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  • Open Access


    Spotted Hyena-Bat Optimized Extreme Learning Machine for Solar Power Extraction

    K. Madumathi1,*, S. Chandrasekar2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1821-1836, 2023, DOI:10.32604/csse.2023.029561

    Abstract Artificial intelligence, machine learning and deep learning algorithms have been widely used for Maximum Power Point Tracking (MPPT) in solar systems. In the traditional MPPT strategies, following of worldwide Global Maximum Power Point (GMPP) under incomplete concealing conditions stay overwhelming assignment and tracks different nearby greatest power focuses under halfway concealing conditions. The advent of artificial intelligence in MPPT has guaranteed of accurate following of GMPP while expanding the significant performance and efficiency of MPPT under Partial Shading Conditions (PSC). Still the selection of an efficient learning based MPPT is complex because each model has its advantages and drawbacks. Recently,… More >

  • Open Access


    Research on the MPPT of Photovoltaic Power Generation Based on the CSA-INC Algorithm

    Tao Hou1, Shan Wang1,2,*

    Energy Engineering, Vol.120, No.1, pp. 87-106, 2023, DOI:10.32604/ee.2022.022122

    Abstract The existing Maximum Power Point Tracking (MPPT) method has low tracking efficiency and poor stability. It is easy to fall into the Local Maximum Power Point (LMPP) in Partial Shading Condition (PSC), resulting in the degradation of output power quality and efficiency. It was found that various bio-inspired MPPT based optimization algorithms employ different mechanisms, and their performance in tracking the Global Maximum Power Point (GMPP) varies. Thus, a Cuckoo search algorithm (CSA) combined with the Incremental conductance Algorithm (INC) is proposed (CSA-INC) is put forward for the MPPT method of photovoltaic power generation. The method can improve the tracking… More > Graphic Abstract

    Research on the MPPT of Photovoltaic Power Generation Based on the CSA-INC Algorithm

  • Open Access


    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 >

  • Open Access


    Evaluation of On-Line MPPT Algorithms for PV-Based Battery Storage Systems

    Belqasem Aljafari1, Eydhah Almatrafi2,3,4, Sudhakar Babu Thanikanti5, Sara A. Ibrahim6, Mohamed A. Enany6,*, Marwa M. Ahmed7

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3595-3611, 2022, DOI:10.32604/cmc.2022.030733

    Abstract This paper presents a novel Simulink models with an evaluation study of more widely used On-Line Maximum Power Point tracking (MPPT) techniques for Photo-Voltaic based Battery Storage Systems (PV-BSS). To have a full comparative study in terms of the dynamic response, battery state of charge (SOC), and oscillations around the Maximum Power Point (MPP) of the PV-BSS to variations in climate conditions, these techniques are simulated in Matlab/Simulink. The introduced methodologies are classified into two types; the first type is conventional hill-climbing techniques which are based on instantaneous PV data measurements such as Perturb & Observe and Incremental Conductance techniques.… More >

  • Open Access


    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

    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 the switch in the DC-DC… More >

  • Open Access


    A Modified-Simplified MPPT Technique for Three-Phase Single-State Grid-Connected PV Systems

    Anuchit Aurairat, Boonyang Plangklang*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2375-2395, 2022, DOI:10.32604/cmc.2022.025122

    Abstract Nowadays, the single state inverter for the grid-connected photovoltaic (PV) systems is becoming more and more popular as they can reduce circuit complexity resulting in less power losses of the inverter. This paper focuses on the use of model predictive control (MPC) to control a 3-phase and 2-level single-state grid-connected inverter in order to regulate the PV maximum power point (MPP). The algorithm of MPC scheme was done to measure the simultaneous current signal including predicting the next sampling current flow. The reference current (Id*) was used to control the distribution of electrical power from the solar cell to the… More >

  • Open Access


    Hybrid Microgrid based on PID Controller with the Modified Particle Swarm Optimization

    R. K. Rojin1,*, M. Mary Linda2

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 245-258, 2022, DOI:10.32604/iasc.2022.021834

    Abstract Microgrids (MG) are distribution networks encompassing distributed energy sources. As it obtains the power from these resources, few problems such as instability along with Steady-State (SS) issues are noticed. To address the stability issues, that arise due to disturbances of low magnitude. Small-Signals Stability (SSS) becomes mandatory in the network. Convergence at local optimum is one of the major issues noticed with the existing optimization algorithms. This paper proposes a detailed model of SSS in Direct Current (DC)-Alternate Current (AC) Hybrid MG (HMG) using Proportional Integral and Derivative Controller (PIDC) tuned with Modified Particle Swarm Optimization (MPSO) algorithm to alleviate… More >

  • Open Access


    OBSO Based Fractional PID for MPPT-Pitch Control of Wind Turbine Systems

    Ibrahim M. Mehedi1,2,*, Ubaid M. Al-Saggaf1,2, Mahendiran T. Vellingiri1, Ahmad H. Milyani1, Nordin Bin Saad3, Nor Zaihar Bin Yahaya3

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4001-4017, 2022, DOI:10.32604/cmc.2022.021981

    Abstract In recent times, wind energy receives maximum attention and has become a significant green energy source globally. The wind turbine (WT) entered into several domains such as power electronics that are employed to assist the connection process of a wind energy system and grid. The turbulent characteristics of wind profile along with uncertainty in the design of WT make it highly challenging for prolific power extraction. The pitch control angle is employed to effectively operate the WT at the above nominal wind speed. Besides, the pitch controller needs to be intelligent for the extraction of sustainable secure energy and keep… More >

  • Open Access


    Enhanced Atom Search Optimization Based Optimal Control Parameter Tunning of PMSG for MPPT

    Xin He1, Ping Wei2, Xiaoyan Gong1, Xiangfei Meng3, Dong Shan4, Jiawei Zhu5,*

    Energy Engineering, Vol.119, No.1, pp. 145-161, 2022, DOI:10.32604/EE.2022.015910

    Abstract For the past few years, wind energy is the most popular non-traditional resource among renewable energy resources and it’s significant to make full use of wind energy to realize a high level of generating power. Moreover, diverse maximum power point tracking (MPPT) methods have been designed for varying speed operation of wind energy conversion system (WECS) applications to obtain optimal power extraction. Hence, a novel and meta-heuristic technique, named enhanced atom search optimization (EASO), is designed for a permanent magnet synchronous generator (PMSG) based WECS, which can be employed to track the maximum power point. One of the most promising… More >

  • Open Access


    A Machine Learning Based Algorithm to Process Partial Shading Effects in PV Arrays

    Kamran Sadiq Awan1, Tahir Mahmood1, Mohammad Shorfuzzaman2, Rashid Ali3, Raja Majid Mehmood4,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 29-43, 2021, DOI:10.32604/cmc.2021.014824

    Abstract Solar energy is a widely used type of renewable energy. Photovoltaic arrays are used to harvest solar energy. The major goal, in harvesting the maximum possible power, is to operate the system at its maximum power point (MPP). If the irradiation conditions are uniform, the P-V curve of the PV array has only one peak that is called its MPP. But when the irradiation conditions are non-uniform, the P-V curve has multiple peaks. Each peak represents an MPP for a specific irradiation condition. The highest of all the peaks is called Global Maximum Power Point (GMPP). Under uniform irradiation conditions,… More >

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