Comparison of Short-Term Electrical Load Forecasting Models using Datasets from The Building Automation System in The Department of Electrical Engineering ITN-Reference-Cited by-同舟云学术

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Comparison of Short-Term Electrical Load Forecasting Models using Datasets from The Building Automation System in The Department of Electrical Engineering ITN

Published:2023-11-23 Issue: Volume: Page:441-445
ISSN:
Container-title:2023 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT)
language:
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Author:

Davi Labib Radimas Putra Muhammad¹,Soetedjo Aryuanto¹,Sulistiawati Irrine Budi¹,Limpraptono Fransiscus Yudi¹,Krismanto Awan Uji¹,Effendi Khoirul Fahmi¹

Affiliation:

1. Institut Teknologi Nasional Malang,Department of Electrical Engineering,Malang,Indonesia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10420524/10420471/10420633.pdf?arnumber=10420633

Reference19 articles.

1. Implementation of a 220v Ac Overload and High Voltage Monitor Alert System with Auto Shut Down

2. Research on line overload identification of power system based on improved neural network algorithm

3. Smart Electricity Meter Load Prediction in Dubai Using MLR, ANN, RF, and ARIMA

4. A New Approach for Forecasting Crude Oil Prices Based on Stochastic and Deterministic Influences of LMD Using ARIMA and LSTM Models

5. From Load to Net Energy Forecasting: Short-Term Residential Forecasting for the Blend of Load and PV Behind the Meter

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