Summer Electricity Consumption Patterns in Households Using Appliance Load Profiles-Reference-Cited by-同舟云学术

Summer Electricity Consumption Patterns in Households Using Appliance Load Profiles

Published:2023-11-15 Issue: Volume: Page:
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Container-title:Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation
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Author:

Maurya Shishir¹^ORCID,CGS Ganesh¹^ORCID,Garg Vishal²^ORCID,Mathur Jyotirmay³^ORCID

Affiliation:

1. Center for IT in Building Science, International Institute of Information Technology, Hyderabad, India

2. Indorama Ventures Center for Clean Energy, Plaksha University, India

3. Center for Energy and Environment, Malaviya National Institute of Technology Jaipur, India

Funder

DST, Government of India and EPSRC, UK

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3600100.3627027

Reference12 articles.

1. Deriving electricity consumption patterns using a decomposition approach

2. “ A Longitudinal Study of Customer Electricity Load Profiles ,” presented at the Annual International Computer Software and Applications Conference , Jun. 2022 , pp. 289– 294 . doi: 10.1109/COMPSAC54236.2022.00048. 10.1109/COMPSAC54236.2022.00048 “A Longitudinal Study of Customer Electricity Load Profiles,” presented at the Annual International Computer Software and Applications Conference, Jun. 2022, pp. 289–294. doi: 10.1109/COMPSAC54236.2022.00048.

3. “ Residential load forecasting based on electricity consumption pattern clustering ,” Frontiers in Energy Research , vol. 10 , Jan. 2023 , doi: 10.3389/fenrg.2022.1113733. 10.3389/fenrg.2022.1113733 “Residential load forecasting based on electricity consumption pattern clustering,” Frontiers in Energy Research, vol. 10, Jan. 2023, doi: 10.3389/fenrg.2022.1113733.

4. Clustering and Load Shape Analysis of Household Electricity Consumption for Demand Response Program;Journal of The Korean Society of Living Environmental System,2022

5. A method for distinguishing appliance, lighting and plug load profiles from electricity ‘smart meter’ datasets;Energy and Buildings,2017