基于拉丁超立方采样的含风电电力系统的概率可靠性评估

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摘要基于随机抽样的蒙特卡罗方法（MC_RS）由于原理简单、易于实现,常用于电力系统的可靠性评估,但在大规模风电接入,特别是以单个小容量的机组接入的情况下会存在样本容量大、效率低等不足。因此提出使用基于拉丁超立方采样的蒙特卡罗（MC_LHS）方法来解决含风电的电力系统概率可靠性评估问题,此方法由于使用了拉丁超立方采样,能有效地改善样本值对输入随机变量的分布空间的覆盖程度和使用Cholesky分解来降低输入变量之间的相关性系数,从而提高了采样效率、增加收敛速度和提高评估准确度。把提出的MC_LHS方法应用到改进IEEE-RTS79算例中,并与常规MC_RS进行比较,结果验证了该方法的有效性。

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关键词 ：概率可靠性评估, 电力系统, 拉丁超立方采样, 风电, Cholesky分解

Abstract：The reliability of power system is often evaluated through Monte-Carlo (MC) simulation with random sampling, namely MC_RS. But it is inappropriate for the power system with large scale wind power integration, because the sample size is large and the assessment efficiency is low. This paper proposes an improved assessment method by MC_LHS, combined the traditional MC method with LHS (Latin hypercube sampling) method, to improve the coverage of sample values for input spaces of random variables and increase the sampling efficiency. Consequently the integrated assessment method could improve the assessment efficiency and stability, as well as reduce the correlation coefficients of repeated assessment results. The analysis of improved IEEE-RTS 79 reliability test system shows that the proposed assessment method is effective.

Key words： Probabilistic reliability assessment power system Latin hypercube sampling wind power Cholesky decomposition

收稿日期: 2015-04-17 出版日期: 2016-07-11

PACS:

TM712

基金资助:国家高技术研究发展计划（863计划）资助项目（2012AA050201）

通讯作者: 蒋程男,1986年生,博士研究生,研究方向为电力系统分析与控制,电力系统安全和可靠性分析。E-mail: jc_2002@163.com（通信作者）

作者简介: 王硕男,1980年生,高级工程师,研究方向为电力系统分析与控制、风险评估和应急管理。E-mail: 188077394@qq.com

引用本文:

蒋程, 王硕, 王宝庆, 张建华, 赵天阳. 基于拉丁超立方采样的含风电电力系统的概率可靠性评估[J]. 电工技术学报, 2016, 31(10): 193-206. Jiang Cheng, Wang Shuo, Wang Baoqing, Zhang Jianhua, Zhao Tianyang. Probabilistic Reliability Assessment of Power System Containing Wind Power Based on Latin Hypercube Sampling. Transactions of China Electrotechnical Society, 2016, 31(10): 193-206.

链接本文:

https://dgjsxb.ces-transaction.com/CN/Y2016/V31/I10/193

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