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Power system impacts of community acceptance policies for renewable energy deployment under storage cost uncertainty

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  • Fitiwi, Desta Z.
  • Lynch, Muireann
  • Bertsch, Valentin

Abstract

Community opposition has caused delays in renewable energy investments. The literature suggests that increasing setback distances, decreasing scale and increasing self-sufficiency among others may increase community acceptance of energy infrastructures. We perform an analysis of the evolution of the Irish power system under these policies by constraining the maximum onshore renewable generation installation at each transmission node, accounting for network and spatial effects. We also consider the impacts of uncertainty in storage costs. An unconstrained renewable development portfolio is marginally cheaper than a constrained one. However, there are substantial differences in the final generation expansion portfolios and spatial allocations. The network reinforcement requirements are also greater under the unconstrained approach. Lower storage costs only slightly mitigate the costs of capacity constraints but significantly alter the spatial distribution of generation investments. The differential in costs between the unconstrained and constrained cases increases non-linearly with renewable generation targets. Future work will consider transmission as well as generation investments.

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  • Fitiwi, Desta Z. & Lynch, Muireann & Bertsch, Valentin, 2020. "Power system impacts of community acceptance policies for renewable energy deployment under storage cost uncertainty," Renewable Energy, Elsevier, vol. 156(C), pages 893-912.
  • Handle: RePEc:eee:renene:v:156:y:2020:i:c:p:893-912
    DOI: 10.1016/j.renene.2020.03.110
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    2. Finke, Jonas & Bertsch, Valentin, 2022. "Implementing a highly adaptable method for the multi-objective optimisation of energy systems," MPRA Paper 115504, University Library of Munich, Germany.
    3. Tabar, Vahid Sohrabi & Banazadeh, Hamidreza & Tostado-Véliz, Marcos & Jordehi, Ahmad Rezaee & Nasir, Mohammad & Jurado, Francisco, 2022. "Stochastic multi-stage multi-objective expansion of renewable resources and electrical energy storage units in distribution systems considering crypto-currency miners and responsive loads," Renewable Energy, Elsevier, vol. 198(C), pages 1131-1147.
    4. Lynch, Muireann Á. & Longoria, Genora & Curtis, John, 2021. "Future market design options for electricity markets with high RES-E: lessons from the Irish Single Electricity Market," Papers WP702, Economic and Social Research Institute (ESRI).
    5. Li, Jianling & Zhao, Ziwen & Xu, Dan & Li, Peiquan & Liu, Yong & Mahmud, Md Apel & Chen, Diyi, 2023. "The potential assessment of pump hydro energy storage to reduce renewable curtailment and CO2 emissions in Northwest China," Renewable Energy, Elsevier, vol. 212(C), pages 82-96.
    6. Finke, Jonas & Bertsch, Valentin, 2023. "Implementing a highly adaptable method for the multi-objective optimisation of energy systems," Applied Energy, Elsevier, vol. 332(C).
    7. Fitiwi, Desta Z. & Lynch, Muireann & Bertsch, Valentin, 2020. "Enhanced network effects and stochastic modelling in generation expansion planning: Insights from an insular power system," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    8. Gaur, Ankita Singh & Fitiwi, Desta Z. & Lynch, Muireann & Longoria, Genaro, 2022. "Implications of heating sector electrification on the Irish power system in view of the Climate Action Plan," Energy Policy, Elsevier, vol. 168(C).
    9. Lynch, Muireann & Longoria, Genaro & Curtis, John, 2021. "Market design options for electricity markets with high variable renewable generation," Utilities Policy, Elsevier, vol. 73(C).
    10. David Huckebrink & Valentin Bertsch, 2021. "Integrating Behavioural Aspects in Energy System Modelling—A Review," Energies, MDPI, vol. 14(15), pages 1-26, July.
    11. Bertsch, Valentin & Di Cosmo, Valeria, 2020. "Are renewables profitable in 2030 and do they reduce carbon emissions effectively? A comparison across Europe," MPRA Paper 101822, University Library of Munich, Germany.

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