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Decision making for sustainable aggregation of clean energy in day-ahead market: Uncertainty and risk

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  • Gomes, I.L.R.
  • Melicio, R.
  • Mendes, V.M.F.
  • Pousinho, H.M.I.

Abstract

This paper addresses a strategy for decision-making of sustainable aggregation for clean energy participating in a day-ahead electricity market. The clean energy consists of wind turbines, photovoltaic arrays and energy storage, contributing to a better resilience of the system. The power delivered by a wind turbine or by a photovoltaic array is most certainly in deviation from the value associated with the bid accepted at a closing of a day-ahead electricity market. The deviation is due to the unpredicted variable nature of the respective sources of energy, leading to uncertainty and may imply a risk of loss of profit. So, uncertainty must be considered, and the addressed strategy considers uncertainty by scenarios of historical data and risk by the conditional value at risk. The strategy is a unified approach based on a risk-constrained and a two-stage stochastic optimization problem rewritten as a mixed-integer linear programming problem. A case study is presented to illustrate the main result and drive conclusions.

Suggested Citation

  • Gomes, I.L.R. & Melicio, R. & Mendes, V.M.F. & Pousinho, H.M.I., 2019. "Decision making for sustainable aggregation of clean energy in day-ahead market: Uncertainty and risk," Renewable Energy, Elsevier, vol. 133(C), pages 692-702.
    • Handle: RePEc:eee:renene:v:133:y:2019:i:c:p:692-702
    DOI: 10.1016/j.renene.2018.10.054
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    References listed on IDEAS

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    9. Yao, Can-Zhong & Mo, Yi-Na & Zhang, Ze-Kun, 2021. "A study of the efficiency of the Chinese clean energy stock market and its correlation with the crude oil market based on an asymmetric multifractal scaling behavior analysis," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
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