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A Wasserstein metric-based distributionally robust optimization approach for reliable-economic equilibrium operation of hydro-wind-solar energy systems

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  • Jin, Xiaoyu
  • Liu, Benxi
  • Liao, Shengli
  • Cheng, Chuntian
  • Yan, Zhiyu

Abstract

Hydro-wind-solar integrated operation is a promising way to balance the growing amount of variable renewable energy (RE) and enhance energy utilization efficiency. This study focuses on the short-term reliable-economic equilibrium operation of the hydro-wind-solar energy systems. A Distributionally Robust Optimization based on Wasserstein metric, which considers multiple power supply risks (output shortage, power curtailment and spilled water) and the economy (the water consumption and the stored energy) of hydropower operation simultaneously is proposed to address the above issue. The model is transformed into a mixed-integer linear programming framework using a reformation approach based on ϵ-constraint method, strong duality theory, and linearization technology. Case studies are conducted for a hydro-wind-solar energy system in Southwest China's Beipan River basin. Results indicate that: (1) with more available data, more information about RE uncertainties is involved in the decision-making process to hedge against RE variability's interference. (2) Decisions obtained from the proposed model overcome the issues of stochastic optimization's over-optimism and robust optimization's over-conservativeness. (3) Reliable-economic trade-off mechanisms are derived by imposing a decision-maker's risk attitude, the risks in dry and wet season typical cases decline from 10483.05 MW to 1606.39 MW and from 8394.15 MW to 118.08 MW by adjusting the economy.

Suggested Citation

  • Jin, Xiaoyu & Liu, Benxi & Liao, Shengli & Cheng, Chuntian & Yan, Zhiyu, 2022. "A Wasserstein metric-based distributionally robust optimization approach for reliable-economic equilibrium operation of hydro-wind-solar energy systems," Renewable Energy, Elsevier, vol. 196(C), pages 204-219.
    • Handle: RePEc:eee:renene:v:196:y:2022:i:c:p:204-219
    DOI: 10.1016/j.renene.2022.06.118
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