Optimal Gain-scheduled POD for Power Systems with Hybrid HVDC Links

Otavio Bertozzi, Harold R. Chamorro, Omar Kotb, Eduardo Prieto-Araujo, Shehab Ahmed

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

The evolving High Voltage Direct Current (HVDC) technology integrated into the modern power grids can help improve operation stability and damp undesired low-frequency oscillations in the system. This paper presents a Power Oscillation Damping (POD) strategy for power systems with a hybrid (LCC-VSC) HVDC link. The work consists of a centralized supervision algorithm that monitors the dynamics of several system variables and sets the appropriate gains to the POD controller from a lookup table (LUT) generated offline via simulation-based Particle Swarm optimization analysis. The mathematical modeling for the test system with an embedded HVDC link is presented, and the optimal tuning problem is defined using performance-oriented objective functions. Details for the detection and scheduling algorithm, LUT construction, and controller structure are provided. The nonlinear simulation model is implemented in MATLAB, and the results support the effectiveness of the proposed approach.

Original languageEnglish (US)
Title of host publicationSEST 2022 - 5th International Conference on Smart Energy Systems and Technologies
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665405577
DOIs
StatePublished - 2022
Event5th International Conference on Smart Energy Systems and Technologies, SEST 2022 - Eindhoven, Netherlands
Duration: Sep 5 2022Sep 7 2022

Publication series

NameSEST 2022 - 5th International Conference on Smart Energy Systems and Technologies

Conference

Conference5th International Conference on Smart Energy Systems and Technologies, SEST 2022
Country/TerritoryNetherlands
CityEindhoven
Period09/5/2209/7/22

Keywords

  • Gain Scheduling
  • Hybrid HVDC
  • Particle Swarm optimization
  • Power Oscillation Damping

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Hardware and Architecture
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Control and Optimization

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