风电不确定性下基于仿射算法的最优电-气流动凸优化方法

Xianghao Zheng, Feixiong Chen, Yixin Guo, Jianming Wang, Chunlin Jiang, Zhenguo Shao
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引用次数: 0

摘要

随着风电发展的突飞猛进,风电的不确定性给电-气一体化系统的运行规划带来了巨大的挑战。提出了一种考虑风电不确定性的基于仿射算法的最优电-气流量求解方法。在凸包络的基础上,建立了不需要非仿射操作的基于aa的OPGF模型。采用仿射形式对不确定风电进行处理,跟踪不确定变量之间的关系。通过引入AA理论,将基于AA的OPGF模型转化为确定性多目标问题。在此基础上,采用一种收紧凸包络算法来提高基于aa的OPGF求解的可行性。数值结果表明,该方法与蒙特卡罗方法相比是有效的。此外,还揭示了不确定因素的传播轨迹。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Convex Optimization Method for Affine Arithmetic-based Optimal Power-Gas Flow under Wind Power Uncertainty
As wind power develops by leaps and bounds, its uncertainty has posed huge challenges for operational planning for integrated electricity-gas system (IEGS). An approach based on affine arithmetic (AA) for optimal power-gas flow (OPGF) considering uncertainty of wind power is proposed. Based on convex envelope, AA-based OPGF model is developed without non-affine operations. Uncertain wind power is treated by affine form keeping track of relationships between uncertain variables. By introducing AA theory, AA-based OPGF model can be converted into deterministic multi-objective problem. Then a tightening convex envelope algorithm is employed to enhance solution feasibility of AA-based OPGF. Numerical results demonstrate the effectiveness of the proposed AA-based method compared with Monte Carlo method. In addition, the transmission tracks of uncertain factors are also revealed.
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