LAPSE:2023.9686
Published Article
LAPSE:2023.9686
Model Predictive Phase Control for Single-Phase Electric Springs
February 27, 2023
Abstract
In this paper, model predictive control (MPC) is proposed for single-phase electric springs (ESs) with the help of the existing δ control, which is realized by controlling the instantaneous phase angle of the predefined sinusoidal reference of a certain controller. System modeling is analyzed first to get differential forms of state variables. The discrete-time state space model is obtained through first-order approximation. Critical load (CL) voltage can be predicted by the prediction of ES voltage and line current. The operating modes of ESs can be determined and the reference signal for CL voltage can be provided by δ control. As a result, cost function is obtained as the absolute value of the error between predicted CL voltage and its predefined reference. Two typical operating functions such as pure reactive power compensation mode and power factor correction (PFC) mode are selected and simulated to validate the proposed control and analysis. It is revealed that both control objectives can be achieved with the proposed MPC and δ control. Additionally, the total harmonic distortion on the critical load is limited to about 0.5%, which is better than other existing methods.
Keywords
distributed generation, electric spring, grid connected, microgrids, Model Predictive Control, phase control, reactive power compensation
Suggested Citation
Wang Q, Ding H, Yan S, Buja G. Model Predictive Phase Control for Single-Phase Electric Springs. (2023). LAPSE:2023.9686
Author Affiliations
Wang Q: School of Electrical Engineering, Southeast University, Nanjing 210096, China; Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment, Southeast University, Nanjing 210096, China [ORCID]
Ding H: School of Software Engineering, Southeast University, Suzhou 215000, China [ORCID]
Yan S: School of Engineering, RMIT University, Melbourne, VIC 3000, Australia
Buja G: Department of Industrial Engineering, University of Padova, 35131 Padova, Italy [ORCID]
Journal Name
Energies
Volume
15
Issue
18
First Page
6654
Year
2022
Publication Date
2022-09-12
ISSN
1996-1073
Version Comments
Original Submission
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PII: en15186654, Publication Type: Journal Article
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LAPSE:2023.9686
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https://doi.org/10.3390/en15186654
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