基于最大熵原理的并网风电容量优化

Qiaoyan Bian, Qian Xu, Liying Sun, Leiqi Zhang, Hao Wu, H. Xin
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引用次数: 3

摘要

针对可再生资源的不确定性对传统电力系统运行和规划的挑战,本文引入信息理论,寻找不确定因素最可能实现的概率分布——“最佳”分布场景。基于最大熵原理,建立了风电容量优化问题的机会约束模型。考虑了电网极限约束和设备运行边界约束。通过IEEE案例30的数值研究,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Grid-connected wind power capacity optimization based on the principle of maximum entropy
As the uncertain renewable resources challenge the conventional power system operations and planning, in this paper, information theory is introduced to find the most possibly realized probability distribution - the `best' distribution scenario, of the uncertain factors. A chance-constrained model is then formulated based on the maximum entropy principle for the wind power capacity optimization problem. The constraints of power network limit and equipment operation bounds are considered. A numerical study of IEEE case 30 is used to demonstrate the effectiveness of the proposed method.
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