Enhancing Energy Trading Between Different Islanded Microgrids

Published in 2020 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE), 2021

Recommended citation: Moayad ELamin, Fay Elhassan, Mahmoud A Manzoul. (2021). "Enhancing Energy Trading Between Different Islanded Microgrids." 2020 ICCCEEE. Pages 1-6. Publisher: IEEE. [https://ieeexplore.ieee.org/abstract/document/9429584]

This paper tackles the problem of rural electrification and the lack of grid connection to large areas of Sudan. It introduces microgrids as an alternative to conventional centralized generation as they provide stability in electricity supply in addition to the environmental benefits accompanied with using renewable energy sources. A new method is introduced to facilitate the fluctuation in energy production when using renewable sources by creating a Reinforcement Learning algorithm to conduct the process of energy trading between different islanded microgrids. The goal of the trading process is to achieve stability and generation-load balance in the microgrids. The paper also presents a case study of three villages in North Kordufan State; Hamza Elsheikh, Tannah and Um-Bader. The study uses real solar irradiance and wind speed data to create a MATLAB simulation for a fully functional microgrid. Download paper here