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The development of microgrids (MGs) has attracted significant interest in the integration of renewable energy sources (RES) into the national grid. MGs offers a promising solution to enhance energy reliability and optimize energy consumption through the incorporation of distributed energy resources (DERs) such as solar photovoltaics (PV), wind turbines (WT), and energy storage systems (ESS). Among ESS, battery sizing plays a pivotal role in ensuring the stability and efficiency of MGs. Accurate battery sizing is crucial for the efficient operation and reliability of MGs. An undersized battery can lead to poor reliability in MG operations while an oversized battery can result in high capital and operating costs. This study presents a verification analysis using Two-Way Analysis of Variance (Two-Way ANOVA) to evaluate the effects of initial battery conditions and battery capacity on the operating cost of MGs, utilizing the Manta Ray Foraging Optimization (MRFO) algorithm. The statistical inference results demonstrate that the interaction between battery capacity and initial battery conditions significantly impacts the operating cost of the MG system.

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Verification of Battery Initial Conditions for Battery Sizing in Microgrids Using Two-Way ANOVA and MRFO

  • 会议论文

  • 发表日期：

    2025年

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  • Yazhar Yatim,
  • M. F. N. Tajuddin,
  • Shahril Irwan Sulaiman,
  • Azralmukmin Azmi,
  • Maz Jamilah Masnan

摘要

The development of microgrids (MGs) has attracted significant interest in the integration of renewable energy sources (RES) into the national grid. MGs offers a promising solution to enhance energy reliability and optimize energy consumption through the incorporation of distributed energy resources (DERs) such as solar photovoltaics (PV), wind turbines (WT), and energy storage systems (ESS). Among ESS, battery sizing plays a pivotal role in ensuring the stability and efficiency of MGs. Accurate battery sizing is crucial for the efficient operation and reliability of MGs. An undersized battery can lead to poor reliability in MG operations while an oversized battery can result in high capital and operating costs. This study presents a verification analysis using Two-Way Analysis of Variance (Two-Way ANOVA) to evaluate the effects of initial battery conditions and battery capacity on the operating cost of MGs, utilizing the Manta Ray Foraging Optimization (MRFO) algorithm. The statistical inference results demonstrate that the interaction between battery capacity and initial battery conditions significantly impacts the operating cost of the MG system.