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  • Open Access

    ARTICLE

    Feature Extraction and Classification of Photovoltaic Panels Based on Convolutional Neural Network

    S. Prabhakaran1,*, R. Annie Uthra1, J. Preetharoselyn2

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1437-1455, 2023, DOI:10.32604/cmc.2023.032300

    Abstract Photovoltaic (PV) boards are a perfect way to create eco-friendly power from daylight. The defects in the PV panels are caused by various conditions; such defective PV panels need continuous monitoring. The recent development of PV panel monitoring systems provides a modest and viable approach to monitoring and managing the condition of the PV plants. In general, conventional procedures are used to identify the faulty modules earlier and to avoid declines in power generation. The existing deep learning architectures provide the required output to predict the faulty PV panels with less accuracy and a more time-consuming process. To increase the… More >

  • Open Access

    ARTICLE

    Optimization of the Placement and Size of Photovoltaic Source

    Maawiya Ould Sidi1,*, Mustafa Mosbah2, Rabie Zine3

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1855-1870, 2023, DOI:10.32604/cmc.2023.030032

    Abstract This paper presents a new optimization study of the placement and size of a photovoltaic source (PVS) in a distribution grid, based on annual records of meteorological parameters (irradiance, temperature). Based on the recorded data, the production output as well as the daily average power (24-h vector) of the PVS is extracted over the year. When a power vector is available, it can be used as an input when searching for the optimal size of the PVS. This allows to take into account the constraint of the variation of the power generated by this source considering the variation of the… More >

  • Open Access

    ARTICLE

    An Experimental Study on the Performance of a Hybrid Photovoltaic/Thermal Solar System

    Xin Xu1,*, Lian Zhang1,2,*

    Energy Engineering, Vol.119, No.6, pp. 2319-2345, 2022, DOI:10.32604/ee.2022.022457

    Abstract Considered as the widespread renewable energy, solar energy is used to produce the electricity and heat for carbon peaking and carbon neutralization. However, the photo-electric conversion efficiency will decrease with the increase of cells temperature. To solve this problem, a water-type hybrid photovoltaic/thermal (PV/T) solar system has been designed and tested in Hong Kong. The outdoor experiment proceeded all days in 6 months with three different operating modes. The data of selected 33 days were used to analyze the performance of the system. The results showed that the thermal efficiencies were 33.6%, 52%, and 48.3% at zero reduced temperature, corresponding… More >

  • Open Access

    ARTICLE

    Ghost-RetinaNet: Fast Shadow Detection Method for Photovoltaic Panels Based on Improved RetinaNet

    Jun Wu, Penghui Fan, Yingxin Sun, Weifeng Gui*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1305-1321, 2023, DOI:10.32604/cmes.2022.020919

    Abstract Based on the artificial intelligence algorithm of RetinaNet, we propose the Ghost-RetinaNet in this paper, a fast shadow detection method for photovoltaic panels, to solve the problems of extreme target density, large overlap, high cost and poor real-time performance in photovoltaic panel shadow detection. Firstly, the Ghost CSP module based on Cross Stage Partial (CSP) is adopted in feature extraction network to improve the accuracy and detection speed. Based on extracted features, recursive feature fusion structure is mentioned to enhance the feature information of all objects. We introduce the SiLU activation function and CIoU Loss to increase the learning and… More >

  • Open Access

    ARTICLE

    Analysis and Power Quality Improvement in Hybrid Distributed Generation System with Utilization of Unified Power Quality Conditioner

    Noor Zanib1, Munira Batool1, Saleem Riaz2, Farkhanda Afzal3, Sufian Munawar4, Ibtisam Daqqa5, Najma Saleem5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1105-1136, 2023, DOI:10.32604/cmes.2022.021676

    Abstract This paper presents a comprehensive study that includes the sizing and power flow by series and parallel inverters in a distributed generation system (DGs) that integrates the system of hybrid wind photovoltaic with a unified power quality conditioner (UPQC). In addition to supplying active power to the utility grid, the system of hybrid wind photovoltaic functions as a UPQC, compensating reactive power and suppressing the harmonic load currents. Additionally, the load is supplied with harmonic-free, balanced and regulated output voltages. Since PVWind-UPQC is established on a dual compensation scheme, the series inverter works like a sinusoidal current source, while the… More >

