A Review of State Estimation Techniques for Grid-Connected PMSG-Based Wind Turbine Systems

Ganesh Mayilsamy; Kumarasamy Palanimuthu; Raghul Venkateswaran; Ruban Periyanayagam Antonysamy; So Mi Lee; Dongran Song; Young Hoon Joo

doi:10.3390/en16020634

journal article Open Access Jan 05, 2023

A Review of State Estimation Techniques for Grid-Connected PMSG-Based Wind Turbine Systems

Ganesh Mayilsamy

Kumarasamy Palanimuthu

Raghul Venkateswaran

Ruban Periyanayagam Antonysamy

So Mi Lee Dongran Song

Young Hoon Joo

Energies Vol. 16 No. 2 pp. 634 · MDPI AG

View at Publisher Save 10.3390/en16020634

Abstract

The power system network grows yearly with a large number of nonlinear power generation systems. In this scenario, accurate modeling, control, and monitoring of interface systems and energy conversion systems are critical to the reliability and performance of the overall power system. In this trend, the permanent magnet synchronous generator (PMSG)-based wind turbine systems (WTS) equipped with a full-rated converter significantly contribute to the development of new and renewable energy generation. The various components and control systems involved in operating these systems introduce higher complexity, uncertainty, and highly nonlinear control challenges. To deal with this, state estimation remains an ideal and reliable procedure in the relevant control of the entire WTS. In essence, state estimation can be useful in control procedures, such as low-voltage ride-through operation, active power regulation, stator fault diagnosis, maximum power point tracking, and sensor faults, as it reduces the effects of noise and reveals all hidden variables. However, many advanced studies on state estimation of PMSG-based WTS deal with real-time information of operating variables through filters and observers, analysis, and summary of these strategies are still lacking. Therefore, this article aims to present a review of state-of-the-art estimation methods that facilitate advances in wind energy technology, recent power generation trends, and challenges in nonlinear modeling. This review article enables readers to understand the current trends in state estimation methods and related issues of designing control, filtering, and state observers. Finally, the conclusion of the review demonstrates the direction of future research.

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Published: Jan 05, 2023
Vol/Issue: 16(2)
Pages: 634
License: View

Authors

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Ganesh Mayilsamy