Charles Darwin University

CDU eSpace
Institutional Repository

 
CDU Staff and Student only
 

Neural network-based active power curtailment for overvoltage prevention in low voltage feeders

Yap, Wai, Havas, Lisa, Overend, Elizabeth and Karri, Vishy (2014). Neural network-based active power curtailment for overvoltage prevention in low voltage feeders. Expert Systems with Applications,41(4 - Part 1):1063-1070.

Document type: Journal Article
Citation counts: Scopus Citation Count Cited 0 times in Scopus Article

Google Scholar Search Google Scholar

IRMA ID 84376995xPUB5
Title Neural network-based active power curtailment for overvoltage prevention in low voltage feeders
Author Yap, Wai
Havas, Lisa
Overend, Elizabeth
Karri, Vishy
Journal Name Expert Systems with Applications
Publication Date 2014
Volume Number 41
Issue Number 4 - Part 1
ISSN 0957-4174   (check CDU catalogue open catalogue search in new window)
Scopus ID 2-s2.0-84888301431
Start Page 1063
End Page 1070
Total Pages 8
Place of Publication United Kingdom
Publisher Pergamon Press
HERDC Category C1 - Journal Article (DIISR)
Abstract As non-controllable and intermittent power sources, grid-connected photovoltaic (PV) systems can contribute to overvoltage in low voltage (LV) distribution feeders during periods of high solar generation and low load where there exists a possibility of reverse power flow. Overvoltage is usually prevented by conservatively limiting the penetration level of PV, even if these critical periods rarely occur. This is the current policy implemented in the Northern Territory, Australia, where a modest system limit of 4.5 kW/house was imposed. This paper presents an active power curtailment (APC) strategy utilizing artificial neural networks techniques. The inverter active power is optimized to prevent any overvoltage conditions on the LV feeder. A residential street located in Alice Springs was identified as a case study for this paper. Simulation results demonstrated that overvoltage conditions can be eliminated and made to comply with the Australian Standards AS60038 and AS4777 by incorporating the proposed predictive APC control. In addition, the inverter downtime due to overvoltage trips was eliminated to further reduce the total power losses in the system.
Keywords Overvoltage
Voltage-rise
Predictive modeling
Active power curtailment
Artificial neural networks
DOI http://dx.doi.org/10.1016/j.eswa.2013.07.103   (check subscription with CDU E-Gateway service for CDU Staff and Students  check subscription with CDU E-Gateway in new window)
 
Versions
Version Filter Type
Access Statistics: 16 Abstract Views  -  Detailed Statistics
Created: Wed, 19 Aug 2015, 12:06:05 CST