Memory-based adaptive sliding mode load frequency control in interconnected power systems with energy storage

Authors

Farhad Farivar, Edith Cowan UniversityFollow
Octavian Bass, Edith Cowan UniversityFollow
Daryoush Habibi, Edith Cowan UniversityFollow

Document Type

Journal Article

Publication Title

IEEE Access

Publisher

IEEE

School

School of Engineering

RAS ID

60692

Comments

Farivar, F., Bass, O., & Habibi, D. (2023). Memory-based adaptive sliding mode load frequency control in interconnected power systems with energy storage. IEEE Access, 11, 102515-102530. https://doi.org/10.1109/ACCESS.2023.3317181

Abstract

This paper presents a memory-based adaptive sliding mode load frequency control (LFC) strategy aimed at minimizing the impacts of exogenous power disturbances and parameter uncertainties on frequency deviations in interconnected power systems with energy storage. First, the dynamic model of the system is constructed by considering the participation of the energy storage system (ESS) in the conventional decentralized LFC model of a multiarea power system. A disturbance observer (DOB) is proposed to generate an online approximation of the lumped disturbance. In order to enhance the transient performance of the system and effectively mitigate the adverse effects of power fluctuations on grid frequency, a novel memory-based sliding surface is developed. This sliding surface incorporates the estimation of the lumped disturbance, as well as the past and present information of the state variables. The conservative assumption about the lumped disturbance is eased by considering the unknown upper bound of the disturbance and its first derivative. Based on the output of the proposed DOB, an adaptive continuous sliding mode controller with prescribed H performance index is introduced. This controller ensures that the sliding surface is reachable and guarantees asymptotic stability of the closed-loop system. The controller design utilizes strict linear matrix inequalities (LMIs) to achieve these objectives. Finally, the applicability and efficacy of the proposed scheme are verified through comparative simulation cases. Author

DOI

10.1109/ACCESS.2023.3317181

Creative Commons License

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