Dynamic Voltage Restorer (DVR) Based On Artificial Neural Network (ANN) and Photovoltaic Design for Power Quality Improvement

In the present electric power grids, power quality issues are recognized as a crucial concerns and a frequently occurring problem possessing significant costly consequence such as sensitive load tripping and production loss. Consequently, demand for high power quality and voltage stability becomes a pressing issue. Dynamic voltage restorer (DVR) is one of the most effective solutions for “restoring” a custom power device, the quality of voltage at its load-side terminals its source-side terminals is disturbed when the quality of voltage and new DVR topology based medium-voltage application has been proposed on double flying capacitor multi-cell (DFCM) converter. The advantage of the proposed DVR is that it does not need any line-frequency step-up isolation transformer, which is bulky and costly, to be connected to medium-voltage power grid. The proposed DVR topology obtains the required active power from the energy storage feeding the dc link of the DFCM converter. The pre-sag compensation method, which is explained in detail, is used to restore amplitude and angle of the sensitive load voltage. Moreover, an approach based on d-q synchronous reference frame to determine DVR reference voltages is utilized. The proposed DVR topology is simulated and results to illustrate its performance under various conditions of voltage sag compensation are provided.