A Dragonfly Optimization Algorithm for Extracting Maximum Power of Grid-Interfaced PV Systems

Currently, grid-connected Photovoltaic (PV) systems are widely encouraged to meet increasing energy demands. However, there are many urgent issues to tackle that are associated with PV systems. Among them, partial shading is the most severe issue as it reduces efficiency. To achieve maximum power, PV system utilizes the maximum power point-tracking (MPPT) algorithms. This paper proposed a two-level converter system for optimizing the PV power and injecting that power into the grid network. The boost converter is used to regulate the MPPT algorithm. To make the grid-tied PV system operate under non-uniform weather conditions, dragonfly optimization algorithm (DOA)-based MPPT was put forward and applied due to its ability to trace the global peak and its higher efficiency and shorter response time. Furthermore, in order to validate the overall performance of the proposed technique, comparative analysis of DOA with adaptive cuckoo search optimization (ACSO) algorithm, fruit fly optimization algorithm combined with general regression neural network (FFO-GRNN), improved particle swarm optimization (IPSO), and PSO and Perturb and Observe (P&O) algorithm were presented by using Matlab/Simulink. Subsequently, a voltage source inverter (VSI) was utilized to regulate the active and reactive power injected into the grid with high efficiency and minimum total harmonic distortion (THD). The instantaneous reactive power was adjusted to zero for maintaining the unity power factor. The results obtained through Matlab/Simulink demonstrated that power injected into the grid is approximately constant when using the DOA MPPT algorithm. Hence, the grid-tied PV system’s overall performance under partial shading was found to be highly satisfactory and acceptable.

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Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading

Electronics ◽

10.3390/electronics9111962 ◽

2020 ◽

Vol 9 (11) ◽

pp. 1962

Author(s):

Muhammad Hamza Zafar ◽

Thamraa Al-shahrani ◽

Noman Mujeeb Khan ◽

Adeel Feroz Mirza ◽

Majad Mansoor ◽

...

Keyword(s):

Particle Swarm Optimization ◽

Statistical Analysis ◽

Optimization Algorithm ◽

Maximum Power ◽

Pv System ◽

Maximum Power Point ◽

Partial Shading ◽

Swarm Optimization ◽

Pv Systems ◽

Power Point

The most cost-effective electrical energy is produced by photovoltaic (PV) systems, and with the smallest carbon footprint, making it a sustainable renewable energy. They provide an excellent alternative to the existing fossil fuel-based energy systems, while providing 4% of global electricity demand. PV system efficiency is significantly reduced by the intrinsic non-linear model, maximum power point (MPP), and partial shading (PS) effects. These two problems cause major power loss. To devise the maximum power point tracking (MPPT) control of the PV system, a novel group teaching optimization algorithm (GTOA) based controller is presented, which effectively deals with the PS and complex partial shading (CPS) conditions. Four case studies were employed that included fast-changing irradiance, PS, and CPS to test the robustness of the proposed MPPT technique. The performance of the GTOA was compared with the latest bio-inspired techniques, i.e., dragon fly optimization (DFO), cuckoo search (CS), particle swarm optimization (PSO), particle swarm optimization gravitational search (PSOGS), and conventional perturb and observe (P&O). The GTOA tracked global MPP with the highest 99.9% efficiency, while maintaining the magnitude of the oscillation <0.5 W at global maxima (GM). Moreover, 13–35% faster tracking times, and 54% settling times were achieved, compared to existing techniques. Statistical analysis was carried out to validate the robustness and effectiveness of the GTOA. Comprehensive analytical and statistical analysis solidified the superior performance of the proposed GTOA based MPPT technique.

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A Modification of the Perturb and Observe Method to Improve the Energy Harvesting of PV Systems under Partial Shading Conditions

Energies ◽

10.3390/en14092521 ◽

2021 ◽

Vol 14 (9) ◽

pp. 2521

Author(s):

Alfredo Gil-Velasco ◽

Carlos Aguilar-Castillo

Keyword(s):

Maximum Power ◽

Global Maximum ◽

Pv System ◽

Maximum Power Point ◽

Partial Shading ◽

Pv Systems ◽

Point Tracking ◽

Power Point Tracking ◽

Power Point ◽

Computational Resources

There are multiples conditions that lead to partial shading conditions (PSC) in photovoltaic systems (PV). Under these conditions, the harvested energy decreases in the PV system. The maximum power point tracking (MPPT) controller aims to harvest the greatest amount of energy even under partial shading conditions. The simplest available MPPT algorithms fail on PSC, whereas the complex ones are effective but require high computational resources and experience in this type of systems. This paper presents a new MPPT algorithm that is simple but effective in tracking the global maximum power point even in PSC. The simulation and experimental results show excellent performance of the proposed algorithm. Additionally, a comparison with a previously proposed algorithm is presented. The comparison shows that the proposal in this paper is faster in tracking the maximum power point than complex algorithms.

