使用非线性规划和置信区间的最大载荷问题

A. Schellenberg, W. Rosehart, J. Aguado
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引用次数: 2

摘要

本文提出了一个具有置信区间约束的随机非线性规划。该问题将传统的最大负荷问题扩展到包括系统负荷水平的随机性和不确定性。该问题将负荷水平的99%置信区间限制在预先指定的平均值范围内。本文给出了当置信区间被限制在平均值的15%、20%和25%以内时的解决方案。采用IEEE 30总线系统对所提出的解决方法进行了测试,并将结果与使用蒙特卡罗模拟得到的解决方案进行了比较。每个蒙特卡罗模拟由10,000个样本组成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Maximum loading problems using nonlinear programming and confidence intervals
This paper presents a stochastic non-linear program (S-NLP) with a confidence interval constraint. The problem extends the conventional maximum loading problem to include randomness and uncertainty in system loading levels. The problem restricts the 99% confidence interval of the loading level to be within a pre-specified amount of the mean. The paper presents solutions when the confidence interval is restricted to be within 15, 20, and 25% of the mean. The proposed solution methodology is tested using the IEEE 30 bus system and results are compared against solutions found using Monte Carlo simulations. Each of the Monte Carlo simulations consist of 10,000 samples.
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