Grid-connected wind power capacity optimization based on the principle of maximum entropy

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

Abstract

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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基于最大熵原理的并网风电容量优化
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。
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