Article

Researchers from the University of Pretoria in South Africa conducted a study to optimize commercial and industrial PV systems with compressed air energy storage (CAES) to minimize investment and operational costs while improving reliability. The study developed a multi-objective optimization framework for real-time sizing of PV and CAES components.

A simulated hybrid microgrid included a PV array, adiabatic CAES, and a backup diesel generator, tested under various conditions. The model indicated that a co-optimized PV-CAES system could reduce capital costs by 15-20% compared to traditional methods.

High-performance configurations achieved up to 41.5% renewable penetration with $13.57 million investment, while cost-constrained setups reduced costs to $9.2 million with lower reliability. Future research will focus on AI-driven energy management for real-time CAES operation.