Disturbance Observer-Based Model Predictive Super-Twisting Control for Soft Open Point

Zhengqi Wang, Haoyu Zhou and Hongyu Su
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Zhengqi Wang: School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China
Haoyu Zhou: School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China
Hongyu Su: School of Electrical and Electronic Engineering, Harbin University of Science and Technology, Harbin 150001, China

Energies, 2022, vol. 15, issue 10, 1-19

Abstract: This paper presents a disturbance observer-based model predictive of super-twisting control for Soft Open Point (SOP). First, with the consideration of the disturbances caused by parameter mismatches and unmodelled dynamics, a super-twisting sliding-mode observer (STO) is proposed to observe the disturbances, and the observed disturbances are introduced into the inner-loop as the compensation to improve the anti-disturbance of SOP system. Second, the outer-loop controller is designed by applying the super-twisting sliding-mode control (STC) approach to improve the dynamic performance and robustness. Third, to deal with large current harmonics by traditional model predictive control (MPC), a Three-Vector-based MPC (TV-MPC) is proposed to increase the number of voltage vectors in a sampling time. Finally, it is verified by simulations that the proposed method can reduce current harmonics, DC-side voltage setting time and improve the dynamic performance of SOP system effectively. In case of parameter mismatches, the proposed observer can observe the disturbances correctly to enhance the robustness of the SOP system.

Keywords: Soft Open Point (SOP); model predictive control (MPC); parameter mismatch; super-twisting algorithm; sliding-mode observer (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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