Improving control flexibility of Electric Spring using Intelligent Neuro Controller

Authors

  • M.D.Udayakumar, A.Shunmugalatha

Abstract

Due to the significant penetration of renewable energy resources in the power generation process, the need for efficient and intelligent control schemes has enormously increased to cope with the power quality and stability issues especially in the power distribution systems. This research article proposes a controller design with improved flexibility for regulation of main voltage of energy grid in presence of large intermittent renewable energy sources such as wind and solar. Electric spring is an emerging control approach and it has been recently introduced in order to improve various features of smart grid. Neural networks are well known for its adaptability to changes in system conditions and sudden variations. They can be well trained to achieve the desired output with the available inputs. For these reasons, an intelligent neuro controller is proposed in this paper for improving the control flexibility of electric spring. Also the performance of proposed controller is verified in the MATLAB Simulink environment and the same is compared with conventional PI controllers.

Keywords- electric spring, neural network, neurocontroller, back to back converter

Published

2020-12-31

Issue

Section

Articles