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 Neural Network (ANN). The WOA… 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 designed to extract maximum power… 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 associated with PV, a novel… 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 analysis to save information that… 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 used onsite in the daytime.… 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 manner whereas the Grey Wolf… More >

C. K. Morarji^1,*, N. Sathish Kumar²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2875-2892, 2023, DOI:10.32604/iasc.2023.025776

Abstract One of the recent advancements in the electrical power systems is the smart-grid technology. For the effective functioning of the smart grid, the process like monitoring and controlling have to be given importance. In this paper, the Wireless Sensor Network (WSN) is utilized for tracking the power in smart grid applications. The smart grid is used to produce the electricity and it is connected with the sensor to transmit or receive the data. The data is transmitted quickly by using the Probabilistic Neural Network (PNN), which aids in identifying the shortest path of the nodes. While transmitting the data from… More >

Thamatapu Eswara Rao^*, S. Elango

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1783-1798, 2023, DOI:10.32604/iasc.2023.028835

Abstract Global energy demand is growing rapidly owing to industrial growth and urbanization. Alternative energy sources are driven by limited reserves and rapid depletion of conventional energy sources (e.g., fossil fuels).Solar photovoltaic (PV), as a source of electricity, has grown in popularity over the last few decades because of their clean, noise-free, low-maintenance, and abundant availability of solar energy. There are two types of maximum power point tracking (MPPT) techniques: classical and evolutionary algorithm-based techniques. Precise and less complex perturb and observe (P&O) and incremental conductance (INC) approaches are extensively employed among classical techniques. This study used a field-programmable gate array… More >

N. Rajeswari^1,*, S. Venkatanarayanan²

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1311-1322, 2023, DOI:10.32604/iasc.2023.028552

Abstract Due to the enormous utilization of solar energy, the photovoltaic (PV) system is used. The PV system is functioned based on a maximum power point (MPP). Due to the climatic change, the Partial shading conditions have occurred under non-uniform irradiance conditions. In the PV system, the global maximum power point (GMPP) is complex to track in the P-V curve due to the Partial shading. Therefore, several tracking processes are performed using various methods like perturb and observe (P & O), hill climbing (HC), incremental conductance (INC), Fuzzy Logic, Whale Optimization Algorithm (WOA), Grey Wolf Optimization (GWO) and Flying Squirrel Search… More >

E. Jessy Mol^*, M. Mary Linda

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1471-1489, 2023, DOI:10.32604/iasc.2023.024027

Abstract The prominence of Renewable Energy Sources (RES) in the process of power generation is exponentially increased in the recent days since these sources assist in minimizing the environmental contamination. A grid-tied DFIG (Doubly Fed Induction Generator) based WECS (Wind Energy Conversion System) is introduced in this work, in which a Landsman converter is implemented to improvise the output voltage of PV without any fluctuations. A novel GA (Genetic Algorithm) assisted ANN (Artificial Neural Network) is employed for tracking the Maximum power from PV. Among the rotor and grid side controllers, the former is implemented by combining the stator flux with… More >