  • Open Access

    ARTICLE

    Research on Volt/Var Control of Distribution Networks Based on PPO Algorithm

    Chao Zhu1, Lei Wang1, Dai Pan1, Zifei Wang2, Tao Wang2, Licheng Wang2,*, Chengjin Ye3

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 599-609, 2023, DOI:10.32604/cmes.2022.021052

    Abstract In this paper, a model free volt/var control (VVC) algorithm is developed by using deep reinforcement learning (DRL). We transform the VVC problem of distribution networks into the network framework of PPO algorithm, in order to avoid directly solving a large-scale nonlinear optimization problem. We select photovoltaic inverters as agents to adjust system voltage in a distribution network, taking the reactive power output of inverters as action variables. An appropriate reward function is designed to guide the interaction between photovoltaic inverters and the distribution network environment. OPENDSS is used to output system node voltage and network loss. This method realizes… More >

  • Open Access

    ARTICLE

    Training Neuro-Fuzzy by Using Meta-Heuristic Algorithms for MPPT

    Ceren Baştemur Kaya1, Ebubekir Kaya2,*, Göksel Gökkuş3

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 69-84, 2023, DOI:10.32604/csse.2023.030598

    Abstract It is one of the topics that have been studied extensively on maximum power point tracking (MPPT) recently. Traditional or soft computing methods are used for MPPT. Since soft computing approaches are more effective than traditional approaches, studies on MPPT have shifted in this direction. This study aims comparison of performance of seven meta-heuristic training algorithms in the neuro-fuzzy training for MPPT. The meta-heuristic training algorithms used are particle swarm optimization (PSO), harmony search (HS), cuckoo search (CS), artificial bee colony (ABC) algorithm, bee algorithm (BA), differential evolution (DE) and flower pollination algorithm (FPA). The antecedent and conclusion parameters of… More >

  • Open Access

    ARTICLE

    Genetic Algorithm Based Smart Grid System for Distributed Renewable Energy Sources

    M. Mythreyee*, Dr A. Nalini

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 819-837, 2023, DOI:10.32604/csse.2023.028525

    Abstract This work presents the smart grid system for distributed Renewable Energy Sources (RES) with control methods. The hybrid MicroGrids (MG) are trending in small-scale power systems that involve distributed generations, power storage, and various loads. RES of solar are implemented with boost converter using Maximum Power Point Tracking (MPPT) with perturb and observe technique to track the maximum power. Also, the wind system is designed by permanent magnet synchronous generator that includes boost converter with MPPT technique. The battery is also employed with a Direct Current (DC)-DC bidirectional converter, and has a state of charge. The MATLAB/Simulink Simscape software is… More >

  • Open Access

    ARTICLE

    Deep Learning-Based Model for Defect Detection and Localization on Photovoltaic Panels

    S. Prabhakaran1,*, R. Annie Uthra1, J. Preetharoselyn2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2683-2700, 2023, DOI:10.32604/csse.2023.028898

    Abstract The Problem of Photovoltaic (PV) defects detection and classification has been well studied. Several techniques exist in identifying the defects and localizing them in PV panels that use various features, but suffer to achieve higher performance. An efficient Real-Time Multi Variant Deep learning Model (RMVDM) is presented in this article to handle this issue. The method considers different defects like a spotlight, crack, dust, and micro-cracks to detect the defects as well as localizes the defects. The image data set given has been preprocessed by applying the Region-Based Histogram Approximation (RHA) algorithm. The preprocessed images are applied with Gray Scale… More >

  • Open Access

    ARTICLE

    Optimization of Adaptive Fuzzy Controller for Maximum Power Point Tracking Using Whale Algorithm

    Mehrdad Ahmadi Kamarposhti1,*, Hassan Shokouhandeh2, Ilhami Colak3, Kei Eguchi4

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5041-5061, 2022, DOI:10.32604/cmc.2022.031583

    Abstract The advantage of fuzzy controllers in working with inaccurate and nonlinear inputs is that there is no need for an accurate mathematical model and fast convergence and minimal fluctuations in the maximum power point detector. The capability of online fuzzy tracking systems is maximum power, resistance to radiation and temperature changes, and no need for external sensors to measure radiation intensity and temperature. However, the most important issue is the constant changes in the amount of sunlight that cause the maximum power point to be constantly changing. The controller used in the maximum power point tracking (MPPT) circuit must be… More >

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