Climate Change and Power Security: Power Load Prediction for Rural Electrical Microgrids Using Long Short Term Memory and Artificial Neural Networks

Climate Change and Power Security: Power Load Prediction for Rural Electrical Microgrids Using Long Short Term Memory and Artificial Neural Networks

Many of rural Alaskan communities operate their own, stand-alone electrical microgrids as there is no state-wide power distribution network. Although the fossil fuel-based power generators are the primary energy source in these isolated communities, an increasing number of microgrids have started to...

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Bibliographic Details
Main Authors: Martin Cenek, Rocco Haro, Brandon Sayers, Jifeng Peng
Format: Article
Language:English
Published: MDPI AG 2018-05-01
Series:Applied Sciences
Subjects:
power load prediction
long short term memory
neural networks
power management systems
Online Access:http://www.mdpi.com/2076-3417/8/5/749

Internet

http://www.mdpi.com/2076-3417/8/5/749

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