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Rapid urbanization has escalated energy demand, pushing governments to prioritize achieving Net Zero Energy consumption through Hybrid Energy Systems (HES) that consists of Renewable Energy Sources, Energy Storage Devices, and conventional grid. An essential algorithm is needed to determine optimal RES capacities and ensure system reliability while achieving NZE and efficiently planning HES for specific loads. This study utilizes the Hybridized Crow Search and Particle Swarm Optimization (HCSAPSO) algorithm to ensure optimal HES capacity for an Educational Campus in India. It considers constraints such as Loss of Power Supply Probability (LPSP) and NZE indices like Load Match Index and Load coverage factor. Outperforming other techniques, HCSAPSO underscores the significance of reliable and cost-effective solutions for optimal sizing by achieving a minimum Net Annualized Invest cost (NAIC) of 8621 USD with the best reliability index (LPSPmax) of 0.1 and 36,621 USD with worst LPSPmax of 0.5 for a maximum demand of 1.673 MWh.

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Optimal Sizing of Reliable HES to Facilitate Net Zero Consumption for an Educational Campus

  • 会议论文

  • 发表日期：

    2026年

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  • Tanima Bal,
  • Anagha Bhattacharya

摘要

Rapid urbanization has escalated energy demand, pushing governments to prioritize achieving Net Zero Energy consumption through Hybrid Energy Systems (HES) that consists of Renewable Energy Sources, Energy Storage Devices, and conventional grid. An essential algorithm is needed to determine optimal RES capacities and ensure system reliability while achieving NZE and efficiently planning HES for specific loads. This study utilizes the Hybridized Crow Search and Particle Swarm Optimization (HCSAPSO) algorithm to ensure optimal HES capacity for an Educational Campus in India. It considers constraints such as Loss of Power Supply Probability (LPSP) and NZE indices like Load Match Index and Load coverage factor. Outperforming other techniques, HCSAPSO underscores the significance of reliable and cost-effective solutions for optimal sizing by achieving a minimum Net Annualized Invest cost (NAIC) of 8621 USD with the best reliability index (LPSPmax) of 0.1 and 36,621 USD with worst LPSPmax of 0.5 for a maximum demand of 1.673 MWh.