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A possibilistic-probabilistic tool for evaluating the impact of stochastic renewable and controllable power generation on energy losses in distribution networks--A case study

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  • Soroudi, Alireza
  • Ehsan, Mehdi

Abstract

This paper proposes a hybrid possibilistic-probabilistic evaluation tool for analyzing the effect of uncertain power production of distributed generations (DGs) on active losses of distribution networks. The considered DG technologies are gas and wind turbines. This tool is useful for distribution network operators (DNOs) when they are faced with uncertainties which some of them can be modeled probabilistically and some of them are described possibilistically. The generation pattern of DG units changes the flow of lines and this will cause change of active losses which DNO is responsible for compensating it. This pattern is highly dependent on DG technology and also on decisions of DG operator which is an entity other than DNO. For wind turbines, this pattern is described using a weibull probability distribution function (PDF) for wind speed along with the power curve of the wind turbine but for other controllable DG technologies like gas turbines, it is not an easy job to provide a PDF to describe the generation schedule. On the other hand, the values of loads cannot be always described using a PDF so the possibilistic (fuzzy) description can be helpful in such cases. In order to demonstrate the effectiveness of the proposed tool, it is applied to a realistic distribution system and the results are analyzed and discussed.

Suggested Citation

  • Soroudi, Alireza & Ehsan, Mehdi, 2011. "A possibilistic-probabilistic tool for evaluating the impact of stochastic renewable and controllable power generation on energy losses in distribution networks--A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 794-800, January.
    • Handle: RePEc:eee:rensus:v:15:y:2011:i:1:p:794-800
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    1. Alarcon-Rodriguez, Arturo & Ault, Graham & Galloway, Stuart, 2010. "Multi-objective planning of distributed energy resources: A review of the state-of-the-art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1353-1366, June.
    2. Lin, Q.G. & Huang, G.H., 2009. "A dynamic inexact energy systems planning model for supporting greenhouse-gas emission management and sustainable renewable energy development under uncertainty--A case study for the City of Waterloo,," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1836-1853, October.
    3. Eltawil, Mohamed A. & Zhao, Zhengming, 2010. "Grid-connected photovoltaic power systems: Technical and potential problems--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(1), pages 112-129, January.
    4. Ancona, D.F. & Goldman, P.R. & Thresher, R.W., 1997. "Wind program technological developments in the United States," Renewable Energy, Elsevier, vol. 10(2), pages 253-258.
    5. Jafarian, M. & Ranjbar, A.M., 2010. "Fuzzy modeling techniques and artificial neural networks to estimate annual energy output of a wind turbine," Renewable Energy, Elsevier, vol. 35(9), pages 2008-2014.
    6. Walter, A. & Overend, R.P., 1999. "Financial and environmental incentives: Impact on the potential of BIG-CC technology at the sugar-cane industry," Renewable Energy, Elsevier, vol. 16(1), pages 1045-1048.
    7. van Dam, J. & Faaij, A.P.C. & Hilbert, J. & Petruzzi, H. & Turkenburg, W.C., 2009. "Large-scale bioenergy production from soybeans and switchgrass in Argentina: Part B. Environmental and socio-economic impacts on a regional level," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1679-1709, October.
    8. Gouveia, Eduardo M. & Matos, Manuel A., 2009. "Symmetric AC fuzzy power flow model," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1012-1018, September.
    9. Kongnam, C. & Nuchprayoon, S. & Premrudeepreechacharn, S. & Uatrongjit, S., 2009. "Decision analysis on generation capacity of a wind park," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 2126-2133, October.
    Full references (including those not matched with items on IDEAS)

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    12. Li, Yanfu & Zio, Enrico, 2012. "Uncertainty analysis of the adequacy assessment model of a distributed generation system," Renewable Energy, Elsevier, vol. 41(C), pages 235-244.
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    14. Maammeur, H. & Hamidat, A. & Loukarfi, L. & Missoum, M. & Abdeladim, K. & Nacer, T., 2017. "Performance investigation of grid-connected PV systems for family farms: case study of North-West of Algeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 1208-1220.
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    17. Zubo, Rana.H.A. & Mokryani, Geev & Rajamani, Haile-Selassie & Aghaei, Jamshid & Niknam, Taher & Pillai, Prashant, 2017. "Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1177-1198.
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