多元数据融合的智能配电网负荷分析预测管理系统

针对多元大数据在智能配电网中的应用问题，为实现配电网的精益管理、科学预测和合理规划，文章开发了多元数据融合的智能配电网负荷分析预测管理系统。对软件系统的总体框架进行了设计；对软件系统的各功能模块进行开发和介绍；给出了软件系统的一个应用实例。该系统充分利用海量的历史负荷数据进行负荷特性分析，建立负荷特征库以及业扩信息库，通过对新接入用户进行信息匹配实现负荷管理及最大负荷预测。此外，该系统建立负荷预测方法模型库，可提供不同维度的负荷预测功能，从传统的地区负荷预测转变为馈线负荷预测，结合馈线现状以及业扩信息优化用户接入决策。总的来说，该系统具有功能模块数据链路互通、不同功能之间能提供信息支持、整体采用模块化设计思想等特点，可满足电网企业的日常应用需求。

Load Analysis and Forecast Management System of Smart Distribution Grid Based on Multivariate Data Source Aggregation

This paper develops a smart distribution network load analysis and forecasting management system based on multivariate data aggregation for the application of multivariate big data in smart distribution networks in order to realize lean management, scientific prediction and rational planning of distribution networks. First, the general framework of the software system is designed; then, each functional module of the software system is developed and introduced; and finally, an application example of the software system is given. The system makes full use of the massive historical load data for load characteristic analysis, establishes load characteristic database and industry expansion information database, and realizes load management and maximum load prediction by matching information to new users. In addition, the system establishes a library of load forecasting method models, which can provide load forecasting functions in different dimensions, from the traditional regional load forecasting. Overall, the system has the features of interoperability of data links between functional modules, information support between different functions, and overall modular design concept, which can meet the daily application requirements of power grid enterprises.