Research on Voltage Sag Loss Assessment Based on a Two-Stage Taguchi Quality Perspective Method
Author:
Guo Cheng1, Zhang Xinyuan1, He Mi2, Wang Linling1, Yang Xuanming1
Affiliation:
1. School of Electric Power Engineering, Kunming University of Science and Technology, Kunming 650500, China 2. Kunming Power Supply Bureau of Yunnan Power Grid Co., Ltd., Kunming 650000, China
Abstract
Voltage sags resulting from symmetrical or asymmetrical faults pose a significant threat to power quality. In response to this challenge, a voltage sag loss assessment method based on a two-stage Taguchi quality perspective approach is proposed to address the quantitative analysis of voltage sag economic losses. Initially, using the Taguchi quality perspective method, single-index quality loss functions are separately established for voltage sag magnitude and fault duration. Subsequently, by introducing a comprehensive load tolerance curve, sensitivity parameters within the quality loss function are accurately calculated. This yields a deterministic model for voltage sag assessment. Building upon this, the relative impact of the two indices on voltage sag loss is evaluated using the quality loss function. Consequently, a comprehensive loss model under the influence of multiple indices is formed by integrating two single-index evaluation models. The simulation results indicate that this method can effectively assess the economic losses of voltage sags under the combined influence of multiple factors. Compared to the original economic loss assessment method, it improves quantitative accuracy by approximately 3.72%. Moreover, the method reduces the computational complexity of loss assessment through the consolidation of intervals with similar sensitivity parameters.
Funder
Yunnan Provincial Department of Science and Technology Joint Special Fund National Natural Science Foundation of China
Reference25 articles.
1. A New PV-Open-UPQC Configuration for Voltage Sensitive Loads Utilizing Novel Adaptive Controllers;Dash;IEEE Trans. Ind. Inform.,2021 2. Zheng, C., Dai, S., Zhang, B., Li, Q., Liu, S., Tang, Y., Wang, Y., Wu, Y., and Zhang, Y. (2022). A Residual Voltage Data-Driven Prediction Method for Voltage Sag Based on Data Fusion. Symmetry, 14. 3. Current Reconstruction of Three-Phase Voltage Source Inverters Considering Current Ripple;Shen;IEEE Trans. Transp. Electrif.,2023 4. Sensitivity Analysis Based Identification of Key Parameters in the Dynamic Model of a Utility-Scale Solar PV Plant;Guddanti;IEEE Trans. Power Syst.,2022 5. Xiao, S., Wang, Z., Wu, G., Guo, Y., Gao, G., Zhang, X., Cao, Y., Zhang, Y., Yu, J., and Liu, P. (2023). The impact analysis of operational overvoltage on traction transformers for high-speed trains based on the improved capacitor network methodology. IEEE Trans. Transp. Electrif., 1.
|
|