This code is for a graduation project, then transformed into 3 papers presented at ICCCEEE20 available at IEEEXPLORE relating to the managment and control of a trading game between islanded microgrids with different deep reinforcement learning techniques run on a custom environment.
The paper presents an algorithm that acts as a trading controller for islanded microgrids, applied to data from Sudanese villages. The paper uses two Deep Reinforcement Learning algorithms, DDPG and PPO on the environment designed by the researchers. DOI for the 3 papers are:
Enhancing Energy Trading Between Different Islanded Microgrids A Reinforcement Learning Algorithm Case Study in Northern Kordofan State: 10.1109/ICCCEEE49695.2021.9429584
Comparison of Deep Reinforcement Learning Algorithms in Enhancing Energy Trading in Microgrids: 10.1109/ICCCEEE49695.2021.9429565
An Economic Evaluation of Islanded Microgrids Implementation in Northern Kordofan State: 10.1109/ICCCEEE49695.2021.9429680