Design of Central Unit for Voltage Estimation-based Load Shedding Methods to Deal with FIDVR

Document Type : Research Article

Authors

1 Department of Electrical Engineering, Shahid Beheshti University

2 Department of Electrical Engineering, Shahid Beheshti University Monenco Iran Consulting Engineers Company

3 Iran Grid Management Company

Abstract

Fault-induced delayed voltage recovery (FIDVR) occurs after fault in the network with high penetration of induction motor (IM) loads. Load shedding (LS) is one of the appropriate methods to reduce the destructive effects of FIDVR on the network, and for this reason, the authors have previously presented three LS methods to deal with FIDVR. The first method uses the index of IM loads’ power change. The second one is an optimization problem and the third method introduces indicators based on sensitivity analysis. The proposed methods obtain less LS amounts, also, the number of LS locations and moments of proposed methods are fewer than previous ones. However, these methods have different execution times which are related to the speed of utilized processor; and the suitable method to deal with FIDVR must have the ability to shed the load in the initial moments of this phenomenon. Since the proposed LS methods are centralized, therefore, a central unit is required to monitor the network through the voltage and current sent through PMUs and status of circuit-breakers, for detecting critical conditions and determining the amount and location of LS. Various states such as estimation of load parameters, detection of fault occurrence and clearance, detection of topology change, and voltage estimation process are also needed before start of LS calculations, which are discussed in this paper. Also, the telecommunication required by this central unit is provided with GOOSE message based on IEC 61850 standard.

Keywords

Main Subjects

AUT Journal of Electrical Engineering

Articles in Press, Accepted Manuscript
Available Online from 23 March 2024

Files

Share

How to cite

Statistics