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Spatial Effects of Wind Generation and Its Implication for Wind Farm Investment Decisions in New Zealand

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  • Le Wen, Basil Sharp, and Erwann Sbai

Abstract

Spill-over effects on electricity nodal prices associated with increased wind generation have not been examined in the literature. To examine these effects, we use spatial econometric models to estimate the direct and indirect effects of wind generation on nodal wholesale electricity prices. Spatial econometric models allow us to provide quantitative estimates of spill-over magnitudes and statistical tests for significance. Results show negative and significant effects are associated with increases in wind penetration, and the effect is stronger during peak hours and weaker during off-peak hours. Simulation results demonstrate net savings of NZ$8 million per MW of additional wind capacity installed at the CNI2 wind site. The findings provide valuable information on the evaluation of wind farm development in terms of site location, wholesale prices, and financial feasibility. Our approach also contributes to forecasting location specific wholesale electricity prices, and provides a better understanding of the implications of locating wind sites.

Suggested Citation

  • Le Wen, Basil Sharp, and Erwann Sbai, 2020. "Spatial Effects of Wind Generation and Its Implication for Wind Farm Investment Decisions in New Zealand," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 47-72.
  • Handle: RePEc:aen:journl:ej41-2-wen
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    Cited by:

    1. De Siano, Rita & Sapio, Alessandro, 2022. "Spatial merit order effects of renewables in the Italian power exchange," Energy Economics, Elsevier, vol. 108(C).
    2. Suomalainen, Kiti & Wen, Le & Sheng, Mingyue Selena & Sharp, Basil, 2022. "Climate change impact on the cost of decarbonisation in a hydro-based power system," Energy, Elsevier, vol. 246(C).
    3. Yang Yi & Le Wen & Shan He, 2022. "Partitioning for “Common but Differentiated” Precise Air Pollution Governance: A Combined Machine Learning and Spatial Econometric Approach," Energies, MDPI, vol. 15(9), pages 1-23, May.
    4. Wen, Le & Sheng, Mingyue Selena & Sharp, Basil & Meng, Tongyu & Du, Bo & Yi, Ming & Suomalainen, Kiti & Gkritza, Konstantina, 2023. "Exploration of the nexus between solar potential and electric vehicle uptake: A case study of Auckland, New Zealand," Energy Policy, Elsevier, vol. 173(C).
    5. Wen, Le & Guang, Fengtao & Sharp, Basil, 2021. "Dynamics in Aotearoa New Zealand’s energy consumption between 2006/2007 and 2012/2013," Energy, Elsevier, vol. 225(C).
    6. Guang, Fengtao & Wen, Le & Sharp, Basil, 2022. "Energy efficiency improvements and industry transition: An analysis of China's electricity consumption," Energy, Elsevier, vol. 244(PA).
    7. Wen, Le & Suomalainen, Kiti & Sharp, Basil & Yi, Ming & Sheng, Mingyue Selena, 2022. "Impact of wind-hydro dynamics on electricity price: A seasonal spatial econometric analysis," Energy, Elsevier, vol. 238(PC).
    8. Yi, Ming & Liu, Yafen & Sheng, Mingyue Selena & Wen, Le, 2022. "Effects of digital economy on carbon emission reduction: New evidence from China," Energy Policy, Elsevier, vol. 171(C).

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    JEL classification:

    • F0 - International Economics - - General

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