A mean-variance portfolio optimization approach for high-renewable energy hub

Authors：Xu, Da; Bai, Ziyi^*; Jin, Xiaolong; Yang, Xiaodong; Chen, Shuangyin; Zhou, Ming

Source：Applied Energy, 2022, 325: 119888.

DOI：10.1016/j.apenergy.2022.119888

• Energy hub
• Renewable energy
• Integrated energy systems
• Strategic planning
• Energy storage

This paper proposes a high-renewable portfolio model of energy hub. In this model, geothermal-solar-wind multi -energy complementarities are fully explored based on electrolytic thermo-electrochemical effects of geothermal -to-hydrogen (GTH), which are converted, conditioned, and coupled through energy hub. The proposed high -renewable energy hub portfolio is an intractable optimization problem due to their inherent strong energy couplings and conflicted energy cost/risk. The original problem is thus characterized through the mean-variance approach to explicitly express the risk associated with the forecast uncertainties. The formulated mean-variance portfolio problem is subsequently modeled as a two-stage mixed-integer nonlinear programming (MINLP) sto-chastic programming to optimally determine appropriate energy generation, conversion, and storage candidates. Numerical studies on a community microgrid are implemented to verify the effectiveness and superiority of the proposed methodology over conventional wind-solar-battery scheme. Simulations results show that the portfolio cost can be reduced by at most 14.9% with a significantly higher operational flexibility.

• Institution
  天津大学; 华中科技大学