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A Comparative Study on Maximum Power Point Tracking Techniques of Photovoltaic Systems

International Journal of Energy Optimization and Engineering ◽

10.4018/ijeoe.2018010104 ◽

2018 ◽

Vol 7 (1) ◽

pp. 66-85 ◽

Cited By ~ 2

Author(s):

Afef Badis ◽

Mohamed Habib Boujmil ◽

Mohamed Nejib Mansouri

Keyword(s):

High Efficiency ◽

Maximum Power Point Tracking ◽

Maximum Power ◽

Pv System ◽

Maximum Power Point ◽

Partial Shading ◽

Point Tracking ◽

Power Point Tracking ◽

Conventional Methods ◽

Power Point

This article concerns maximizing the energy reproduced from the photovoltaic (PV) system, ensured by using an efficient Maximum Power Point Tracking (MPPT) process. The process should be fast, rigorous and simple for implementation because the PV characteristics are extremely affected by fast changing conditions and Partial Shading (PS). PV systems are popularly known to have many peaks (one Global Peak (GP) and several local peaks). Therefore, the MPPT algorithm should be able to accurately detect the unique GP as the maximum power point (MPP), and avoid any other peak to mitigate the effect of (PS). Usually, with no shading, nearly all the conventional methods can easily reach the MPP with high efficiency. Nonetheless, they fail to extract the GP when PS occurs. To overcome this problem, Evolutionary Algorithms (AEs), namely the Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are simulated and compared to the conventional methods (Perturb & Observe) under the same software.

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Stochastic Fractal Search Optimization Algorithm Based Global MPPT for Triple-Junction Photovoltaic Solar System

Energies ◽

10.3390/en13184971 ◽

2020 ◽

Vol 13 (18) ◽

pp. 4971

Author(s):

Hegazy Rezk ◽

Ahmed Fathy

Keyword(s):

Optimization Algorithm ◽

Triple Junction ◽

Maximum Power ◽

Global Maximum ◽

Pv System ◽

Maximum Power Point ◽

Partial Shading ◽

Power Point ◽

Global Mppt ◽

Stochastic Fractal Search

A significant growth in PV (photovoltaic) system installations have been observed during the last decade. The PV array has a nonlinear output characteristic because of weather intermittency. Partial shading is an environmental phenomenon that causes multiple peaks in the power curve and has a negative effect on the efficiency of the conventional maximum power point tracking (MPPT) methods. This tends to have a substantial effect on the overall performance of the PV system. Therefore, to enhance the performance of the PV system under shading conditions, the global MPPT technique is mandatory to force the PV system to operate close to the global maximum. In this paper, for the first time, a stochastic fractal search (SFS) optimization algorithm is applied to solve the dilemma of tracking the global power of PV system based triple-junction solar cells under shading conditions. SFS has been nominated because it can converge to the best solution at a fast rate. Moreover, balance between exploration and exploitation phases is one of its main advantages. Therefore, the SFS algorithm has been selected to extract the global maximum power point (MPP) under partial shading conditions. To prove the superiority of the proposed global MPPT–SFS based tracker, several shading scenarios have been considered. The idea of changing the shading scenario is to change the position of the global MPP. The obtained results are compared with common optimizers: Antlion Optimizer (ALO), Cuckoo Search (CS), Flower Pollination Algorithm (FPA), Firefly-Algorithm (FA), Invasive-Weed-Optimization (IWO), JAYA and Gravitational Search Algorithm (GSA). The results of comparison confirmed the effectiveness and robustness of the proposed global MPPT–SFS based tracker over ALO, CS, FPA, FA, IWO, JAYA, and GSA.

