Automatic Load Frequency Control for Wind-Thermal Micro Grid Based on Deep Reinforcement Learning

International Journal of Electrical and Electronics Engineering
© 2021 by SSRG - IJEEE Journal
Volume 8 Issue 8
Year of Publication : 2021
Authors : E. G. Swetala, P. Sujatha, P. Bharath
How to Cite?

E. G. Swetala, P. Sujatha, P. Bharath, "Automatic Load Frequency Control for Wind-Thermal Micro Grid Based on Deep Reinforcement Learning," SSRG International Journal of Electrical and Electronics Engineering, vol. 8,  no. 8, pp. 1-8, 2021. Crossref,


Renewable energy demand keeps increasing each day due its significances over the conventional sources of energy, particularly in this era where the world is faced with many challenges related to clean energy. Among Renewable Energy Resources (RERs), wind energy has proven to be cheaper and readily available. However, it is intermittent in nature and therefore affecting the voltage and frequency stability of microgrid systems, especially in occurrence of wind power ramping events. In this work, a simple Deep Reinforcement based Automatic Load Frequency Controller (DRL-ALFC) is designed so as to improve the frequency stability of an ALFC during wind power ramping events in a wind-thermal micro grid. A DRL-ALFC for wind-thermal microgrid is verified in MATLAB/Simulink environment where it shows the ability to adapt to the variations wind power fluctuation and load.


Automatic load frequency controller, Deep Reinforcement based Automatic Load Frequency Controller (DRL-ALFC), Renewable energy resources (RERs), Wind-Thermal microgrid.


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