Smart Grid Optimization for Managing Peak Loads during Heatwave Events

Abstract

Heatwave events, intensified by climate change, create acute challenges for power systems by driving unprecedented electricity demand spikes from air conditioning often increasing peaks by 30–50% or more while simultaneously degrading infrastructure performance through elevated conductor temperatures, increased line losses, reduced generation efficiency, and derated transmission capacity. Smart grid technologies, including advanced metering infrastructure, distributed energy resource management systems, dynamic line ratings, demand response, virtual power plants, and energy storage systems, enable sophisticated optimization strategies to manage these peaks effectively. This research paper presents a comprehensive smart grid optimization framework for heatwave peak load management. The framework co-optimizes centralized generation, transmission flows (with DLR unlocking 10–40%+ additional capacity under favorable conditions), behind-the-meter flexibility from VPPs and DR, and battery storage for peak shaving and arbitrage. Multi-objective extensions balance operational costs, reliability (minimizing unserved energy or CVaR of risk), emissions, and equity (vulnerability-weighted curtailment using social vulnerability indices). Predictive analytics, including LSTM/TCN for DLR and load forecasting, and reinforcement learning for adaptive control, enhance decision making under uncertainty.