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A Simple Method for Detecting Partial Shading in PV Systems

Energies ◽

10.3390/en14164938 ◽

2021 ◽

Vol 14 (16) ◽

pp. 4938

Author(s):

Waleed Al Abri ◽

Rashid Al Abri ◽

Hassan Yousef ◽

Amer Al-Hinai

Keyword(s):

Accurate Method ◽

Maximum Power ◽

Global Maximum ◽

Pv System ◽

Maximum Power Point ◽

Simple Method ◽

Partial Shading ◽

Pv Systems ◽

Power Point ◽

Global Peak

Partial shading conditions (PSCs) can significantly reduce the output energy produced by photovoltaic (PV) systems. Moreover, when such conditions occur, conventional and advanced maximum power point tracking (MPPT) systems fail to operate the PV system at its peak because the bypassing diodes may cause the PV system to become trapped at a low power point when they are in conduction mode. The PV system can be operated at the global maximum power point (MPP) with the help of global peak searching tools. However, the frequent use of these tools will reduce the output of PV systems since they force the PV system to operate outside its power region while scanning the I-V curve in order to determine the global MPP. Thus, the global peak searching tools should be deployed only when a PSC occurs. In this paper, a simple and accurate method is proposed for detecting PSCs by means of monitoring the sign of voltage changes (positive or negative). The method predicts a PSC if the sign of successive voltage changes is the same for a certain number of successive changes. The proposed method was tested on two types of PV array configurations (series and series–parallel) with several shading patterns emulated on-site. The proposed method correctly and timely identified all emulated shading patterns. It can be used to trigger the global MPP searching techniques for improving the PV system’s output under PSCs; furthermore, it can be used to notify the PV system’s operator of the occurrence of PSCs.

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PV Solar-Optimal Maximum Power Search using a Modified P&O Technique

European Journal of Engineering Research and Science ◽

10.24018/ejers.2017.2.5.321 ◽

2017 ◽

Vol 2 (5) ◽

pp. 13

Author(s):

Mohamed Salama Ebrahim ◽

Adel M. Sharaf ◽

Ahmed M. Atallah ◽

Adel Sedky Emarah

Keyword(s):

Smart Grid ◽

Reactive Power ◽

Search Algorithm ◽

Digital Simulation ◽

Maximum Power ◽

Energy Utilization ◽

Pv System ◽

Partial Shading ◽

Point Tracking ◽

Power Point

Smart Grid- PV system interface requires power electronic converter interface and robust optimal controller to ensure maximum solar energy utilization. This paper presents a new Controller based on an optimized search algorithm for maximum power point tracking controller performance using a modified Perturb and Observe P&O Algorithm for a smart grid connected PV DC-AC interface system. The modified P & O method is based on dividing the change of the power into three distinct zones with assigned zone- duty cycle ratio of the Chopper converter (D) has an initial preset value. The feasibility of the proposed method is easily implemented using proportional plus integral and fuzzy logic controllers. The controllers are assumed to control the active output power through adjusting of the dc bus voltage as well as the reactive power given to the ac smart grid network. Digital simulation results of a comparison with conventional P&O approach reflects the fast conversion and dynamic superiority of the new algorithm even under both uniform and partial shading conditions. Furthermore, the active and reactive output powers are regulated at the inverter interface with smart grid.

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A novel PV array interconnection scheme to extract maximum power based on global shade dispersion using grey wolf optimization algorithm under partial shading conditions

Circuit World ◽

10.1108/cw-07-2020-0143 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Balraj R. ◽

Albert Alexander Stonier

Keyword(s):

Optimization Algorithm ◽

Energy Systems ◽

Maximum Power ◽

Grey Wolf ◽

Grey Wolf Optimization ◽

Partial Shading ◽

Content Type ◽

Pv Systems ◽

Pv Array ◽

Grey Wolf Algorithm

Purpose Partial shading causes significant power decreases in the PV systems. The purpose of this paper is to address this problem, connectivity regulation is designed to reduce partial shading problems. Design/methodology/approach In this approach, the partial shading was estimated and dispersed evenly on the whole array by global shade dispersion technique (GSD). The grey wolf algorithm was implemented for the interconnection of arrays by an efficient switching matrix. Findings After the implementation of the GSD technique using a grey wolf algorithm, the performance under different shading conditions was analyzed using the MatLab simulation tool. The results were compared with total cross-tied (TCT), Su Do Ku and the proposed method of reconfiguration, where the proposed method improves the maximum power of the PV system appropriately. Research limitations/implications This methodology uses any size of PV systems. Social implications Replacement of conventional energy systems with renewable energy systems such as solar helps the environment clean and green. Originality/value The GSD interconnection scheme using the grey wolf optimization algorithm has proved an improved output performance compared with the existing TCT and Sudoku based reconfiguration techniques. By comparing with existing techniques in literature, the proposed method is more advantageous for reducing mismatch losses between the modules of any size of the PV array with less operating time.

