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A novel method for long-term power demand prediction using enhanced data decomposition and neural network with integrated uncertainty analysis: A Cuba case study
https://hiroshima.repo.nii.ac.jp/records/2040674
https://hiroshima.repo.nii.ac.jp/records/204067405a6dc8f-0953-4128-b0ca-48b8cff743bb
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
ApEnergy_372_123864.pdf (2.3 MB)
Download is available from 2026/7/9.
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| Item type | デフォルト(1) | |||||||||||
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| 公開日 | 2025-06-02 | |||||||||||
| タイトル | ||||||||||||
| タイトル | A novel method for long-term power demand prediction using enhanced data decomposition and neural network with integrated uncertainty analysis: A Cuba case study | |||||||||||
| 言語 | en | |||||||||||
| 作成者 |
Calvo, Manuel Soto
× Calvo, Manuel Soto
× Lee, Han Soo
× Chisale, Sylvester William
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| アクセス権 | ||||||||||||
| アクセス権 | embargoed access | |||||||||||
| アクセス権URI | http://purl.org/coar/access_right/c_f1cf | |||||||||||
| 権利情報 | ||||||||||||
| 言語 | en | |||||||||||
| 権利情報 | © <2024>. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/ | |||||||||||
| 権利情報 | ||||||||||||
| 言語 | en | |||||||||||
| 権利情報 | This is not the published version. Please cite only the published version. | |||||||||||
| 権利情報 | ||||||||||||
| 言語 | ja | |||||||||||
| 権利情報 | この論文は出版社版ではありません。引用の際には出版社版をご確認、ご利用ください。 | |||||||||||
| 主題 | ||||||||||||
| 言語 | en | |||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | Enhanced ensemble empirical mode decomposition (ECEEMDAN） | |||||||||||
| 主題 | ||||||||||||
| 言語 | en | |||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | Long short-term memory (LSTM) | |||||||||||
| 主題 | ||||||||||||
| 言語 | en | |||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | Monte Carlo simulation | |||||||||||
| 主題 | ||||||||||||
| 言語 | en | |||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | CMIP6 | |||||||||||
| 主題 | ||||||||||||
| 言語 | en | |||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | Energy planning and strategy | |||||||||||
| 主題 | ||||||||||||
| 言語 | en | |||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | Energy policy | |||||||||||
| 内容記述 | ||||||||||||
| 内容記述タイプ | Abstract | |||||||||||
| 内容記述 | This study developed a methodological approach for long-term electricity demand forecasting and applied it to the electricity demand in Cuba, which is crucial for transitioning from a fossil fuel-dependent system to renewable energy sources. The methodology employs enhanced complete ensemble empirical mode decomposition with adaptive noise (ECEEMDAN) applied for obtaining long-term trends from historical electricity usage data decomposition, combined with a long short-term memory (LSTM) deep learning model for prediction. Comprehensive datasets, including historical electricity consumption, economic indicators, and demographic data, are utilized in the analysis. Monte Carlo simulations, then, are integrated to address uncertainties in prediction and explore 50 different scenarios of future electricity demand. The study forecasts varying scenarios for the energy demand of Cuba by 2050, with the extreme low scenario projecting a decrease of up to 7.9% compared to the 2019 level. This research offers a groundbreaking framework specifically designed to aid Cuba's energy sector stakeholders in informed decision-making during this critical energy transition. The adaptability of the methodology makes it applicable for long-term projections in various sectors, offering a reliable tool for global decision makers. | |||||||||||
| 言語 | en | |||||||||||
| 出版者 | ||||||||||||
| 出版者 | Elsevier | |||||||||||
| 言語 | en | |||||||||||
| 日付 | ||||||||||||
| 日付 | 2026-07-09 | |||||||||||
| 日付タイプ | Available | |||||||||||
| 言語 | ||||||||||||
| 言語 | eng | |||||||||||
| 資源タイプ | ||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||
| 資源タイプ | journal article | |||||||||||
| 出版タイプ | ||||||||||||
| 出版タイプ | AM | |||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||||||||
| 関連情報 | ||||||||||||
| 関連タイプ | isVersionOf | |||||||||||
| 識別子タイプ | DOI | |||||||||||
| 関連識別子 | http://dx.doi.org/10.1016/j.apenergy.2024.123864 | |||||||||||
| 収録物識別子 | ||||||||||||
| 収録物識別子タイプ | ISSN | |||||||||||
| 収録物識別子 | 0306-2619 | |||||||||||
| 書誌情報 |
en : APPLIED ENERGY 巻 372, p. 123864, 発行日 2024-07-09 |
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| 備考 | ||||||||||||
| 言語 | en | |||||||||||
| 値 | The full-text file will be made open to the public on [09 July 2026］ in accordance with publisher's 'Terms and Conditions for Self-Archiving' | |||||||||||
