Equity Based Energy Distribution Strategies under Extreme Heat Conditions

Abstract

Extreme heat conditions, exacerbated by climate change, create profound challenges for energy systems by simultaneously driving massive spikes in electricity demand for cooling and constraining supply through thermal derating of transmission lines, reduced generation efficiency, and increased outage risks. Traditional energy distribution strategies prioritize technical efficiency or economic cost minimization, often resulting in disproportionate burdens on socioeconomically vulnerable populations who suffer amplified health impacts when cooling systems fail during prolonged outages. Equity-based energy distribution strategies explicitly incorporate social vulnerability metrics into decision-making processes to ensure fair allocation of limited energy resources during heatwaves. This research paper develops a comprehensive framework for equity based energy distribution that integrates social vulnerability indices (SVI), vulnerability-weighted value of lost load, and grid-adapted Gini coefficients into multi-objective optimization models for load management and distribution under extreme heat. Using mixed-integer linear programming and distributionally robust optimization, the framework co-optimizes generation dispatch, dynamic line ratings (DLR), demand response, and controlled load curtailment while minimizing disparities in outage exposure across demographic groups. Predictive analytics and reinforcement learning enhance real-time adaptability to evolving temperature and load conditions. Case studies demonstrate that equity-based approaches can reduce vulnerability-weighted impacts by 25–50% compared to traditional methods, with only modest trade-offs in total operational costs or unserved energy. As heatwaves intensify, equity-based energy distribution emerges as a critical requirement for just and resilient power systems that protect the most vulnerable communities without compromising overall system stability.