MOGOA Based RLNN Controller for LFC of Three Area Deregulated HDG Power System

Conference Paper

This paper presents the multi-objective grasshopper optimization algorithm (MOGOA) based reinforced learning neural network controller (RLNN) controllers in the load frequency control (LFC) problems for three area deregulated hybrid distributed generation (HDG) power system. The controller parameters and gains are optimized by MOGOA and its performance is compared with PID controllers. Sensitivity analyses are performed to investigate robustness of the considered MOGOA-RLNN controllers expose to change of inertia constant and loading conditions and also analysis exposes that MOGOA-RLNN controllers is superior performances than PID controllers.

Full Text

Duke Authors

Cited Authors

  • Das, MK; Bera, P; Sarkar, PP; Chakrabarty, K

Published Date

  • September 24, 2021

Published In

  • 2021 Ieee 4th International Conference on Computing, Power and Communication Technologies, Gucon 2021

International Standard Book Number 13 (ISBN-13)

  • 9781728199511

Digital Object Identifier (DOI)

  • 10.1109/GUCON50781.2021.9573671

Citation Source

  • Scopus