Artificial intelligence study shows reduced grid import in hybrid power simulation

Bioengineer.org reported that a simulation study demonstrated how an artificial intelligence augmented hybrid solar, wind, and battery system can reduce grid import by 14.8 percent. The study also showed a 9.5 percent reduction in the levelized cost of energy while maintaining IEEE-519 power quality standards. The research was published in the journal Discover Energy. [1]

According to Bioengineer.org, the study presented a co-designed architecture where artificial intelligence algorithms manage energy dispatch while deterministic control loops maintain power quality. The central contribution of the research is a time-scale-separated architecture that couples an offline optimizer, a forecasting network, and a reinforcement learning dispatcher directly to device-level control loops. [1]

Simulations use models to represent the key characteristics, evolution, or behaviors of a real-world process or system over time. Computer programs are often used to execute these simulations to conduct experimentation. [4]

Bioengineer.org reported that the integration of the artificial intelligence dispatch system and deterministic control loops aims to enhance power quality and reduce grid dependence. The design also preserves grid-code compliance even in the event of an artificial intelligence failure. [1]