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Cited by 16Optimal Power Flow DistributionThermal Analysis in Power TransmissionElectric Power System Optimization

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Sensitivity of Hosting Capacity to Data Resolution and Uncertainty Modeling

Abad, Mohammad Seydali Seyf, Ma, Jin, Zhang, Diwei, Ahmadyar, Ahmad Shabir, Marzooghi, Hesamoddin·2018·2018 Australasian Universities Power Engineering Conference (AUPEC)
DOI 10.1109/aupec.2018.8757980
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Abstract

Integration limits of distributed generations (DGs) in distribution networks, i.e. the hosting capacity (HC), are highly dependent on uncertainties associated with the size, location and output power of DGs. Addressing these uncertainties to a great extent is reliant on the availability and resolution of the historical data. This paper investigates the effects of data resolution and uncertainty modeling on the HC calculation. To do so, a mathematical model of the HC problem is used in a Monte Carlo-based framework. Our analysis is carried out on an agricultural distribution network in Australia. It is shown that decreasing the resolution of historical data shifts the probability distribution function of the HC towards right implying an increase in the estimated HC. Further, it is illustrated that assuming a fixed capacity for DGs instead of proper modeling of the uncertainty associated with their size results in underestimation of the HC in the network.

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Research works printed but not linked: 23

  1. 2015, Western Australian Distribution Connections Manual, Horizon Power and Western Power
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  7. dubey, 2016, On estimation and sensitivity analysis of distribution circuit’s photovoltaic hosting capacity, IEEE Transactions on Power Systems, pp, 1
  8. 10.1016/j.energy.2016.11.095 · DOI
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  11. 10.1109/TSTE.2010.2098483 · DOI
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  13. ding, 2016, On distributed PV hosting capacity estimation, sensitivity study and improvement, IEEE Transactions on Sustainable Energy, pp, 1
  14. 10.1109/AUPEC.2017.8282428 · DOI
  15. smith, 2012, Stochastic Analysis to Determine Feeder Hosting Capacity for Distributed Solar PV
  16. 2014, Small Generator Interconnection Procedures, Section 2.2.1.2, FERC
  17. 10.1016/j.enpol.2011.07.027 · DOI
  18. 10.1109/TSG.2017.2665530 · DOI
  19. 10.1016/j.segan.2016.06.003 · DOI · Paper page
  20. berry, 2013, National feeder taxonomy describing a representative feeder set for Australian networks
  21. 0, Solar home electricity data
  22. 0, Aggregated price and demand data - historical
  23. 10.1109/PESGM.2015.7286510 · DOI

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Metadata

Authors
Abad, M. S. S., Ma, J., Zhang, D., Ahmadyar, A. S., & Marzooghi, H.
Affiliations
The University of Sydney (AU)
ORCID
Venue
2018 Australasian Universities Power Engineering Conference (AUPEC)
Publisher
IEEE
Published
2018-11
Pages
1-6
DOI
10.1109/aupec.2018.8757980
OpenAlex
W2956169614
Cited by
16
References
0
Citations by year
2024: 4 · 2023: 2 · 2022: 2 · 2021: 1 · 2020: 2 · 2019: 4 · 2018: 1
FWCI
3.19
Type
conference paper
Language
en
Open access
closed
Locations
Australasian Universities Power Engineering Conference (publishedVersion)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Thermal Analysis in Power Transmission
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
Keywords
hosting capacity, distributed generation, distribution networks, uncertainty modeling, data resolution, historical data, Monte Carlo simulation, limits of integration

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