Wind-Driven Scheduling of Compressed Air and Latent Heat Storage for Optimal Gas Turbines Operation

There has been an insatiable trend focusing on the use of Compressed Air Energy Storage (CAES) in electric power systems. The ever-increasing attempts to exploit the benefits of CAES were strongly encouraged by the versatility of combinations in which CAES can be implemented. The intent of this paper is to present a Mixed-Integer Non-Linear Programming (MINLP) mathematical model that demonstrates the potential benefits of combining adiabatic CAES, Phase Change Materials (PCM) heat storage and renewable wind energy for electrical power production in a gas turbine. The mathematical model aims at minimizing fuel consumption and reducing renewable energy curtailment by providing optimal decisions for charging and discharging the CAES and Latent Heat Storage (LHS) systems, while meeting a variety of technical constraints. The proposed model could be developed in future research to serve as a planning tool in electrical power systems.