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A distributionally robust bidding strategy for a wind power plant

机译:风力发电场的分布式鲁棒招标策略

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This paper presents a two-stage distributionally robust model to derive optimal bidding strategies for an aggregated wind power plant (WPP), that participates as a price-maker in the day-ahead market, and a deviator in the balancing market. The market power is realized by using a bi-level model, which is then transformed into a mixed-integer linear programming model using the Karush-Kuhn-Tucker (KKT) optimality conditions and strong duality theory. The uncertainty in wind generation output is characterized by an ambiguity set that defines a family of distributions. The optimal decision is robust to the expectation over the worst-case distribution. With a case study based on a modified Swiss system, we verify the effectiveness of the proposed distributionally robust optimization model and compare its performance to that of robust and stochastic optimization models.
机译:本文提出了一个两阶段的分布稳健模型,以得出集合风电厂(WPP)的最优竞标策略,该电厂作为价格制定者参与日前市场,而作为偏离者参与平衡市场。通过使用双层模型来实现市场支配力,然后使用Karush-Kuhn-Tucker(KKT)最优条件和强对偶理论将其转换为混合整数线性规划模型。风力发电输出的不确定性以定义一组分布的模糊集为特征。最佳决策对于最坏情况下的分布具有鲁棒性。通过基于修改后的瑞士系统的案例研究,我们验证了所提出的分布式鲁棒优化模型的有效性,并将其性能与鲁棒和随机优化模型进行了比较。

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