Decentralized Load Frequency Control with Prescribed Performance for Interconnected Power Systems

Charalampos P. Bechlioulis, Leonidas Dritsas, Kostas J. Kyriakopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper deals with the Load Frequency Control (LFC) problem of a networked electric power system, consisting of multiple areas interconnected via weak tie-lines, under the effect of unknown bounded and piecewise continuous power load disturbances. Within this framework, the control objective is to stabilize both the frequency deviation and the power transferred via the tie-lines. The main contribution of this work is the design of a fully decentralized control law guaranteeing regulation of both frequency and tie-line power deviation to an a priori specified and arbitrarily small area of the origin with prescribed transient performance. The proposed controller, apart from being decentralized, is also robust against all admissible load disturbances as well as plant modeling errors, since it is (by design) model-free. Finally, comparative simulation results on a power system benchmark model of three identical areas with a fully centralized model-based linear controller based on H∞ techniques, demonstrated the applicability of the proposed decentralized control protocol and highlighted its efficiency to handle extreme load conditions.

Original languageEnglish (US)
Title of host publication2019 IEEE 58th Conference on Decision and Control, CDC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781728113982
StatePublished - Dec 2019
Event58th IEEE Conference on Decision and Control, CDC 2019 - Nice, France
Duration: Dec 11 2019Dec 13 2019

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370


Conference58th IEEE Conference on Decision and Control, CDC 2019

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization


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