一种改进轻鲁棒优化模型及其线性对应式

发布时间：2018-04-25 07:02

本文选题：鲁棒优化 + 轻鲁棒优化　；参考：《中国电机工程学报》2016年13期

【摘要】：轻鲁棒优化模型是改善鲁棒优化模型保守性的一种方法,但该模型还存在无法独立求解、计算量较大、不能保证保守性一定改善、约束可能过度违背、不适于对右侧不确定问题进行建模等缺点。针对上述问题,提出一种适用于右侧不确定问题的改进轻鲁棒优化(improved light robust,ILR)模型,并以命题的形式证明了其在保守性改善方面的有效性;然后基于排序截断法,进一步推导出ILR模型在预算不确定集下的线性对应式,并以命题的形式证明线性对应式与原鲁棒约束的等价性;该线性对应式因保持了模型的线性特点,而可直接采用线性方法进行求解,相应提高了求解效率。算例证明了所提方法的有效性。该文研究工作促进了鲁棒优化理论的发展,并为电力系统机组组合等实际优化问题的进一步研究及发展奠定了理论基础。
[Abstract]:The light robust optimization model is a method to improve the conservatism of the robust optimization model. However, the model can not be solved independently and has a large amount of computation, which can not guarantee the conservatism to be improved, and the constraints may be violated excessively. Is not suitable for the right side of the uncertain problem modeling and other shortcomings. In order to solve the above problems, an improved lightweight robust optimal light robust ILR model is proposed for the right uncertain problems, and its effectiveness in conservative improvement is proved in the form of propositions, and then based on the ranking truncation method, Furthermore, the linear correspondence of ILR model under the uncertain set of budget is deduced, and the equivalence between the linear correspondence and the original robust constraint is proved in the form of propositions, and the linear correspondence factor preserves the linear characteristic of the model. The linear method can be directly used to solve the problem, and the efficiency of the solution can be improved accordingly. An example is given to show the effectiveness of the proposed method. The research work in this paper promotes the development of robust optimization theory and lays a theoretical foundation for the further research and development of practical optimization problems such as power system unit commitment.
【作者单位】：智能电网教育部重点实验室(天津大学);同济大学电子与信息工程学院;中国电力科学研究院;国网天津市电力公司;
【分类号】：TM73

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