Salman Muhammad, Kashif Syed Abdul Rahman, Fakhar Muhammad Salman, Rasool Akhtar, Hussen Abdulkerim Sherefa
Department of Electrical Engineering, University of Engineering and Technology, Lahore, Lahore, 54890, Pakistan.
Department of Electrical Engineering, University of Botswana, Gaborone, UB0061, Botswana.
Sci Rep. 2025 Mar 27;15(1):10550. doi: 10.1038/s41598-025-95248-8.
The rising demand for renewable energy has recently spurred notable advancements in hybrid energy systems that utilize solar and wind power. The Hybrid Solar Wind Energy System (HSWES) integrates wind turbines with solar energy systems. This research project aims to develop effective modeling and control techniques for a grid-connected HSWES. The goal is to optimize power tracking efficiency in an electrically linked solar photovoltaic system combined with a wind-powered Doubly Fed Induction Generator (DFIG). The back-to-back ([Formula: see text]) converters' DC link is connected to this to integrate the solar photovoltaic (PV). The study controls the rotor and grid converters via a vector control technique. This study aims to optimize power extraction efficiency and hybrid system integration with electrical grids by applying the Maximum Power Point Tracking (MPPT) technique to solar and wind systems. Combining the control strategy with the optimization algorithm makes our work new and compelling. We utilized this technology with a focus on optimization to evaluate how our system performs when applying optimization techniques to the control strategies. We optimized the solar system using the conventional Perturb and Observe (P & O) method and the metaheuristic Particle Swarm Optimization (PSO) technique. Our primary objective was to validate the effectiveness of the optimization process in enhancing the control strategy. The paper investigates the applications of Particle Swarm Optimization (PSO) and Perturb and Observe (P & O) algorithms in solar photovoltaics under constant and real-time sunlight. The hybrid Indirect Speed Controller MPPT algorithms are utilized for step-up and step-down wind speeds. An HSWES simulation is used to confirm the effectiveness and efficiency of the recommended regulation technique. The suggested control approach is simulated using the Sim Power of the MATLAB/Simulink platform. The advantage of the established techniques lies in their capacity to swiftly and precisely monitor the ideal power output of the HSWES. The comprehensive simulations conducted provide compelling evidence for the efficacy of the proposed system in attaining optimal efficiency and stability, propelling the progress of sustainable energy solutions.
对可再生能源日益增长的需求最近推动了利用太阳能和风能的混合能源系统取得显著进展。混合太阳能风能系统（HSWES）将风力涡轮机与太阳能系统集成在一起。本研究项目旨在为并网HSWES开发有效的建模和控制技术。目标是在与风力双馈感应发电机（DFIG）相结合的电连接太阳能光伏系统中优化功率跟踪效率。背靠背（[公式：见原文]）变流器的直流链路连接到此处以集成太阳能光伏（PV）。该研究通过矢量控制技术控制转子和电网变流器。本研究旨在通过将最大功率点跟踪（MPPT）技术应用于太阳能和风能系统来优化功率提取效率以及混合系统与电网的集成。将控制策略与优化算法相结合使我们的工作新颖且引人注目。我们利用这项技术专注于优化，以评估在将优化技术应用于控制策略时我们的系统性能如何。我们使用传统的扰动观察（P&O）方法和元启发式粒子群优化（PSO）技术对太阳能系统进行了优化。我们的主要目标是验证优化过程在增强控制策略方面的有效性。本文研究了粒子群优化（PSO）和扰动观察（P&O）算法在恒定和实时阳光条件下在太阳能光伏中的应用。混合间接速度控制器MPPT算法用于风速的升压和降压。使用HSWES仿真来确认推荐调节技术的有效性和效率。使用MATLAB/Simulink平台的Sim Power对建议的控制方法进行仿真。既定技术的优势在于它们能够快速且精确地监测HSWES的理想功率输出。所进行的全面仿真为所提出系统在实现最佳效率和稳定性方面的有效性提供了有力证据，推动了可持续能源解决方案的发展。
