配电网络中结合原始数据转换的拓扑路径识别系统化流程
A Systematic Procedure for Topological Path Identification with Raw Data Transformation in Electrical Distribution Networks
AI总结：
针对配电网络拓扑路径识别问题，提出原始数据转换、假设路径生成与兼容性识别的迭代流程，可在数据不完整时提升准确性与适应性，支撑数字孪生构建。
摘要：
本文提出一种系统化方法，用于解决配电网络中的拓扑路径识别（TPI）问题。该方法首先梳理配电系统运营商（DSO）来自多个来源的原始信息。原始信息通过一组转换函数经历转换过程，被转化为算法可利用的、定义明确的信息。随后，考虑配电系统各元件之间任何可能的连接，生成一组假设路径。该假设路径集合由算法处理，算法识别出与定义明确的信息相兼容的假设路径。该流程以迭代方式运行，并根据所得结果调整转换函数集合：如果识别出的路径未能满足 DSO 的预期，则收集新数据，和/或修改被认定为导致差异的转换函数。该系统化流程为 DSO 提供了实际优势，包括提高路径识别的准确性，以及对多样化网络配置的高度适应性，即使在数据不完整或不准确的情况下也是如此。因此，它成为构建符合 DSO 预期的配电网络数字孪生的有用工具。
英文摘要：
This paper introduces a systematic approach to address the topological path identification (TPI) problem in power distribution networks. Our approach starts by listing the DSO's raw information coming from several sources. The raw information undergoes a transformation process using a set of transformation functions. This process converts the raw information into well-defined information exploitable by an algorithm. Then a set of hypothetical paths is generated, considering any potential connections between the elements of the power distribution system. This set of hypothetical paths is processed by the algorithm that identifies the hypothetical paths that are compatible with the well-defined information. This procedure operates iteratively, adapting the set of transformation functions based on the result obtained: if the identified paths fail to meet the DSO's expectations, new data is collected, and/or the transformation functions found to be responsible for the discrepancies are modified. The systematic procedure offers practical advantages for DSOs, including improved accuracy in path identification and high adaptability to diverse network configurations, even with incomplete or inaccurate data. Consequently, it emerges as a useful tool for the construction of digital twins of power distribution networks that aligns with DSO expectations.
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