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Wind Integration into Various Generation Mixtures

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  • Maddaloni, Jesse D.
  • Rowe, Andrew M.
  • van Kooten, G. Cornelis

Abstract

A load balance model is used to quantify the economic and environmental effects of integrating wind power into three typical generation mixtures. System operating costs over a specified period are minimized by controlling the operating schedule of existing power generating facilities for a range of wind penetrations. Unlike other studies, variable generator efficiencies, and thus variable fuel costs, are taken into account, as are the ramping constraints on thermal generators. Results indicate that system operating cost will increase by 15% to 110% (pending generation mixture) at a wind penetration of 100% of peak demand. Results also show that some mixtures will exhibit cost reductions on the order of 13% for moderate wind penetrations and high wind farm capacity factors. System emissions also decrease by 13% to 32% (depending on generation mixture) at a wind penetration of 100%. This leads to emission abatement costs in the range of $65 per tonne-CO2e for coal dominated mixtures, but $450 per tonne-CO2e for hydro dominated mixtures. For natural gas dominated mixtures, the introduction of wind power may well be beneficial overall.

Suggested Citation

  • Maddaloni, Jesse D. & Rowe, Andrew M. & van Kooten, G. Cornelis, 2007. "Wind Integration into Various Generation Mixtures," Working Papers 37044, University of Victoria, Resource Economics and Policy.
  • Handle: RePEc:ags:uvicwp:37044
    DOI: 10.22004/ag.econ.37044
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    Cited by:

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    5. van Kooten, G. Cornelis & Timilsina, Govinda R., 2009. "Wind power development : economics and policies," Policy Research Working Paper Series 4868, The World Bank.
    6. De Jonghe, Cedric & Delarue, Erik & Belmans, Ronnie & D'haeseleer, William, 2011. "Determining optimal electricity technology mix with high level of wind power penetration," Applied Energy, Elsevier, vol. 88(6), pages 2231-2238, June.
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    8. Simla, Tomasz & Stanek, Wojciech, 2020. "Influence of the wind energy sector on thermal power plants in the Polish energy system," Renewable Energy, Elsevier, vol. 161(C), pages 928-938.
    9. Gerber, Annelies & Qadrdan, Meysam & Chaudry, Modassar & Ekanayake, Janaka & Jenkins, Nick, 2012. "A 2020 GB transmission network study using dispersed wind farm power output," Renewable Energy, Elsevier, vol. 37(1), pages 124-132.
    10. McPherson, Madeleine & Harvey, L.D. Danny & Karney, Bryan, 2017. "System design and operation for integrating variable renewable energy resources through a comprehensive characterization framework," Renewable Energy, Elsevier, vol. 113(C), pages 1019-1032.
    11. Lion Hirth, 2013. "The Market Value of Variable Renewables. The Effect of Solar and Wind Power Variability on their Relative Price," RSCAS Working Papers 2013/36, European University Institute.
    12. G. Cornelis van Kooten & Govinda R. Timilsina, 2008. "Wind Power Development: Opportunities and Challenges," Working Papers 2008-13, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    13. De Jonghe, C. & Hobbs, B. F. & Belmans, R., 2011. "Integrating short-term demand response into long-term investment planning," Cambridge Working Papers in Economics 1132, Faculty of Economics, University of Cambridge.
    14. Lund, Peter D. & Lindgren, Juuso & Mikkola, Jani & Salpakari, Jyri, 2015. "Review of energy system flexibility measures to enable high levels of variable renewable electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 785-807.
    15. Qadrdan, Meysam & Chaudry, Modassar & Wu, Jianzhong & Jenkins, Nick & Ekanayake, Janaka, 2010. "Impact of a large penetration of wind generation on the GB gas network," Energy Policy, Elsevier, vol. 38(10), pages 5684-5695, October.
    16. Simoglou, Christos K. & Bakirtzis, Emmanouil A. & Biskas, Pandelis N. & Bakirtzis, Anastasios G., 2016. "Optimal operation of insular electricity grids under high RES penetration," Renewable Energy, Elsevier, vol. 86(C), pages 1308-1316.
    17. Kuo, Cheng-Chien, 2010. "Wind energy dispatch considering environmental and economic factors," Renewable Energy, Elsevier, vol. 35(10), pages 2217-2227.
    18. Simoglou, Christos K. & Biskas, Pandelis N. & Vagropoulos, Stylianos I. & Bakirtzis, Anastasios G., 2014. "Electricity market models and RES integration: The Greek case," Energy Policy, Elsevier, vol. 67(C), pages 531-542.
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    20. Hart, Elaine K. & Jacobson, Mark Z., 2011. "A Monte Carlo approach to generator portfolio planning and carbon emissions assessments of systems with large penetrations of variable renewables," Renewable Energy, Elsevier, vol. 36(8), pages 2278-2286.
    21. Xu, M. & Zhuan, X., 2013. "Optimal planning for wind power capacity in an electric power system," Renewable Energy, Elsevier, vol. 53(C), pages 280-286.

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    More about this item

    Keywords

    Environmental Economics and Policy; Resource /Energy Economics and Policy;

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General

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