Sensitivity analysis of voltage imbalance in distribution networks with rooftop PVs

Shahnia, Farhad; Majumder, Ritwik; Ghosh, Arindam; Ledwich, Gerard; Zare, Firuz

doi:10.1109/pes.2010.5590149

Cited by 62 publications

(57 citation statements)

References 22 publications

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“…Using SAX, the voltage profile time series can be reduced to a lower dimension, w, where w is the size of the SAX word. The compression ratio achieved using SAX can be defined as, w n  ratio n compressio (9) where, n is the length of original data and w is the SAX word size. With a 20 word SAX representation, the compression ratio achieved for 1 day's voltage profile data is 14.4.…”

Section: B Dimensionality Reduction Of Results Database Using Saxmentioning

confidence: 99%

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A SAX-Based Advanced Computational Tool for Assessment of Clustered Rooftop Solar PV Impacts on LV and MV Networks in Smart Grid

Alam

Muttaqi

Sutanto

2013

IEEE Trans. Smart Grid

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Future distribution networks with increasing level of solar PV penetration will be managed using smart grid technologies capable of producing appropriate and timely response during normal and abnormal operational events. Distribution feeder loads vary throughout the day according to the trend of consumption of the customers. Solar PV outputs fluctuate in proportion to irradiance level of sun. Simultaneous occurrence of both of these variations would result in various operating conditions that may lead to unexpected events, and would require a large amount of network data to be processed and analyzed for decision making. It is envisaged that such data will be available in the future grids with the availability of smart technologies and advanced communication in residential dwellings, commercial buildings and industrial complexes. In this paper, an advanced intelligent computational tool is developed to characterize and analyze the large amount of data associated with wide variations in network behavior using SAX (Symbolic Aggregate Approximation) and pattern recognition. The proposed tool is capable of dealing with network asymmetry, load unbalance, single-phase solar PV integration and their impacts on upstream networks and will assist in making right and timely decision to mitigate adverse impacts of solar PV. The proposed tool has been tested with a practical three-phase distribution system in Australia and can provide an extensive assessment with less computational efforts and time. © 2010-2012 IEEE.

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Section: B Dimensionality Reduction Of Results Database Using Saxmentioning

confidence: 99%

“…The distribution of PV generation in a PV cluster therefore may not be equal at all the phases. This may deteriorate the existing voltage unbalance factor of the network [9]. The unbalance factor may vary from time to time due to the variations of solar irradiance and PV output.…”

Section: Voltage Unbalancementioning

confidence: 99%

A SAX-Based Advanced Computational Tool for Assessment of Clustered Rooftop Solar PV Impacts on LV and MV Networks in Smart Grid

Alam

Muttaqi

Sutanto

2013

IEEE Trans. Smart Grid

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“…In [4], custom power devices such as dynamic voltage restorer (DVR) and distribution static compensator (DSTATCOM) are used for voltage correction within the network and it is shown that for voltage profile and voltage unbalance improvements, DSTATCOMs are more efficient than DVRs. Reference [5] has investigated the voltage unbalance issue at different locations along the LV feeders populated with rooftop PVs based on a Monte Carlo method. This research indicates that rooftop PV installations will have minor effect on the voltage unbalance at the beginning of a LV feeder designed with engineering judgments; however, the voltage unbalance might increase at the end of the feeder to more than the standard limit.…”

Section: Introductionmentioning

confidence: 99%

Coordination of single-phase rooftop PVs to regulate voltage profiles of unbalanced residential feeders

Safitri

Shahnia

Masoum

2014

2014 Australasian Universities Power Engineering Conference (AUPEC)

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“…When evaluating VU in distribution networks with DG, the three-phase loads were considered as having constant values in [7,8]. For instance, in [7], loads in phase A, B and C were assumed to be 60, 120 and 180 kW, respectively.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, in [7], loads in phase A, B and C were assumed to be 60, 120 and 180 kW, respectively. The time varying characteristics of loads should be considered.…”

Section: Introductionmentioning

confidence: 99%

Point Estimate Method for Voltage Unbalance Evaluation in Residential Distribution Networks with High Penetration of Small Wind Turbines

et al. 2014

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Abstract:Voltage unbalance (VU) in residential distribution networks (RDNs) is mainly caused by load unbalance in three phases, resulting from network configuration and load-variations. The increasing penetration of distributed generation devices, such as small wind turbines (SWTs), and their uneven distribution over the three phases have introduced difficulties in evaluating possible VU. This paper aims to provide a three-phase probabilistic power flow method, point estimate method to evaluate the VU. This method, considering the randomness of load switching in customers' homes and time-variation in wind speed, is shown to be capable of providing a global picture of a network's VU degree so that it can be used for fast evaluation. Applying the 2m + 1 scheme of the proposed method to a generic UK distribution network shows that a balanced SWT penetration over three phases reduces the VU of a RDN. Greater unbalance in SWT penetration results in higher voltage unbalance factor (VUF), and cause VUF in excess of the UK statutory limit of 1.3%.

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Sensitivity analysis of voltage imbalance in distribution networks with rooftop PVs

Cited by 62 publications

References 22 publications

A SAX-Based Advanced Computational Tool for Assessment of Clustered Rooftop Solar PV Impacts on LV and MV Networks in Smart Grid

A SAX-Based Advanced Computational Tool for Assessment of Clustered Rooftop Solar PV Impacts on LV and MV Networks in Smart Grid

Coordination of single-phase rooftop PVs to regulate voltage profiles of unbalanced residential feeders

Point Estimate Method for Voltage Unbalance Evaluation in Residential Distribution Networks with High Penetration of Small Wind Turbines

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