Short-Term Load Forecasting Algorithm Using a Similar Day Selection Method Based on Reinforcement Learning

Short-Term Load Forecasting Algorithm Using a Similar Day Selection Method Based on Reinforcement Learning

Short-term load forecasting (STLF) is very important for planning and operating power systems and markets. Various algorithms have been developed for STLF. However, numerous utilities still apply additional correction processes, which depend on experienced professionals. In this study, an STLF algor...

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Bibliographic Details
Main Authors:	Rae-Jun Park, Kyung-Bin Song, Bo-Sung Kwon
Format:	Article
Language:	English
Published:	MDPI AG 2020-05-01
Series:	Energies
Subjects:	short-term load forecasting deep Q-network (DQN) backpropagation neural network (BPNN) long short-term memory (LSTM) reinforcement learning algorithm
Online Access:	https://www.mdpi.com/1996-1073/13/10/2640

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