高比例新能源接入背景下配电高频采集业务发展迅速，接入终端数量与业务采集量激增，对配电网数据采集、传输与处理能力提出了更高要求。因此，提出了面向配电网高频采集的通信资源智能编排技术。首先，构建面向配电网高频采集的通信资源智能编排框架。其次，在考虑高频采集业务对时延与能耗敏感性的基础上建立以满足差异化业务需求为目标的优化模型。最后，针对终端决策耦合、网关选择冲突等问题，提出基于业务差异性感知的通信资源智能编排算法，通过改进的单边匹配实现配电网高频采集业务差异化需求保障，避免计算资源浪费。仿真结果表明所提算法相较于对比算法终端平均能耗分别降低58.54 %和73.98 %，平均数据处理时延分别降低51.99 %和69.93 %。

Under the background of high proportion of new energy access, the development of high frequency distribution data collection business is rapid, and the number of access terminals and business collection volume has surged, which puts higher requirements on the data collection, transmission, and processing capabilities of distribution networks. Therefore, a communication resource intelligent scheduling technology for high frequency collection in distribution networks is proposed. Firstly, a communication resource intelligent scheduling framework is constructed for high frequency collection in distribution networks. Secondly, based on considering the sensitivity of high frequency connection services to latency and energy consumption, an optimization model is established with the goal of meeting differentiated business requirements. Finally, in response to issues such as terminal decision coupling and gateway selection conflicts, a communication resource intelligent scheduling algorithm based on business differentiation awareness is proposed. Through improved unilateral matching, the differentiated demand guarantee of high frequency collection business in distribution networks is achieved, avoiding the waste of computing resources. The simulation results show that the proposed algorithm reduces the average energy consumption of terminals by 58.54% and 73.98% respectively, and reduces the average data processing latency by 51.99% and 69.93% respectively compared to the comparative algorithm.