Ezhilmathi Nagarathinam¹, Buvana Devaraju², Karthiyayini Jayamoorthy³, Padmavathi Radhakrishnan⁴, Santhana Lakshmi ChandraMohan⁵, Vijayakumar Perumal⁶, Karthikeyan Balakrishnan^7,*

Energy Engineering, Vol.121, No.8, pp. 2129-2142, 2024, DOI:10.32604/ee.2024.052280

Abstract Maximum Power Point Tracking (MPPT) is crucial for maximizing the energy output of photovoltaic (PV) systems by continuously adjusting the operating point of the panels to track the point of maximum power production under changing environmental conditions. This work proposes the design of an MPPT system for solar PV installations using the Differential Grey Wolf Optimizer (DGWO). It dynamically adjusts the parameters of the MPPT controller, specifically the duty cycle of the SEPIC converter, to efficiently track the Maximum Power Point (MPP). The proposed system aims to enhance the energy harvesting capability of solar PV More >

Bo Yang^1,2, Rui Xie¹, Zhengxun Guo^3,4,*

Energy Engineering, Vol.121, No.8, pp. 2009-2022, 2024, DOI:10.32604/ee.2024.049423

Abstract Maximum power point tracking (MPPT) technology plays a key role in improving the energy conversion efficiency of photovoltaic (PV) systems, especially when multiple local maximum power points (LMPPs) occur under partial shading conditions (PSC). It is necessary to modify the operating point efficiently and accurately with the help of MPPT technology to maximize the collected power. Even though a lot of research has been carried out and impressive progress achieved for MPPT technology, it still faces some challenges and dilemmas. Firstly, the mathematical model established for PV cells is not precise enough. Second, the existing… More > Graphic Abstract

Huaxing Zhao¹, Yanbo Che^1,*, Gang Wen², Yijing Chen³

Energy Engineering, Vol.121, No.3, pp. 643-660, 2024, DOI:10.32604/ee.2023.045204

Abstract Long-term use in challenging natural conditions is possible for photovoltaic modules, which are extremely prone to failure. Failure to diagnose and address faults in Photovoltaic (PV) power systems in a timely manner can cause permanent damage to PV modules and, in more serious cases, fires. Therefore, research into photovoltaic module defect detection techniques is crucial for the growth of the photovoltaic sector as well as for maintaining national economic prosperity and ensuring public safety. Considering the drawbacks of the current real-time and historical data-based methods for monitoring distributed PV systems, this paper proposes a method… More >

Gaber Magdy^1,2,*, Mostafa Metwally³, Adel A. Elbaset^3,4, Esam Zaki⁵

Energy Engineering, Vol.121, No.1, pp. 13-26, 2024, DOI:10.32604/ee.2023.043562

Abstract The generation of photovoltaic (PV) solar energy is increasing continuously because it is renewable, unlimited, and clean energy. In the past, generation systems depended on non-renewable sources such as oil, coal, and gas. Therefore, this paper assesses the performance of a 51 kW PV solar power plant connected to a low-voltage grid to feed an administrative building in the 6th of October City, Egypt. The performance analysis of the considered grid-connected PV system is carried out using power system simulator for Engineering (PSS/E) software. Where the PSS/E program, monitors and uses the power analyzer that… More >

B. Jegajothi^1,*, Sundaram Arumugam², Neeraj Kumar Shukla³, I. Kathir⁴, P. Yamunaa⁵, Monia Digra⁶

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2417-2437, 2023, DOI:10.32604/csse.2023.038074

Abstract Renewable energy sources like solar, wind, and hydro are becoming increasingly popular due to the fewer negative impacts they have on the environment. Because, Since the production of renewable energy sources is still in the process of being created, photovoltaic (PV) systems are commonly utilized for installation situations that are acceptable, clean, and simple. This study presents an adaptive artificial intelligence approach that can be used for maximum power point tracking (MPPT) in solar systems with the help of an embedded controller. The adaptive method incorporates both the Whale Optimization Algorithm (WOA) and the Artificial… More >

