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故障关联矩阵下弹性配电网可靠性评估

Reliability assessment of elastic distribution network based on fault correlation matrix
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摘要 配电网弹性是指系统受到干扰后恢复原有状态的能力,而自然灾害的频发要求配电网不仅在正常条件下能够可靠运行,而且还能够在极端灾害出现时保持必要能力。据此,提出一种基于故障关联矩阵(fault incidence matrix,FIM)的弹性配电网可靠性评价方法。通过建立FIM,使用简化的矩阵代数、布尔运算即可实现配电系统可靠性、弹性和供电能力的显式解析计算,避免了评估过程中故障枚举的重复性搜索工作,节省了计算时间,并且可适用于结构复杂的配电网,易于扩展。最后结果表明:采用文中方法的计算时间仅为约0.055 s,相较于故障扩散算法和分块算法分别减少87%和75%的时间。 The elasticity of the distribution network indicates the ability of the system to restore its original state after interference,and the frequent occurrence of natural disasters requires that the distribution network can not only operate reliably under normal conditions,and but also maintain the necessary capabilities for extreme disasters.Accordingly,a reliability evaluation method of elastic distribution network based on fault incidence matrix(FIM)was proposed in this paper.With FIM,the explicit analytical calculation of the reliability,elasticity and power supply capacity of the distribution system can be achieved by using simplified matrix algebra and Boolean operation,which saves the repetitive search work of fault enumeration in the evaluation process,and the calculation time,and can be applied to the complex structure of the distribution network and easy to expand.The final results show that the calculation time of the proposed method is only about 0.055s,which is reduced by 87%and 75%respectively compared with that of the fault diffusion algorithm and the block algorithm.
作者 李宁 胡佳乐 詹晓暄 申盼盼 姜盼勇 卓超然 LI Ning;HU Jiale;ZHAN Xiaoxuan;SHEN Panpan;JIANG Panyong;ZHUO Chaoran(School of Electrical Engineering,Xi’an University of Technology,Xi’an 710048,China;Chengdu Wenjiang Power Supply Branch of State Grid Sichuan Electric Power Company,Chengdu 611130,China;School of Electrical Engineering,Xi’an Jiaotong University,Xi’an 710049,China)
出处 《西安工程大学学报》 CAS 2024年第2期1-8,共8页 Journal of Xi’an Polytechnic University
基金 国家自然科学基金(52177193) 陕西省重点研发计划(2022GY-182) 西安市科技计划项目(22GXFW0078)。
关键词 故障关联矩阵 弹性配电网 可靠性 供电能力 fault correlation matrix(FIM) elastic distribution network reliability power supply capacity
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