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Maximum power point tracking of partially shading PV system using cuckoo search algorithm

International Journal of Power Electronics and Drive Systems (IJPEDS) ◽

10.11591/ijpeds.v10.i2.pp1081-1089 ◽

2019 ◽

Vol 10 (2) ◽

pp. 1081 ◽

Cited By ~ 2

Author(s):

Ahmed Ibrahim ◽

Raef Aboelsaud ◽

Sergey Obukhov

Keyword(s):

High Efficiency ◽

Search Algorithm ◽

Cuckoo Search ◽

Cuckoo Search Algorithm ◽

Maximum Power ◽

Global Maximum ◽

Pv System ◽

Maximum Power Point ◽

Partial Shading ◽

Power Point

This paper presents a cuckoo search (CS) algorithm for determining the global maximum power point (GMPP) tracking of photovoltaic (PV) under partial shading conditions (PSC). The conventional methods are fail to track the GMPP under PSC, which decrease the reliability of the power system and increase the system losses. The performance of the CS algorithm is compared with perturb and observe (P&O) algorithm for different cases of operations of PV panels under PSC. The CS algorithm used in this work to control directly the duty cycle of the DC-DC converter without proportional integral derivative (PID) controller. The proposed CS model can track the GMPP very accurate with high efficiency in less time under different conditions as well as in PSC.

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PHOTOVOLTAIC MODELING METHODS BASED ON MATLAB SIMULINK IMPLEMENTATION

SINERGI ◽

10.22441/sinergi.2018.1.001 ◽

2018 ◽

Vol 22 (1) ◽

pp. 1

Author(s):

Azriyenni Azhari Zakri ◽

Nurhalim Nurhalim ◽

Dohardo P.H. Simanulang ◽

Ihwallibi Tribowo

Keyword(s):

Renewable Energy ◽

Power Plant ◽

Energy Development ◽

Maximum Power ◽

Photovoltaic System ◽

Pv System ◽

Matlab Simulink ◽

Pv Systems ◽

Modeling Methods ◽

Renewable Energy Development

This paper presents photovoltaic system as a stand-alone electric power plant in the renewable energy development. To maximize these stand-alone generators, it is necessary to design photovoltaic modeling to produce energy and maximum power. The problems that exist in the design of PV systems are PV configuration, battery size, and the maximum power system. Therefore, this research will be proposed modeling Matlab/Simulink based PV system. The contribution of this research can provide various characteristics of the photovoltaic system with a capacity of 100 Wp. This modeling is designed using Matlab/Simulink software. The data generated from this simulation will provide a good reference for designing the stand-alone generators in the future.

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PV Systems Control Using Fuzzy Logic Controller Employing Dynamic Safety Margin under Normal and Partial Shading Conditions

Energies ◽

10.3390/en14040841 ◽

2021 ◽

Vol 14 (4) ◽

pp. 841 ◽

Cited By ~ 1

Author(s):

Mostafa Bakkar ◽

Ahmed Aboelhassan ◽

Mostafa Abdelgeliel ◽

Michael Galea

Keyword(s):

Fuzzy Logic ◽

Performance Index ◽

Safety Margin ◽

Operating Conditions ◽

Maximum Power ◽

Practical Implementation ◽

Pv System ◽

Partial Shading ◽

Pv Systems ◽

A Performance

Because of the unpredictable activity of solar energy sources, photovoltaic (PV) maximum power point tracking (MPPT) is essential to guarantee the continuous operation of electrical energy generation at optimal power levels. Several works have extensively examined the generation of the maximum power from the PV systems under normal and shading conditions. The fuzzy logic control (FLC) method is one of the effective MPPT techniques, but it needs to be adapted to work in partial shading conditions. The current paper presents the FLC-based on dynamic safety margin (DSM) as an MPPT technique for a PV system to overcome the limitations of FLC in shading conditions. The DSM is a performance index that measures the system state deviation from the normal situation. As a performance index, DSM is used to adapt the FLC controller output to rapidly reach the global maxima of the PV system. The ability of the proposed algorithm and its performance are evaluated using simulation and practical implementation results for single phase grid-connected PV system under normal and partial shading operating conditions.

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