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  • Open Access

    ARTICLE

    Hyperparameter Optimization Based Deep Belief Network for Clean Buses Using Solar Energy Model

    Shekaina Justin1,*, Wafaa Saleh1,2, Tasneem Al Ghamdi1, J. Shermina3

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1091-1109, 2023, DOI:10.32604/iasc.2023.032589 - 29 April 2023

    Abstract Renewable energy has become a solution to the world’s energy concerns in recent years. Photovoltaic (PV) technology is the fastest technique to convert solar radiation into electricity. Solar-powered buses, metros, and cars use PV technology. Such technologies are always evolving. Included in the parameters that need to be analysed and examined include PV capabilities, vehicle power requirements, utility patterns, acceleration and deceleration rates, and storage module type and capacity, among others. PVPG is intermittent and weather-dependent. Accurate forecasting and modelling of PV system output power are key to managing storage, delivery, and smart grids. With… More >

  • Open Access

    ARTICLE

    Data-Driven Approach for Condition Monitoring and Improving Power Output of Photovoltaic Systems

    Nebras M. Sobahi1,*, Ahteshamul Haque2, V S Bharath Kurukuru2, Md. Mottahir Alam1, Asif Irshad Khan3

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5757-5776, 2023, DOI:10.32604/cmc.2022.028340 - 28 December 2022

    Abstract Increasing renewable energy targets globally has raised the requirement for the efficient and profitable operation of solar photovoltaic (PV) systems. In light of this requirement, this paper provides a path for evaluating the operating condition and improving the power output of the PV system in a grid integrated environment. To achieve this, different types of faults in grid-connected PV systems (GCPVs) and their impact on the energy loss associated with the electrical network are analyzed. A data-driven approach using neural networks (NNs) is proposed to achieve root cause analysis and localize the fault to the… 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 - 16 August 2022

    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… 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 - 01 August 2022

    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… 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 - 28 July 2022

    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… More >

  • Open Access

    ARTICLE

    Optimum Tuning of Photovoltaic System Via Hybrid Maximum Power Point Tracking Technique

    M. Nisha1,*, M. Germin Nisha2

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1399-1413, 2022, DOI:10.32604/iasc.2022.024482 - 03 May 2022

    Abstract A new methodology is used in this paper, for the optimal tuning of Photovoltaic (PV) by integrating the hybrid Maximum Power Point Tracking (MPPT) algorithms is proposed. The suggested hybrid MPPT algorithms can raise the performance of PV systems under partial shade conditions. It attempts to address the primary research issues in partial shading conditions in PV systems caused by clouds, trees, dirt, and dust. The proposed system computes MPPT utilizing an innovative adaptive model-based approach. In order to manage the input voltage at the Maximum PowerPoint, the MPPT algorithm changes the duty cycle of… More >

  • Open Access

    ARTICLE

    Optimized CUK Converter Based 1Φ Grid Tied Photovoltaic System

    S. K. Janarthanan*, C. Kathirvel

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 33-50, 2022, DOI:10.32604/iasc.2022.023165 - 15 April 2022

    Abstract Renewable energy-based power generation, particularly photovoltaic (PV)-connected grid systems, has gained popularity in recent years due to its widespread adoption for residential and commercial customers of all sizes, from kilowatt (KW) to megawatt (MW). The purpose of this work is to demonstrate how an efficient CUK-integrated boost converter with continuous current flow may be used to maximise the output of solar arrays. The constant voltage at the converter output is maintained with increased dynamic performance using a Proportional Integral (PI) controller based on a hybrid optimization technique GWO-PSO (Grey Wolf Optimization-Particle Swarm Optimization). This hybrid More >

  • Open Access

    ARTICLE

    Total Cross Tied-Inverted Triangle View Configuration for PV System Power Enhancement

    P. Rajesh1,*, K. S. Saji2

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1531-1545, 2022, DOI:10.32604/iasc.2022.023331 - 24 March 2022

    Abstract Electricity can be generated from a photovoltaic cell depending on the amount of solar radiation received from the solar system. But due to some factors such as partial shade conditions, as the thickness of the shade increases, the peak power output from the solar photovoltaic system decreases. Photovoltaic cells can be connected in parallel and in series to generate the required voltage and power. Peak power can be obtained even under shade conditions using the appropriate configuration of solar cells. A novel configuration as Total Cross Tied-Inverted Triangle View (TCT-ITV) is developed in the research… More >

  • Open Access

    ARTICLE

    Performance Analysis of Photovoltaic Systems and Energy Return on the Environment Economy

    Murad A. A. Almekhlafi1, Fahd N. Al-Wesabi2,3, Anwer Mustafa Hilal4, Manar Ahmed Hamza4,*, Abdelzahir Abdelmaboud5, Mohammed Rizwanullah4

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 557-571, 2022, DOI:10.32604/iasc.2022.020576 - 26 October 2021

    Abstract Using fossil fuels and non-renewable forms of energy has many adverse effects on the global ecosystem, and global demand exceeds the limited available resources. Renewable energy is one of the essential elements of social and economic development in any civilized country. This study comprises a feasibility study of the implementation of PV systems in a hybrid diesel network and analyzes the relationship between the effective uses of photovoltaic systems, the return of energy to the environment, and that country’s national economy. As a potential solution for the public and private utilities, the sunny web design More >

  • Open Access

    ARTICLE

    Gaussian Kernel Based SVR Model for Short-Term Photovoltaic MPP Power Prediction

    Yasemin Onal*

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 141-156, 2022, DOI:10.32604/csse.2022.020367 - 08 October 2021

    Abstract Predicting the power obtained at the output of the photovoltaic (PV) system is fundamental for the optimum use of the PV system. However, it varies at different times of the day depending on intermittent and nonlinear environmental conditions including solar irradiation, temperature and the wind speed, Short-term power prediction is vital in PV systems to reconcile generation and demand in terms of the cost and capacity of the reserve. In this study, a Gaussian kernel based Support Vector Regression (SVR) prediction model using multiple input variables is proposed for estimating the maximum power obtained from… More >

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