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Optimizing transmission from distant wind farms


  • Pattanariyankool, Sompop
  • Lave, Lester B.


We explore the optimal size of the transmission line from distant wind farms, modeling the tradeoff between transmission cost and benefit from delivered wind power. We also examine the benefit of connecting a second wind farm, requiring additional transmission, in order to increase output smoothness. Since a wind farm has a low capacity factor, the transmission line would not be heavily loaded, on average; depending on the time profile of generation, for wind farms with capacity factor of 29-34%, profit is maximized for a line that is about 3/4 of the nameplate capacity of the wind farm. Although wind generation is inexpensive at a good site, transmitting wind power over 1600Â km (about the distance from Wyoming to Los Angeles) doubles the delivered cost of power. As the price for power rises, the optimal capacity of transmission increases. Connecting wind farms lowers delivered cost when the wind farms are close, despite the high correlation of output over time. Imposing a penalty for failing to deliver minimum contracted supply leads to connecting more distant wind farms.

Suggested Citation

  • Pattanariyankool, Sompop & Lave, Lester B., 2010. "Optimizing transmission from distant wind farms," Energy Policy, Elsevier, vol. 38(6), pages 2806-2815, June.
  • Handle: RePEc:eee:enepol:v:38:y:2010:i:6:p:2806-2815

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    References listed on IDEAS

    1. Denholm, Paul & Sioshansi, Ramteen, 2009. "The value of compressed air energy storage with wind in transmission-constrained electric power systems," Energy Policy, Elsevier, vol. 37(8), pages 3149-3158, August.
    2. Baldick, Ross & Kahn, Edward, 1993. "Network Costs and the Regulation of Wholesale Competition in Electric Power," Journal of Regulatory Economics, Springer, vol. 5(4), pages 367-384, December.
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    Cited by:

    1. Fallahi, Farhad & Nick, Mostafa & Riahy, Gholam H. & Hosseinian, Seyed Hossein & Doroudi, Aref, 2014. "The value of energy storage in optimal non-firm wind capacity connection to power systems," Renewable Energy, Elsevier, vol. 64(C), pages 34-42.
    2. Shropshire, David & Purvins, Arturs & Papaioannou, Ioulia & Maschio, Isabella, 2012. "Benefits and cost implications from integrating small flexible nuclear reactors with off-shore wind farms in a virtual power plant," Energy Policy, Elsevier, vol. 46(C), pages 558-573.
    3. Osmani, Atif & Zhang, Jun, 2014. "Optimal grid design and logistic planning for wind and biomass based renewable electricity supply chains under uncertainties," Energy, Elsevier, vol. 70(C), pages 514-528.
    4. Fertig, Emily & Apt, Jay, 2011. "Economics of compressed air energy storage to integrate wind power: A case study in ERCOT," Energy Policy, Elsevier, vol. 39(5), pages 2330-2342, May.
    5. Waite, Michael & Modi, Vijay, 2016. "Modeling wind power curtailment with increased capacity in a regional electricity grid supplying a dense urban demand," Applied Energy, Elsevier, vol. 183(C), pages 299-317.
    6. Lamy, Julian & Azevedo, Inês L. & Jaramillo, Paulina, 2014. "The role of energy storage in accessing remote wind resources in the Midwest," Energy Policy, Elsevier, vol. 68(C), pages 123-131.
    7. José F. Herbert-Acero & Oliver Probst & Pierre-Elouan Réthoré & Gunner Chr. Larsen & Krystel K. Castillo-Villar, 2014. "A Review of Methodological Approaches for the Design and Optimization of Wind Farms," Energies, MDPI, Open Access Journal, vol. 7(11), pages 1-87, October.
    8. repec:eee:appene:v:217:y:2018:i:c:p:178-188 is not listed on IDEAS


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