【摘要】 【目的】为应对风电消纳不足以及燃煤自备电厂高能耗、高污染问题，进行风电与自备电厂发电权交易是一种可行的方案。目前针对风电与自备电厂发电权交易的研究较多，但缺乏对多时间尺度下不确定性进行精细化建模的决策行为研究。为此，提出了一种基于多时间尺度耦合的风电场与自备电厂的发电权交易方法。【方法】首先，分析各市场主体参与发电权交易前后的成本与收益，计算发电权交易的利润空间。其次，基于多时间尺度弃风预测，利用Copula函数计算实际弃风量的条件概率密度分布模型，进而分析风电场在多时间尺度下的决策行为并开展发电权交易。最后，以某省份运行数据进行算例仿真验证方法的合理性。【结果】多时间尺度耦合发电权交易模型相较于传统发电权交易模型，其风电消纳量提高了3.7%，经济效益提高了3.3%。【结论】所提多时间尺度耦合模型相较传统发电权交易能够有效促进风电消纳，同时进一步发掘潜在利润空间，最大化发电权交易的总社会效益。更多还原

【Abstract】 [Objective] To address the issues of insufficient wind power integration and the high energy consumption and pollution associated with coal-fired captive power plants, conducting generation rights trading between wind power and captive power plants represents a feasible solution. Although extensive research exists on generation rights trading involving wind power and captive power plants, studies on decision-making behavior that involves refined modeling of uncertainties across multiple time scales remain limited. To bridge this gap, this paper proposes a generation rights trading method for wind farms and captive power plants based on multi-time-scale coupling. [Methods] First, the costs and benefits of each market entity before and after participating in generation rights trading are analyzed to calculate the profit margin of such trading. Second, based on multi-time-scale wind curtailment forecasts, the Copula function is used to compute the conditional probability density distribution model of actual wind curtailment. This enables an analysis of the decision-making behavior of wind farms under multi-time-scale conditions and facilitates the implementation of generation rights trading. Finally, operational data from a provincial power system are used in a case study to validate the rationality of the proposed method.[Results] Compared with the traditional generation rights trading model, the multi-time-scale coupled generation rights trading model increases wind power integration by 3. 7% and improves economic benefits by 3. 3%. [Conclusions] The proposed multi-time-scale coupling model promotes wind power integration more effectively than traditional generation rights trading, while further exploring potential profit margins and maximizing the overall social benefits of generation rights trading.更多还原