The economic cost of power outages has been estimated to be between \$35 billion and \$50 billion annually in the United States. We analyze and advance methodologies for electrical distribution network reconfiguration in order to quickly restore power, an important lever for improving reliability. For short-term network disruptions, we give a novel model for reconfiguration by considering switches that can be sequentially closed upon detection of a network anomaly upstream. The order in which switches close has an impact on reliability metrics such as SAIDI, which are the basis for regulator-imposed financial performance incentives. We introduce the Minimum Reconnection Time (MRT) problem of finding an optimal switch ordering that minimizes the cost of outages and show that it generalizes metrics like SAIDI. We first show that MRT is a special case of the well-known minimum linear ordering problem from submodular optimization literature and that MRT is also NP-hard. We show how to approximate MRT using recent kernel-based randomized rounding approaches, and in turn improve the state-of-the-art for a broad class of MLOP instances. Finally, we note that the choice of reliability metric can result in significant differences for low and medium voltage buses. We therefore consider optimizing multiple metrics simultaneously using local search methods that reconfigure the system's base tree to optimize service disruptions, reconnection times, and energy losses. We computationally validate our reconfiguration methods on the NREL SMART-DS Greensboro synthetic urban-suburban network and show significant improvement in reliability metrics.
翻译:据估计,美国每年断电的经济成本在350亿至500亿美元之间。我们分析并推进电力分销网络重组的方法,以便迅速恢复电力,这是提高可靠性的重要杠杆。短期网络中断,我们给出了一种新的重组模式,即考虑在发现网络异常时可以按顺序关闭的开关,在发现网络异常上游时可以按顺序关闭。关闭的顺序对可靠性衡量标准产生了影响,如SADIDI,这是监管者实施金融绩效激励的基础。我们引入了最低再连接时间(MRT)问题,即找到最佳开关,以尽可能降低断电成本,并显示它普遍采用像SADI这样的标准。我们首先显示,MRT是已知的最低线性订购问题的特殊例子,在检测到网络异常异常时,MRT是如何使用基于内核的随机四舍方法来接近MRTT,而反过来则是改善低级的状态。最后,我们指出,在进行绿色再连接时,我们采用中值的智能智能智能智能智能的服务器系统可以同时显示我们内部的智能的智能智能智能智能的智能和智能的智能的智能的智能系统。