Event‐triggered distributed model predictive control for resilient voltage control of an islanded microgrid. (22nd September 2020)

• Record Type: Journal Article
• Authors: Ge, Pudong; Chen, Boli; Teng, Fei
• Other Names: Wan Yan guestEditor.; Yang Tao guestEditor.; Yuan Ye guestEditor.; Lewis Frank L. guestEditor.
• Is Part Of: International journal of robust and nonlinear control. Volume 31:Number 6(2021)
• Page Start: 1979
• Page End: 2000
• Publication Date: 2020-09-22
• Subjects: distributed model predictive control -- event‐triggered control -- microgrid -- nonasymptotic observer -- resilience; Automatic control -- Periodicals; Control theory -- Periodicals; Nonlinear systems -- Periodicals; 629.836
• DOI: 10.1002/rnc.5238
• Languages: English
• ISSNs: 1049-8923

Abstract

Summary: This article addresses the problem of distributed secondary voltage control of an islanded microgrid (MG) from a cyber‐physical perspective. An event‐triggered distributed model predictive control (DMPC) scheme is designed to regulate the voltage magnitude of each distributed generators (DGs) in order to achieve a better trade‐off between the control performance and communication and computation burdens. By using two novel event triggering conditions that can be easily embedded into the DMPC for the application of MG control, the computation and communication burdens are significantly reduced with negligible compromise of control performance. In addition, to reduce the sensor cost and to eliminate the negative effects of nonlinearity, an adaptive nonasymptotic observer is utilized to estimate the internal and output signals of each DG. Thanks to the deadbeat observation property, the observer can be applied periodically to cooperate with the DMPC‐based voltage regulator. Finally, the effectiveness of the proposed control method has been tested on a simple configuration with four DGs and the modified IEEE‐13 test system through several representative scenarios.