Novel Adaptive Neural Controller Design Based on HVDC Transmission System to Damp Low Frequency Oscillations and Sub Synchronous Resonance

Ahad Goli,Samad Goli,Naser Taheri

doi:10.4236/epe.2015.710044

Abstract

This paper presents the effect of the high voltage direct current (HVDC) transmission system based on voltage source converter (VSC) on the sub synchronous resonance (SSR) and low frequency oscillations (LFO) in power system. Also, a novel adaptive neural controller based on neural identifier is proposed for the HVDC which is capable of damping out LFO and sub synchronous oscillations (SSO). For comparison purposes, results of system based damping neural controller are compared with a lead-lag controller based on quantum particle swarm optimization (QPSO). It is shown that implementing adaptive damping controller not only improves the stability of power system but also can overcome drawbacks of conventional compensators with fixed parameters. In order to determine the most effective input of HVDC system to apply supplementary controller signal, analysis based on singular value decomposition is performed. To evaluate the performance of the proposed controller, transient simulations of detailed nonlinear system are considered.

Highlights

IntroductionHow to cite this paper: Goli, S., Goli, A. and Taheri, N. (2015) Novel Adaptive Neural Controller Design Based on high voltage direct current (HVDC) Transmission System to Damp Low Frequency Oscillations and Sub Synchronous Resonance
Series capacitors have extensively been used as a very effective means of increasing the power transfer capabil-How to cite this paper: Goli, S., Goli, A. and Taheri, N. (2015) Novel Adaptive Neural Controller Design Based on high voltage direct current (HVDC) Transmission System to Damp Low Frequency Oscillations and Sub Synchronous Resonance
A power system including turbine-generator and voltage source converter (VSC) HVDC transmission system has been modeled as nonlinear state space equations

Summary

Introduction

How to cite this paper: Goli, S., Goli, A. and Taheri, N. (2015) Novel Adaptive Neural Controller Design Based on HVDC Transmission System to Damp Low Frequency Oscillations and Sub Synchronous Resonance. (2015) Novel Adaptive Neural Controller Design Based on HVDC Transmission System to Damp Low Frequency Oscillations and Sub Synchronous Resonance. SSR is a condition of an electrical power system where electrical networks exchange energy with the mechanical system of the generator at frequencies less than the nominal frequency of the transmission line [6] At this situation, the turbine-generator oscillates at a frequency corresponding to the torsional mode frequency. A power system including turbine-generator and VSC HVDC transmission system has been modeled as nonlinear state space equations. These equations have been linearized around operating point in order to analyze the small-signal stability, design damping phase compensator and measurement of oscillation mode controllability. The online training method is applied to training the controller through neural identifier and the performance of supplementary neural controller, which can be tuned for overall operating points, is compared with phase compensator

Power System Equipped by HVDC and Turbine-Generator System

VSC HVDC Dynamical Model

Turbine-Generator Dynamic Model

Lead-Lag Compensator based on QPSO

Adaptive Neural Controller

Controllability of Oscillation Mode

Simulation Results

Conclusion