abstract

• Power quality (PQ) in microgrids is a relevant topic, particularly with the complex dynamic behaviour of disturbances produced by the electronic components intrinsic in these technologies. In this paper, a qualitative-quantitative hybrid approach named multiscale recurrence quantification decomposition (MSRQD) combined with support vector machines (SVM) is proposed for PQ monitoring in microgrid systems. MSRQD combines variational mode decomposition (VMD) with recurrence quantification analysis (RQA). To validate the effectiveness of the proposed method, it is compared against other methods. In addition, three study cases are conducted in a microgrid test system using simulations, and real measured data of a main distribution feeder to prove the classification capability of the proposed method in a real environment. This novel approach, provides qualitative graphics and quantitative statistical indexes for disturbance localisation, disturbance time evolution and disturbance characterisation, as well as 3D visualisation feature space of perturbations that makes easy the interpretation to the system operator. © 2020 Elsevier Ltd

authors

• Barocio E.
• Cortes-Robles O.
• Guillen D.
• Olivares-Galvan J.C.
• Segundo J.

publication date

• 2020-01-01

published in

• Measurement: Journal of the International Measurement Confederation  Journal

keywords

• Disturbance classification; Microgrid; Power quality; Recurrence quantification analysis; Support vector machines; Variational mode decomposition Multivariable control systems; Power quality; Quality control; Support vector machines; Distribution feeders; Disturbance classification; Electronic component; Micro grid; Mode decomposition; Power quality disturbances; Real measured data; Recurrence quantification analysis; Monitoring

Digital Object Identifier (DOI)

• 10.1016/j.measurement.2019.107453

start page

end page

volume

• 154