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

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  • Nykamp, Stefan
  • Molderink, Albert
  • Hurink, Johann L.
  • Smit, Gerald J.M.

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.

Suggested Citation

  • Nykamp, Stefan & Molderink, Albert & Hurink, Johann L. & Smit, Gerald J.M., 2012. "Statistics for PV, wind and biomass generators and their impact on distribution grid planning," Energy, Elsevier, vol. 45(1), pages 924-932.
    • Handle: RePEc:eee:energy:v:45:y:2012:i:1:p:924-932
    DOI: 10.1016/j.energy.2012.06.067
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    References listed on IDEAS

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    1. Lund, Henrik & Andersen, Anders N. & Østergaard, Poul Alberg & Mathiesen, Brian Vad & Connolly, David, 2012. "From electricity smart grids to smart energy systems – A market operation based approach and understanding," Energy, Elsevier, vol. 42(1), pages 96-102.
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    7. Pousinho, H.M.I. & Silva, H. & Mendes, V.M.F. & Collares-Pereira, M. & Pereira Cabrita, C., 2014. "Self-scheduling for energy and spinning reserve of wind/CSP plants by a MILP approach," Energy, Elsevier, vol. 78(C), pages 524-534.
    8. Ramon-Marin, Miquel & Sumper, Andreas & Villafafila-Robles, Roberto & Bergas-Jane, Joan, 2014. "Active power estimation of photovoltaic generators for distribution network planning based on correlation models," Energy, Elsevier, vol. 64(C), pages 758-770.

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