Canonical Correlation Analysis and Visualization for Big Data in Smart Grid

IF 3.7 2区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Journal on Emerging and Selected Topics in Circuits and Systems Pub Date : 2023-06-28 DOI:10.1109/JETCAS.2023.3290418

Zigui Jiang;Qihao Yuan;Rongheng Lin;Fangchun Yang

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引用次数: 0

Abstract

Electricity consumption behaviors are influenced by various external and internal factors such as climate, location, building type, consumer characteristics and even other energy consumption. In order to investigate the electricity consumption behaviors of diverse consumers, we propose a methodology based on canonical correlation analysis to explore the correlation among electricity consumption, gas consumption and climate change under different circumstances. We first preprocess three multivariable datasets that contain 24-value daily data in a one-year period, and conduct consumer segmentation based on climate zones, locations and building types. Then an optimized canonical correlation analysis model with an optimal result selection mechanism is adopted to calculate the canonical correlations and weights of every set of daily data. Finally, we propose a post-processing analysis for further comparison on the calculated results. We investigate three research questions to present and discuss the analysis results, including canonical correlation and weights overview, typical patterns analysis, and comparison on climate zones and locations.

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智能电网大数据的典型相关分析与可视化

电力消费行为受到气候、地理位置、建筑类型、消费者特征乃至其他能源消耗等各种外部和内部因素的影响。为了研究不同消费者的用电量行为，我们提出了一种基于典型相关分析的方法来探讨不同情况下用电量、用气量与气候变化之间的相关性。我们首先对三个包含一年24值每日数据的多变量数据集进行预处理，并根据气候带、地点和建筑类型进行消费者细分。然后，采用具有最优结果选择机制的优化典型相关分析模型，计算每组日常数据的典型相关和权重。最后，我们提出了一个后处理分析，以进一步比较计算结果。本文从典型相关和权重概述、典型模式分析、气候带和地点比较三个方面对分析结果进行了探讨。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Journal on Emerging and Selected Topics in Circuits and Systems ENGINEERING, ELECTRICAL & ELECTRONIC-

CiteScore

8.50

自引率

2.20%

发文量

期刊介绍： The IEEE Journal on Emerging and Selected Topics in Circuits and Systems is published quarterly and solicits, with particular emphasis on emerging areas, special issues on topics that cover the entire scope of the IEEE Circuits and Systems (CAS) Society, namely the theory, analysis, design, tools, and implementation of circuits and systems, spanning their theoretical foundations, applications, and architectures for signal and information processing.