang="EN-US"&gt;Nested neutral point clamped multi level inverter with inter connection to grid through the synchronous reference frame (SRF) controller for synchronization of voltage to the grid is demonstrated. The system's main feature is that voltage stress in each inverter switching device is kept to a minimum, and redundant inverter switching states are utilised for neutral point and flying capacitor voltage balancing with sinusoidal pulse-width modulation (PWM) technique, synchronisation to grid voltages, and power injection with low harmonic generation. The inverter receives its input from a photovoltaic (PV) source that is coupled to DC-DC booster converters that are regulated by the maximum power point tracking (MPPT) incremental conductance algorithm to maintain a constant dc voltage. The system is examined under various load conditions with MATLAB Simulink model.&lt;/span&gt;&lt;/p&gt;

A grid interconnected nested neutral-point clamped inverter with voltage synchronization using synchronous reference frame controller

&lt;p&gt;&lt;span lang="EN-US"&gt;Nested neutral-point clamped multi level inverter with inter connection to grid through the synchronous reference frame (SRF) controller for synchronization of voltage to the grid is demonstrated. The system's main feature is that voltage stress in each inverter switching device is kept to a minimum, and redundant inverter switching states are utilised for neutral point and flying capacitor voltage balancing with sinusoidal pulse-width modulation (PWM) technique, synchronisation to grid voltages, and power injection with low harmonic generation. The inverter receives its input from a photovoltaic (PV) source that is coupled to DC-DC booster converters that are regulated by the maximum power point &lt;span lang="EN-US"&gt;(MPP)&lt;/span&gt; tracking incremental conductance algorithm to maintain a constant dc voltage. The system is examined under various load conditions with MATLAB/Simulink model.&lt;/span&gt;&lt;/p&gt;

Energy Management of a Renewable Hybrid Isolated DC Microgrid

Abstract: Hybrid microgrid is the key solution to energize remote rural areas. The microgrid system incorporates more than one Distributed Renewable Energy (DRE) source to complement one another. This paper proposes a hybrid DC microgrid system to be operated in isolated mode. The proposed microgrid consists of a PMSG based Wind Turbine, PV array, and Lead-acid battery as an energy storage device. The Wind Turbine generator is connected to the DC bus through a Three-phase Diode Bridge Rectifier. The PV array is tied to the DC bus by a Boost converter and incremental conductance algorithm is used to extract the maximum power from the PV array. The battery uses a bidirectional converter for charging and discharging. A simple PI-based closed-loop control system is incorporated for proper energy management. The bus voltage is maintained either by the boost converter or the bidirectional converter depending upon the operating condition. The proposed microgrid system is modeled in MATLAB/SIMULINK software. Simulation of this model is done for varying irradiance, temperature, wind condition, and different load condition. The simulation results show that the system is stable under various load and supply conditions. Keywords: Hybrid microgrid, Distributed Renewable Energy (DRE), PMSG, PV array, DC bus, Boost converter, incremental conductance, bidirectional converter

Multipurpose water storage tank based DC microgrid system for isolated communities

AbstractRenewable energy sources can contribute a lot to deliver reliable/resilient power to isolated communities and the world's sustainable energy future. In this paper, a novel DC microgrid system has been proposed for multipurpose use for isolated communities. The system taps the unused potential of the storage water to generate electricity. The system is configured to reduce complexity and cost by reducing the sensors in the solar pumping unit. Source, storage, and loads are the parts of an isolated system. The DC microgrid includes solar PV, battery, and domestic loads (All types' loads, that is, DC, AC, and dynamic loads). Incremental conductance algorithm has been chosen for the MPPT control, and sliding mode controls have been implemented to supply the sinusoidal supply for the AC loads. The system has included a battery unit to support the DC bus voltage and stable DC microgrid operation. The centrifugal pump has been taken to operate the pump as a turbine to extract the partial power potential from the water. The proposed system's MATLAB/Simulink model was designed for a village and presented as a case study.

Design and Implementation of Modified INC, Conventional INC, and Fuzzy Logic Controllers Applied to a PV System under Variable Weather Conditions

Maximum power point tracking (MPPT) algorithms are used in photovoltaic applications to extract the maximum power that the photovoltaic (PV) panel can produce, which depends on two inputs that are: temperature and irradiance. A DC-DC converter is inserted between the photovoltaic panel and the load to obtain the desired voltage level on the load side. In this paper, incremental conductance (INC) algorithm, modified INC, and fuzzy logic controller (FLC) are designed and assessed to improve energy conversion efficiency. These algorithms are applied to the control of boost converter for tracking the maximum power point (MPP). The modified INC offers fast response and good performance in terms of oscillations than conventional INC and FLC. The Matlab/Simulink environment is used to analyze, interpret the simulation results, and show the performances of each algorithm; and Proteus-based Arduino environment is used to implement the three methods in order to compare the Matlab simulation results with measurements acquired during implementation that is similar to real experiment.

Maximum Power Point Tracking for Photovoltaic Panels Using Model Predictive Control and Incremental Conductance

— In this work, a novel maximum power point tracking algorithm (MPPT) based on Model Predictive Control (MPC) for photovoltaic systems is proposed. The considered system is composed by a photovoltaic panel connected to a load using a flyback converter. The proposed approach combines MPC with a modified Incremental Conductance algorithm with a variable step size, verified in this work to be more efficient than the Perturb and Observe algorithm in tracking maximum power point, making the PV system to generate more energy. Computational simulations are carried out to compare the performance of the considered MPPT algorithms, analyzing the output voltage and output power behavior at the photovoltaic panel. The results of the simulations show that the proposed algorithm provides better performance for the photovoltaic system than the main MPPT algorithms in the literature.

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.