Improve Capability of LVRT by STATCOM with Intelligent Control
Date Issued
2011
Date
2011
Author(s)
Huang, Sheng-Min
Abstract
Because of global warming ,carbon reduction requirements and the increasing price of fossil energy, renewable energy will become gradually generalization that power system will face scheduling, system impact and stability problems. This paper focuses on the use of STATCOM, series dynamic break resistance and series dynamic break inductance combination those technologies to enhance micro-grid LVRT capacity. Synchronous generator can also make low-voltage conditions, an increase in tolerance within a short period of service capabilities, and improve the system stability during the recovery period.
Taking into account the instability of micro-grid due to intermittence of renewable energy supply, in all cases to have more stable and faster control output ,this thesis utilizes fuzzy neural networks online learning approach to control STATCOM, aiming at achieving the effective ,adaptive and nonlinear control.
In this study, MATLAB / Simulink software package as a simulation platform to validate the feasibility of fuzzy neural networks control, and to observe LVRT performance improvement results.
Subjects
micro-grid
low voltage ride through
fuzzy neural networks
DHP algorithm
series dynamic breaking resistor (SDBR)
SDGs
Type
thesis
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