Combined use of long short‐term memory neural network and quantum computation for hierarchical forecasting of locational marginal prices

Combined use of long short‐term memory neural network and quantum computation for hierarchical forecasting of locational marginal prices

Abstract Accurate locational marginal price forecasting (LMPF) is crucial for the efficient allocation of resources. Nevertheless, the sudden changes in LMP make it inadequate for many existing long short‐term memory (LSTM) network‐based prediction models to achieve the required accuracy for practic...

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Bibliographic Details
Main Authors: Xin Huang, Guozhong Liu, Jiajia Huan, Shuxin Luo, Jing Qiu, Feiyan Qin, Yunxia Xu
Format: Article
Language:English
Published: Wiley 2025-02-01
Series:Energy Conversion and Economics
Subjects:
electricity market
electricity price forecasting
long short‐term memory network
quantum grey wolf optimisation algorithm
support vector machine
Online Access:https://doi.org/10.1049/enc2.70004
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https://doi.org/10.1049/enc2.70004

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