Improving short-term electricity price forecasting using day-ahead LMP with ARIMA models-Reference-Cited by-同舟云学术

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Improving short-term electricity price forecasting using day-ahead LMP with ARIMA models

Published:2017-07 Issue: Volume: Page:
ISSN:
Container-title:2017 IEEE Power & Energy Society General Meeting
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Author:

Zhao Zhongyang,Wang Caisheng,Nokleby Matthew,Miller Carol J.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8263544/8273724/08274124.pdf?arnumber=8274124

Cited by 15 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Two-Stage Forecasting Approach for Day-Ahead Electricity Price Based on Improved Wavelet Neural Network With ELM Initialization;IEEE Transactions on Industry Applications;2024-05

2. Revenue Analysis of Stationary and Transportable Battery Storage for Power Systems: A Market Participant Perspective;Sustainability;2024-03-13

3. Application of Machine Learning Techniques in Natural Gas Price Modeling. Analyses, Comparisons, and Predictions for Romania;Springer Proceedings in Business and Economics;2024

4. Day-ahead electricity price forecasting using artificial intelligence-based algorithms;2023 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT);2023-11-20

5. LMP Sensitivity Calculation with Load Uncertainty by Using Combined Heuristic and Brute-force Technique;Journal of Electrical Engineering & Technology;2023-09-12

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