Spatial Electric Load Forecasting Using a Geographic Information System: A Case Study of Khon Kaen, Thailand-Reference-Cited by-同舟云学术

Spatial Electric Load Forecasting Using a Geographic Information System: A Case Study of Khon Kaen, Thailand

Published:2023-08-09 Issue: Volume: Page:
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Container-title:2023 IEEE 3rd International Conference on Sustainable Energy and Future Electric Transportation (SEFET)
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Author:

Tephiruk Naowarat¹,Hongesombut Komsan¹,Damrongkulkamjorn Parnjit¹,Jamroen Chaowanan²

Affiliation:

1. Kasetsart University,Faculty of Engineering,Department of Electrical Engineering,Bangkok,Thailand,10900

2. King Mongkut's University of Technology North Bangkok,Division of Instrumentation and Automation Engineering Technology, Faculty of Engineering and Technology,Bangkok,Thailand,10800

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10244770/10244772/10245044.pdf?arnumber=10245044

Reference22 articles.

1. Forecasting short-term electricity consumption using the adaptive grey-based approach—An Asian case

2. A data-driven approach for multi-scale GIS-based building energy modeling for analysis, planning and support decision making;ali;Appl Energy,2020

3. A novel machine learning approach for estimation of electricity demand: An empirical evidence from Thailand

4. Forecasting Electricity Demand in Thailand with an Artificial Neural Network Approach

5. GIS-Based Distribution System Planning for New PV Installations

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