Open AccessPower Quality Enhancement in Microgrid With Dstatcom Using Modified Reinforcement Learning Algorithm
Author(s) -
K Prabaakaran,
Sri Krishnakumar,
R Srividhya,
R Ganesh Raw,
R Gotham,
R. Tamilarasan
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1362/1/012080
Subject(s) - reinforcement learning , microgrid , harmonics , voltage sag , computer science , swell , voltage , controller (irrigation) , grid , control theory (sociology) , reinforcement , ac power , power (physics) , power quality , algorithm , engineering , artificial intelligence , electrical engineering , control (management) , mathematics , agronomy , oceanography , physics , geometry , structural engineering , quantum mechanics , geology , biology
To enhance the power quality issue in grid system a new strategy with modification in algorithm is presented as reinforcement learning. A new technique will mitigate issues like reactive power, harmonics, voltage sag, voltage swell. A system as a current controller to enhance the current issue and the voltage controller to enhance the power quality issues in voltage. Due to an issue of unbalanced load in the grid the weak AC supply can be compensated by using the modified reinforcement learning algorithm. During the occurrence of the power quality issue in the grid modified reinforcement learning algorithm is proposed due to quick response.