A Smart Microgrid Platform Integrating AI and Deep Reinforcement
DRL is a transformative AI approach that combines neural networks and reinforcement learning to enable intelligent decision making in complex, dynamic environments. Within SMGs, DRL
DRL is a transformative AI approach that combines neural networks and reinforcement learning to enable intelligent decision making in complex, dynamic environments. Within SMGs, DRL
This study proposes an energy management platform based on an intelligent probabilistic wavelet petri neuro-fuzzy inference algorithm (IPWPNFIA) to control the V/F index in the presence of
The experimental setup and results are based on the rapid control prototyping of the micro-grid platform, MATLAB/Simulink and RT-LAB software, and hardware infrastructure such as the OPAL-RT
It then studies the microgrid system design and develops a complete physical test platform for microgrids, which includes a battery bank, a load pack, an inverter, and a power meter.
Microgrid (MG) concept is becoming increasingly mature. It allows integrating better distributed generation, and especially renewable energy sources, in the grid. However, many issues
The Smart Microgrid and Renewable Technology (SMRT) lab is a power converter based microgrid testbed. The facility consists of four types of subsystems, i.e., two real-time simulators (RTS), two
The Intelligent Grid Experimental Facilities at IERC – Tyndall offer a virtual living lab for low-voltage microgrid research, integrating detailed modelling, real-time simulation, and hardware testing.
The platform serves as a foundation for next-generation microgrid control systems that demand real-time intelligence, scalability, and reliability across evolving smart grid landscapes.
This paper presents the ''Picogrid'' - an experimental platform particularly designed for dc prosumer microgrids. It is a low-power, low-cost hardware platform that enables interconnecting multiple
In this article, we focus on a real-world microgrid in Singapore and develop a cognitive DT. Our DT consists of a client, located near the physical microgrid for real-time control, and a cloud
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