Regarding power system dispatch decisions, the current-carrying limits of transmission lines in each dispatch period in the look-ahead time horizon should be represented by the intra-period minimum thermal rating (IMTR) for the sake of security. In this paper, the IMTR prediction issue of the overhead conductor is raised, and the predictability of the IMTR is investigated. Specifically, for the overhead conductor, the distribution and correlation characteristics of the IMTR and its corresponding meteorological elements are analyzed based on the measured meteorological data around an overhead conductor. On this basis, the quantile regression neural network (QRNN) and copula model are employed to make probability predictions on IMTRs of multiple periods in the prediction time horizon considering the temporal correlation of the IMTR. Also, the influences of the time period length, prediction time horizon, and the consideration of the temporal correlation of the IMTR on prediction results are analyzed. The work presented in this paper reveals the predictability of the IMTR, which is of significance to guide the prediction of the IMTR of the overhead conductor. Thus, it can help operators safely exploit the current-carrying capability of the overhead line.

中文翻译：

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架空导线期内最低热额定值预测


在电力系统调度决策中，为了安全起见，前瞻时间范围内每个调度周期内输电线路的载流限值应采用周期内最小热额定值（IMTR）来表示。本文提出了架空导线的IMTR预测问题，并对IMTR的可预测性进行了研究。具体来说，对于架空导线，根据架空导线周围的实测气象数据，分析IMTR及其相应气象要素的分布和相关特征。在此基础上，考虑IMTR的时间相关性，采用分位数回归神经网络（QRNN）和Copula模型对预测时间范围内多个周期的IMTR进行概率预测。还分析了IMTR的时间段长度、预测时间范围以及考虑时间相关性对预测结果的影响。本文的工作揭示了IMTR的可预测性，对指导架空导线IMTR的预测具有重要意义。因此，它可以帮助操作员安全地利用架空线路的载流能力。