2025 Theses Master's

Optimizing Urban Microgrid Deployment for Critical Infrastructure: A Social Value–Driven Approach to Government Subsidy and Green Finance

Zhang, Hanyin

This study develops a planning framework for urban microgrids that integrates resilience, equity, and participatory governance to address climate-induced disruptions and structural inequities in traditional energy systems.

A Critical Load Index (CLI) model is introduced to prioritize infrastructure based on functional importance, energy demand, social vulnerability (SVI), and recovery capacity. Empirical analysis in Shenzhen identifies data centers and hospitals as resilience-critical nodes due to their high Value of Lost Load (VoLL, $20,000–50,000/MWh) and service sensitivity.

Building on CLI outputs, a Social Value-Based Subsidy Optimization Model (SV-SOM) is proposed to overcome limitations of conventional CAPEX-based subsidies. By incorporating co-benefits such as carbon mitigation ($10.03 million/year), public health gains ($42.4 million/year), and job creation ($15.43 million/year), the model enables dynamic and equitable subsidy allocation. Over a 20-year horizon, it demonstrates a Social Return on Investment (SROI) of 8.97:1, supporting green bonds and carbon-linked financial tools.

The study also proposes a tiered subsidy and community co-governance mechanism. High-priority facilities receive upfront capital support and access to carbon revenue, while pilot community equity models in high-vulnerability areas allocate 30% of project revenues to a Health Protection Fund, reinforcing local investment and energy democratization. By bridging technical resilience with social equity, this research advances a data-driven, value-based framework for China’s evolving power system and offers transferable strategies for global sustainable energy transitions.

Keywords: Microgrid Planning; Urban Resilience; Critical Load Identification (CLI); Social Value Optimization; Green Finance; Energy Equity; Social Return on Investment (SROI)