Nur Fairuz Mohamed Yusof¹, Dahaman Ishak², Muhammad Ammirrul Atiqi Mohd Zainuri^3,*, Muhammad Najwan Hamidi², Zuhair Muhammed Alaas⁴, Mohamed Mostafa Ramadan Ahmed⁵

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2441-2457, 2023, DOI:10.32604/iasc.2023.037778

Abstract Grid-connected reactive-load compensation and harmonic control are becoming a central topic as photovoltaic (PV) grid-connected systems diversified. This research aims to produce a high-performance inverter with a fast dynamic response for accurate reference tracking and a low total harmonic distortion (THD) even under nonlinear load applications by improving its control scheme. The proposed system is expected to operate in both stand-alone mode and grid-connected mode. In stand-alone mode, the proposed controller supplies power to critical loads, alternatively during grid-connected mode provide excess energy to the utility. A modified variable step incremental conductance (VS-InCond) algorithm is… More >

J. Aran Glenn^1,*, Srinivasan Alavandar²

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1523-1545, 2023, DOI:10.32604/iasc.2023.033545

Abstract Nowadays, researchers are becoming increasingly concerned about developing a highly efficient emission free transportation and energy generation system for addressing the pressing issue of environmental crisis in the form of pollution and climate change. The introduction of Electric Vehicles (EVs) solves the challenge of emission-free transportation while the necessity for decarbonized energy production is fulfilled by the installation and expansion of solar-powered Photovoltaic (PV) systems. Hence, this paper focuses on designing an effective PV based EV charging system that aids in stepping towards the achievement of a pollution free future. For overcoming the inherent intermittency… More >

Xing Deng^1,2, Feipeng Da^1,*, Haijian Shao², Xia Wang³

Energy Engineering, Vol.120, No.2, pp. 385-408, 2023, DOI:10.32604/ee.2023.023480

Abstract Photovoltaic power generating is one of the primary methods of utilizing solar energy resources, with large-scale photovoltaic grid-connected power generation being the most efficient way to fully utilize solar energy. In order to provide reference strategies for pertinent researchers as well as potential implementation, this paper tries to provide a survey investigation and technical analysis of machine learning-related approaches, statistical approaches and optimization techniques for solar power generation and forecasting. Deep learning-related methods, in particular, can theoretically handle arbitrary nonlinear transformations through proper model structural design, such as hidden layer topology optimization and objective function More > Graphic Abstract

Anis Ammous^*, Ammar Alsaedi, Ahmed N. M. Alahmadi, Fahad Alharbi, Kaiçar Ammous

Computer Systems Science and Engineering, Vol.45, No.2, pp. 2171-2186, 2023, DOI:10.32604/csse.2023.029389

Abstract The Low Voltage Direct Current (LVDC) architecture gives higher benefits over the classic low-voltage alternating current (LVAC) supply concept. LVDC has fewer energy conversion stages, is compatible with renewable energy sources, and is easier to integrate with accumulators. In this paper, an LVDC supply concept is proposed and compared with currently used conventional photovoltaic (PV) systems in terms of efficiency. The new LVDC photovoltaic system behavior is validated using LTspice modeling tool. The findings of this work prove that the concept of LVDC supply is highly attractive when the electricity produced by the photovoltaic is… More >

R. K. Negesh^1,*, S. Karthikeyan²

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1151-1172, 2023, DOI:10.32604/iasc.2023.027764

Abstract In the recent era, the significance of Renewable Energy (RE) sources in the process of power generation has attained considerable attention as it provides multiple beneficial impacts without harming the environment. The Photovoltaic (PV) and Doubly-Fed Induction Generator (DFIG) fed wind turbine are employed as hybrid power sources in this study. The output voltages of these sources are independently controlled by separate controllers in an optimal manner for effectively maximizing the overall performance of the system. The Reboost Luo converter is introduced in this work to maximize the output voltage of PV in an efficient… More >