An Efficient Approach for User Power Consumption Forecasting Based on Feature Extraction in Virtual Power Plants-Reference-Cited by-同舟云学术

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An Efficient Approach for User Power Consumption Forecasting Based on Feature Extraction in Virtual Power Plants

Published:2022-04-10 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Wireless Communications and Networking Conference (WCNC)
language:
Short-container-title:

Author:

Yan Min¹,Wang Li¹,Xu Lianming²,Fei Aiguo¹

Affiliation:

1. Beijing University of Posts and Telecommunications,School of Computer Science (National Pilot Software Engineering School),Beijing,China,100876

2. Beijing University of Posts and Telecommunications,School of Electronic Engineering,Beijing,China,100876

Funder

National Natural Science Foundation of China

Beijing Municipal Natural Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9771381/9771540/09771618.pdf?arnumber=9771618

Reference17 articles.

1. A Comprehensive Review of Dimensionality Reduction Techniques for Feature Selection and Feature Extraction

2. Convolutional Autoencoder Based Feature Extraction and Clustering for Customer Load Analysis

3. Synchronous Pattern Matching Principle-Based Residential Demand Response Baseline Estimation: Mechanism Analysis and Approach Description

4. When Bias Matters: An Economic Assessment of Demand Response Baselines for Residential Customers

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