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Developing an optimal electricity generation mix for the UK 2050 future

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  • Sithole, H.
  • Cockerill, T.T.
  • Hughes, K.J.
  • Ingham, D.B.
  • Ma, L.
  • Porter, R.T.J.
  • Pourkashanian, M.

Abstract

The UK electricity sector is undergoing a transition driven by domestic and regional climate change and environmental policies. Aging electricity generating infrastructure is set to affect capacity margins after 2015. These developments, coupled with the increased proportion of inflexible and variable generation technologies will impact on the security of electricity supply. Investment in low-carbon technologies is central to the UK meeting its energy policy objectives. The complexity of these challenges over the future development of the UK electricity generation sector has motivated this study which aims to develop a policy-informed optimal electricity generation scenario to assess the sector's transition to 2050. The study analyses the level of deployment of electricity generating technologies in line with the 80% by 2050 emission target. This is achieved by using an excel-based “Energy Optimisation Calculator” which captures the interaction of various inputs to produce a least-cost generation mix. The key results focus on the least-cost electricity generation portfolio, emission intensity, and total investment required to assemble a sustainable electricity generation mix. A carbon neutral electricity sector is feasible if low-carbon technologies are deployed on a large scale. This requires a robust policy framework that supports the development and deployment of mature and emerging technologies.

Suggested Citation

  • Sithole, H. & Cockerill, T.T. & Hughes, K.J. & Ingham, D.B. & Ma, L. & Porter, R.T.J. & Pourkashanian, M., 2016. "Developing an optimal electricity generation mix for the UK 2050 future," Energy, Elsevier, vol. 100(C), pages 363-373.
  • Handle: RePEc:eee:energy:v:100:y:2016:i:c:p:363-373
    DOI: 10.1016/j.energy.2016.01.077
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    15. Jean-Nicolas Louis & Stéphane Allard & Freideriki Kotrotsou & Vincent Debusschere, 2020. "A multi-objective approach to the prospective development of the European power system by 2050," Post-Print hal-02376337, HAL.
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    18. Guo, Hua & Deng, Shengxiang & Yang, Jinbiao & Liu, Jiangwei & Nie, Changda, 2020. "Analysis and prediction of industrial energy conservation in underdeveloped regions of China using a data pre-processing grey model," Energy Policy, Elsevier, vol. 139(C).
    19. Chung-Geon Lee & La-Hoon Cho & Seok-Jun Kim & Sun-Yong Park & Dae-Hyun Kim, 2022. "Prediction Model for the Internal Temperature of a Greenhouse with a Water-to-Water Heat Pump Using a Pellet Boiler as a Heat Source Using Building Energy Simulation," Energies, MDPI, vol. 15(15), pages 1-17, August.
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