High penetration of rooftop photovoltaic cells in low voltage distribution networks : voltage imbalance and improvement

Shahnia, Farhad & Ghosh, Arindam (2014) High penetration of rooftop photovoltaic cells in low voltage distribution networks : voltage imbalance and improvement. In Hossain, Jahangir & Mahmud, Apel (Eds.) Renewable Energy Integration, Challenges and Solutions. Springer Singapore, Singapore, pp. 69-95.

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Abstract

Installation of domestic rooftop photovoltaic cells (PVs) is increasing due to feed–in tariff and motivation driven by environmental concerns. Even though the increase in the PV installation is gradual, their locations and ratings are often random. Therefore, such single–phase bi–directional power flow caused by the residential customers can have adverse effect on the voltage imbalance of a three–phase distribution network. In this chapter, a voltage imbalance sensitivity analysis and stochastic evaluation are carried out based on the ratings and locations of single–phase grid–connected rooftop PVs in a residential low voltage distribution network. The stochastic evaluation, based on Monte Carlo method, predicts a failure index of non–standard voltage imbalance in the network in presence of PVs. Later, the application of series and parallel custom power devices are investigated to improve voltage imbalance problem in these feeders. In this regard, first, the effectiveness of these two custom power devices is demonstrated vis–à–vis the voltage imbalance reduction in feeders containing rooftop PVs. Their effectiveness is investigated from the installation location and rating points of view. Later, a Monte Carlo based stochastic analysis is utilized to investigate their efficacy for different uncertainties of load and PV rating and location in the network. This is followed by demonstrating the dynamic feasibility and stability issues of applying these devices in the network.

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ID Code: 69796
Item Type: Book Chapter
Keywords: Distribution network, Single–phase rooftop PV, Voltage imbalance, Sensitivity analysis, Stochastic evaluation, DSTATCOM, DVR
DOI: 10.1007/978-981-4585-27-9_4
ISBN: 9789814585262
ISSN: 1865-3529
Divisions: Current > QUT Faculties and Divisions > Chancellery
Current > Schools > School of Electrical Engineering & Computer Science
Copyright Owner: Copyright 2014 Springer Science+Business Media Singapore
Deposited On: 03 Apr 2014 22:07
Last Modified: 23 Aug 2016 16:02

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