Statistics for PV, wind and biomass generators and their impact on distribution grid planning

Stefan Nykamp, Albert Molderink, Johann L. Hurink, Gerardus Johannes Maria Smit

Research output: Contribution to journalArticleAcademicpeer-review

26 Citations (Scopus)

Abstract

The integration of renewable energy generation leads to major challenges for distribution grid operators. When the feed-in of photovoltaic (PV), biomass and wind generators exceed significantly the local consumption, large investments are needed. To improve the knowledge on the interaction between these technologies, statistical information for load curves, correlation coefficients and general feed-in behavior is derived. These derivations are based on measured data of different generators in a German distribution area. In this paper, we give new insights useful for the dimensioning of grid structures and assets. Furthermore, an approach is presented which allows the calculation of the maximum and minimum feed-in resulting from different combinations of the considered technologies.
Original languageUndefined
Pages (from-to)924-932
Number of pages9
JournalEnergy
Volume45
Issue numberNo. 1
DOIs
Publication statusPublished - 1 Sep 2012

Keywords

  • PhotovoltaicWind energyBiomass generationRenewable energy generationDistribution grid planning
  • Distribution grid planning
  • Wind Energy
  • Renewable energy generation
  • Biomass generation
  • EWI-22186
  • METIS-287983
  • IR-81360
  • Photovoltaic

Cite this

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title = "Statistics for PV, wind and biomass generators and their impact on distribution grid planning",
abstract = "The integration of renewable energy generation leads to major challenges for distribution grid operators. When the feed-in of photovoltaic (PV), biomass and wind generators exceed significantly the local consumption, large investments are needed. To improve the knowledge on the interaction between these technologies, statistical information for load curves, correlation coefficients and general feed-in behavior is derived. These derivations are based on measured data of different generators in a German distribution area. In this paper, we give new insights useful for the dimensioning of grid structures and assets. Furthermore, an approach is presented which allows the calculation of the maximum and minimum feed-in resulting from different combinations of the considered technologies.",
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journal = "Energy",
issn = "0360-5442",
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Statistics for PV, wind and biomass generators and their impact on distribution grid planning. / Nykamp, Stefan; Molderink, Albert; Hurink, Johann L.; Smit, Gerardus Johannes Maria.

In: Energy, Vol. 45, No. No. 1, 01.09.2012, p. 924-932.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Statistics for PV, wind and biomass generators and their impact on distribution grid planning

AU - Nykamp, Stefan

AU - Molderink, Albert

AU - Hurink, Johann L.

AU - Smit, Gerardus Johannes Maria

N1 - eemcs-eprint-22186

PY - 2012/9/1

Y1 - 2012/9/1

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AB - The integration of renewable energy generation leads to major challenges for distribution grid operators. When the feed-in of photovoltaic (PV), biomass and wind generators exceed significantly the local consumption, large investments are needed. To improve the knowledge on the interaction between these technologies, statistical information for load curves, correlation coefficients and general feed-in behavior is derived. These derivations are based on measured data of different generators in a German distribution area. In this paper, we give new insights useful for the dimensioning of grid structures and assets. Furthermore, an approach is presented which allows the calculation of the maximum and minimum feed-in resulting from different combinations of the considered technologies.

KW - PhotovoltaicWind energyBiomass generationRenewable energy generationDistribution grid planning

KW - Distribution grid planning

KW - Wind Energy

KW - Renewable energy generation

KW - Biomass generation

KW - EWI-22186

KW - METIS-287983

KW - IR-81360

KW - Photovoltaic

U2 - 10.1016/j.energy.2012.06.067

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