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<p>An eco-friendly and sustainable substitute for conventional power systems is the generation of electricity from Renewable Energy Sources (RES), such as Solar Photovoltaic (SPV) and Wind Energy Sources (WES). Due to the exhaustion of conventional energy sources and their detrimental environmental effects, renewable energy sources are becoming increasingly vital for a dependable electricity supply. Nonetheless, elements such as thunderstorms, system malfunctions, and the difficulties of supplying electricity to remote or mountainous regions require resilient solutions. Hybrid Energy Systems (HES), which amalgamate several energy sources, have arisen as a feasible solution to guarantee a continuous and dependable power supply. This study centres on the development of a hybrid energy system incorporating solar photovoltaic, wind energy systems, and diesel power sources utilising MATLAB/Simulink. A diesel generator is integrated into the solar-wind system to furnish backup power, hence augmenting reliability. The research assesses the viability and reliability of the proposed system for a 50&#xa0;kW load indicative of a small settlement. Optimisation is a vital component of this research, focused on enhancing system performance and stability. The Artificial Bee Colony Optimisation (ABCO) method is utilised to optimise the parameters of the Proportional-Integral (PI) controller for the SPV system. Following optimisation, the SPV system is amalgamated with the wind and diesel components to create a holistic HES. The findings indicate that the optimised HES efficiently satisfies load requirements, delivering a consistent and high-performance energy supply. This study emphasises the promise of hybrid renewable systems in tackling energy issues and promoting sustainable development, especially in isolated and disadvantaged areas. The current research utilizes the Artificial Bee Colony (ABC) algorithm to enhance the efficiency of hybrid energy systems that incorporate both renewable and traditional energy sources. The aim is to optimize energy efficiency, improve reliability, and decrease operational expenses amid fluctuating renewable generation. The results indicate that ABC significantly enhances system performance, exhibiting superior efficiency and consistent power output relative to traditional techniques. The research underscores the practical significance of ABC optimization for the deployment of scalable and sustainable hybrid energy systems.</p>

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Enhancing the performance of hybrid energy system through artificial bee colony optimization

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月13日

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  • Hemant Sharma,
  • Abinash Singh,
  • Mohit Yadav,
  • Khushwant Singh,
  • Keshav Kaushik,
  • Renu Kumawat

摘要

An eco-friendly and sustainable substitute for conventional power systems is the generation of electricity from Renewable Energy Sources (RES), such as Solar Photovoltaic (SPV) and Wind Energy Sources (WES). Due to the exhaustion of conventional energy sources and their detrimental environmental effects, renewable energy sources are becoming increasingly vital for a dependable electricity supply. Nonetheless, elements such as thunderstorms, system malfunctions, and the difficulties of supplying electricity to remote or mountainous regions require resilient solutions. Hybrid Energy Systems (HES), which amalgamate several energy sources, have arisen as a feasible solution to guarantee a continuous and dependable power supply. This study centres on the development of a hybrid energy system incorporating solar photovoltaic, wind energy systems, and diesel power sources utilising MATLAB/Simulink. A diesel generator is integrated into the solar-wind system to furnish backup power, hence augmenting reliability. The research assesses the viability and reliability of the proposed system for a 50 kW load indicative of a small settlement. Optimisation is a vital component of this research, focused on enhancing system performance and stability. The Artificial Bee Colony Optimisation (ABCO) method is utilised to optimise the parameters of the Proportional-Integral (PI) controller for the SPV system. Following optimisation, the SPV system is amalgamated with the wind and diesel components to create a holistic HES. The findings indicate that the optimised HES efficiently satisfies load requirements, delivering a consistent and high-performance energy supply. This study emphasises the promise of hybrid renewable systems in tackling energy issues and promoting sustainable development, especially in isolated and disadvantaged areas. The current research utilizes the Artificial Bee Colony (ABC) algorithm to enhance the efficiency of hybrid energy systems that incorporate both renewable and traditional energy sources. The aim is to optimize energy efficiency, improve reliability, and decrease operational expenses amid fluctuating renewable generation. The results indicate that ABC significantly enhances system performance, exhibiting superior efficiency and consistent power output relative to traditional techniques. The research underscores the practical significance of ABC optimization for the deployment of scalable and sustainable hybrid energy systems.