| 引用本文: | 黄煜,徐青山,卞海红,刘建坤.基于拉丁超立方采样技术的半不变量法随机潮流计算[J].电力自动化设备,2016,36(11): |
| HUANG Yu,XU Qingshan,BIAN Haihong,LIU Jiankun.Cumulant method based on Latin hypercube sampling for calculating probabilistic power flow[J].Electric Power Automation Equipment,2016,36(11): |
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| 摘要: |
| 新能源发电的兴起加剧了电力系统运行中的不确定性和关联性，传统潮流计算方法无法适应新环境下电网分析和评估的要求。提出一种可考虑输入变量相关性的基于拉丁超立方采样技术的半不变量法随机潮流计算方法。该算法综合了模拟法精度高、适用性广和半不变量法计算速度快的优点，采用分段线性化潮流模型减小截断误差，并通过Cholesky分解解决了半不变量法只能处理独立变量的难题。对IEEE 30和IEEE 118节点系统的测试验证了所提方法的准确性、快速性和实用性。 |
| 关键词: 拉丁超立方采样 相关性 半不变量法 分段线性化 Cholesky分解 随机潮流 |
| DOI：10.16081/j.issn.1006-6047.2016.11.017 |
| 分类号:TM732 |
| 基金项目:国家自然科学基金资助项目(51377021)；国网公司科技项目(新能源发电预测误差对电网安全运行影响评价方法研究) |
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| Cumulant method based on Latin hypercube sampling for calculating probabilistic power flow |
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HUANG Yu1, XU Qingshan1, BIAN Haihong2, LIU Jiankun3
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1.School of Electrical Engineering, Southeast University, Nanjing 210096, China;2.School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China;3.Jiangsu Electric Power Research Institute, Nanjing 210003, China
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| Abstract: |
| As the development of new-energy power generation increases the operational uncertainty and correlation of power system, the traditional power flow calculation algorithm could not meet the requirements of power grid analysis and evaluation in this environment. A probabilistic power flow calculation algorithm is proposed, which applies the cumulant method based on Latin hypercube sampling to consider the correlation between input variables. It combines the high precision and wide applicability of analog method with the high speed of cumulant method, adopts the multi-linearized power flow model to reduce the truncation error, and applies Cholesky decomposition to solve the problem that the cumulant method can only deal with the independent variables. The simulative results of IEEE 30-bus system and IEEE 118-bus system verify the accuracy, rapidity and practicability of the proposed algorithm. |
| Key words: Latin hypercube sampling correlation cumulant method multi-linearization Cholesky decomposition probabilistic power flow |
