سیویلیکا را در شبکه های اجتماعی دنبال نمایید.

Fault Detection and Location in Power Systems with Large-Scale Photovoltaic Power Plant by Adaptive Distance Relays

Publish Year: 1403
Type: Journal paper
Language: English
View: 115

This Paper With 14 Page And PDF Format Ready To Download

Export:

Link to this Paper:

Document National Code:

JR_IJEE-15-3_003

Index date: 14 December 2023

Fault Detection and Location in Power Systems with Large-Scale Photovoltaic Power Plant by Adaptive Distance Relays abstract

In this paper, a novel approach is introduced for Fault Detection and Fault Location in power systems that incorporate Large-Scale Photovoltaic Power Plants (LSPPPs). Given that short-circuit (SC) characteristics in photovoltaic systems differ significantly from those observed in traditional Synchronous Generators (SGs). The increasing integration of LSPPPs into the power grid is anticipated to have an impact on the performance of conventional protection relay systems; initially designed for SG-dominated setups. Therefore, the proposed method revolves around analyzing the influence of LSPPPs on the alteration of observed transmission line impedance to identify and locate faults accurately. Furthermore, the methodology takes into consideration factors such as fault location, fault resistance, fault type, changing the LSPPP generation, and noise conditions. when calculating the phase angle of the fault loop current. The effectiveness of this approach was assessed through testing and evaluation on 2-bus and IEEE 39-bus test systems connected to an LSPPP, simulated using PSCAD/EMTDC and MATLAB/SIMULINK.

Fault Detection and Location in Power Systems with Large-Scale Photovoltaic Power Plant by Adaptive Distance Relays Keywords:

Fault Detection and Location in Power Systems with Large-Scale Photovoltaic Power Plant by Adaptive Distance Relays authors

A. Jodaei

Faculty of Electrical & Computer Engineering, Semnan University, Semnan, Iran

Z Moravej

Faculty of Electrical & Computer Engineering, Semnan University, Semnan, Iran

مراجع و منابع این Paper:

لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :
Salazar-Chiralt R, Cheah-Mane M, Mateu-Barriendos E, Bullich-Massague E, Prieto-Araujo E, ...
نمایش کامل مراجع