Short‐term load forecasting in smart grids using artificial intelligence methods: A survey-Reference-Cited by-同舟云学术

Short‐term load forecasting in smart grids using artificial intelligence methods: A survey

Published:2022-08-16 Issue:12 Volume:2022 Page:1133-1142
ISSN:2051-3305
Container-title:The Journal of Engineering
language:en
Short-container-title:The Journal of Engineering

Author:

Salehimehr Sirus¹^ORCID,Taheri Behrooz²^ORCID,Sedighizadeh Mostafa³^ORCID

Affiliation:

1. Department of Energy Politecnico di Milano Milano Italy

2. Department of Electrical Engineering Qazvin Branch Islamic Azad University Qazvin Iran

3. Faculty of Electrical Engineering Shahid Beheshti University Evin Tehran Iran

Publisher

Institution of Engineering and Technology (IET)

Subject

General Engineering,Energy Engineering and Power Technology,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/tje2.12183

Reference62 articles.

1. Short-Term Load Forecasting in Smart Grids: An Intelligent Modular Approach

2. Demand side management in smart grid: A review and proposals for future direction

3. Currie R. Ault G. Foote C. Burt G. McDonald J.:Fundamental research challenges for active management of distribution networks with high levels of renewable generation. In:39th International Universities Power Engineering Conference.Bristol UK pp.1024–1028(2004)

4. A residual load modeling approach for household short-term load forecasting application

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