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A pattern recognition methodology for analyzing residential customers load data and targeting demand response applications

  • Published:2019-11 Issue: Volume:203 Page:109455
  • ISSN:0378-7788
  • Container-title:Energy and Buildings
  • language:en
  • Short-container-title:Energy and Buildings

Author:

Rajabi Amin,Eskandari Mohsen,Jabbari Ghadi Mojtaba,Ghavidel Sahand,Li Li,Zhang Jiangfeng,Siano Pierluigi

Funder

Australian Government Research

University of Technology Sydney

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Building and Construction,Civil and Structural Engineering

Cited by 36 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A generalizable approach to imbalanced classification of residential electric space heat;Environmental Research: Infrastructure and Sustainability;2024-08-21

2. An Improved Parallel Clustering Method Based on K-Means for Electricity Consumption Patterns;Journal of Advanced Computational Intelligence and Intelligent Informatics;2024-07-20

3. Short-Term Residential Load Forecasting via Pooling-Ensemble Model With Smoothing Clustering;IEEE Transactions on Artificial Intelligence;2024-07

4. Methods and attributes for customer-centric dynamic electricity tariff design: A review;Renewable and Sustainable Energy Reviews;2024-03

5. A new customer selection framework for time-based pricing program;Energy;2024-03
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