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Robust Risk-Constrained Unit Commitment with Large-scale Wind Generation: An Adjustable Uncertainty Set Approach

机译:具有大风的稳健风险约束单位承诺   生成:一种可调整的不确定性集方法

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摘要

This paper addresses two vital issues which are barely discussed in theliterature on robust unit commitment (RUC): 1) how much the potentialoperational loss could be if the realization of uncertainty is beyond theprescribed uncertainty set; 2) how large the prescribed uncertainty set shouldbe when it is used for RUC decision making. In this regard, a robustrisk-constrained unit commitment (RRUC) formulation is proposed to cope withlarge-scale volatile and uncertain wind generation. Differing from existing RUCformulations, the wind generation uncertainty set in RRUC is adjustable viachoosing diverse levels of operational risk. By optimizing the uncertainty set,RRUC can allocate operational flexibility of power systems over spatial andtemporal domains optimally, reducing operational cost in a risk-constrainedmanner. Moreover, since impact of wind generation realization out of theprescribed uncertainty set on operational risk is taken into account, RRUCoutperforms RUC in the case of rare events. Three algorithms based on columnand constraint generation (C&CG) are derived to solve the RRUC. As the proposedalgorithms are quite general, they can also apply to other RUC models toimprove their computational efficiency. Simulations on a modified IEEE 118-bussystem demonstrate the effectiveness and efficiency of the proposed methodology
机译:本文针对两个至关重要的问题,在文献中关于鲁棒的单位承诺(RUC)几乎没有讨论:1)如果不确定性的实现超出了规定的不确定性集,那么潜在的运营损失将是多少? 2)当用于RUC决策时,规定的不确定性集应有多大。在这方面,提出了一种鲁棒的风险约束单位承诺(RRUC)公式,以应对大规模的动荡和不确定的风力发电。与现有的RUC公式不同,在RRUC中设置​​的风力发电不确定性可以通过选择各种运行风险级别进行调整。通过优化不确定性集,RRUC可以在时空范围内优化分配电力系统的运营灵活性,从而降低了风险受限的运营成本。此外,由于考虑了风力发电超出规定的不确定性设置对运行风险的影响,因此在罕见事件中,RRUC优于RUC。推导了基于列和约束生成(C&CG)的三种算法来求解RRUC。由于所提出的算法相当笼统,因此它们也可以应用于其他RUC模型以提高其计算效率。在改进的IEEE 118总线系统上进行的仿真证明了所提出方法的有效性和效率

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