Researchers developed a new method to model microgrids using Hybrid Petri Net (HPN), allowing for efficient operation under various conditions. This analysis helps engineers estimate time and cost required for grid component switching, enabling improved microgrid design.
Researchers used fractional calculus to model crowds as cost-minimizing agents who interact cooperatively or competitively, leading to realistic simulations of emergency exit scenarios and real-world data comparisons.
Researchers at Northeastern University have proposed a way to optimize power exchange between the main grid and multiple microgrids using consensus-based algorithms. These algorithms allow decentralized generators to communicate with each other and with the main grid, ensuring reliable and cost-effective energy distribution.
Researchers create a closed-loop system to test their proposed method, which is a better fit for how humans actually behave compared to traditional models. The new model uses fractional order calculus to describe human operator behavior, providing a unified and formalized description.
Researchers developed a fractional order model to estimate Lithium-ion battery charge, reducing errors of up to 1% compared to traditional methods. The model replicated the battery's performance and provided accurate results, promising to reduce drivers' anxiety on the road.
The world is shifting towards Intelligent Technology, rethinking core principles of automation and Al to navigate an IT paradigm. The fifth era introduces a new control framework, bridging physical, mental, and augmented realities.
AlphaGo, a computer program, defeated an 18-time world champion of Go by integrating data-driven AI approaches and recognizing game patterns
A recent study demonstrates the potential of deep reinforcement learning in optimizing traffic signal timing, reducing average delay by 14% and vehicle waiting time by 13 seconds.