Open AccessImproved disturbance detection and load shedding technique for low voltage islanded microgrids
Author(s) -
Arunan Anusuya,
Ravishankar Jayashri,
Ambikairajah Eliathamby
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.5707
Subject(s) - microgrid , control theory (sociology) , disturbance (geology) , voltage , electric power system , matlab , limit (mathematics) , computer science , inertia , battery (electricity) , power (physics) , engineering , control (management) , mathematics , artificial intelligence , paleontology , physics , quantum mechanics , electrical engineering , biology , mathematical analysis , classical mechanics , operating system
The rate of change of frequency (RoCoF) following any disturbance in low voltage islanded microgrids is not only relatively high compared to conventional systems, but also becomes location specific due to the presence of highly resistive lines. This makes the disturbance detection challenging. A novel real‐time disturbance detection technique for low voltage islanded microgrids is proposed that is independent of the system inertia, which can detect any disturbance within 100 ms. A dedicated initial RoCoF calculation is developed over a 30 ms window especially during disturbances. The authors use a support vector machine‐based regression model for the estimation of the amount of disturbance with three different feature selections. These models prove that only the RoCoF is not enough to estimate the amount of disturbance in an islanded microgrid and additional features from the frequency and different bus voltages also required. A load shedding algorithm encompassing battery support is also proposed to protect the system from quick frequency collapse by providing power from the battery when the frequency reaches its standard operational limit. All the proposed algorithms are tested with a low voltage islanded microgrid modelled in MATLAB/SIMULINK. The results are also verified with noisy data to reflect real system performance.