Grid Parameter estimation using Model Predictive Direct Power Control

Arif, Bilal; Tarisciotti, Luca; Zanchetta, Pericle; Clare, Jon C.; Degano, Marco

Abstract

This paper presents a novel Finite Control Set Model Predictive Control (FS-MPC) approach for grid-connected converters. The control performance of such converters may get largely affected by variations in the supply impedance, especially for systems with low Short Circuit Ratio (SCR) values. A novel idea for estimating the supply impedance variation, and hence the grid voltage, using an algorithm embedded in the MPC is presented in this paper. The estimation approach is based on the difference in grid voltage magnitudes at two consecutive sampling instants, calculated on the basis of supply currents and converter voltages directly within the MPC algorithm, achieving a fast estimation and integration between the controller and the impedance estimator. The proposed method has been verified, using simulation and experiments, on a 3-phase 2-level converter.

Citation

Arif, B., Tarisciotti, L., Zanchetta, P., Clare, J. C., & Degano, M. (2015). Grid Parameter estimation using Model Predictive Direct Power Control. IEEE Transactions on Industry Applications, 51(6), https://doi.org/10.1109/TIA.2015.2453132

• Journal Article Type: Article
• Acceptance Date: Jun 25, 2015
• Online Publication Date: Jul 7, 2015
• Publication Date: Nov 19, 2015
• Deposit Date: May 5, 2016
• Publicly Available Date: May 5, 2016
• Journal: IEEE Transactions on Industry Applications
• Print ISSN: 0093-9994
• Electronic ISSN: 1939-9367
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 51
• Issue: 6
• DOI: https://doi.org/10.1109/TIA.2015.2453132
• Public URL: https://nottingham-repository.worktribe.com/output/766134
• Publisher URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7151796
• Additional Information: 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.