Scholarlink

<p>This study develops a resilience-oriented optimization framework for hospital microgrids that integrates photovoltaic (PV) generation, multi-node battery energy storage systems (BESS), and medical load prioritization under grid outage conditions. A mixed-integer linear programming (MILP) model is formulated to jointly optimize ESS scheduling, critical-load support, and renewable utilization across a set of Monte Carlo outage scenarios. The framework introduces a multi-tier hospital load hierarchy (ICU, OR, imaging, pharmacy) based on Value of Lost Load (VOLL), and employs a composite resilience index combining ENS, LOLP, and critical-load survivability. The model is evaluated on modified IEEE 13-, 33-, and 69-bus systems. Results show that coordinated multi-node ESS placement improves resilience significantly, reducing Energy Not Supplied (ENS) by 55–63% compared with baseline configurations, while maintaining ≥ 95% supply to life-critical loads across most stochastic outage realizations. The proposed strategy also ensures stable Resilience Index (RI) values with a variance below 10%, highlighting robustness against PV variability and outage timing uncertainty. Sensitivity analysis demonstrates that ESS capacity, PV penetration, and outage duration are the dominant factors influencing resilience. Overall, the framework provides a practical and quantitatively validated tool for hospital energy planners seeking enhanced survivability and operational security during grid disruptions.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Resilience-oriented optimization of hospital microgrids with critical load support using ESS and PV under grid outage conditions

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月29日

查看全文
  • Pourya Nazartalab,
  • Hosein Alavi-Rad

摘要

This study develops a resilience-oriented optimization framework for hospital microgrids that integrates photovoltaic (PV) generation, multi-node battery energy storage systems (BESS), and medical load prioritization under grid outage conditions. A mixed-integer linear programming (MILP) model is formulated to jointly optimize ESS scheduling, critical-load support, and renewable utilization across a set of Monte Carlo outage scenarios. The framework introduces a multi-tier hospital load hierarchy (ICU, OR, imaging, pharmacy) based on Value of Lost Load (VOLL), and employs a composite resilience index combining ENS, LOLP, and critical-load survivability. The model is evaluated on modified IEEE 13-, 33-, and 69-bus systems. Results show that coordinated multi-node ESS placement improves resilience significantly, reducing Energy Not Supplied (ENS) by 55–63% compared with baseline configurations, while maintaining ≥ 95% supply to life-critical loads across most stochastic outage realizations. The proposed strategy also ensures stable Resilience Index (RI) values with a variance below 10%, highlighting robustness against PV variability and outage timing uncertainty. Sensitivity analysis demonstrates that ESS capacity, PV penetration, and outage duration are the dominant factors influencing resilience. Overall, the framework provides a practical and quantitatively validated tool for hospital energy planners seeking enhanced survivability and operational security during grid disruptions.