IDEAS home Printed from https://ideas.repec.org/a/spt/admaec/v14y2024i1f14_1_2.html
   My bibliography  Save this article

Developing Information Gateway for Intelligent Decision-Making and Stability in Solar Power Generation

Author

Listed:
  • Cheng-Wen Lee
  • Wen-Chuan Wu

Abstract

This study has developed a specialized information gateway for inverters, utilizing relays, data converters, and single-board computers, among other components. Upon receiving data from the gateway, the server processes it to generate an intelligent solar monitoring system. The platform utilizes deep learning RNN and LSTM algorithms to forecast power generation at solar power plants, allowing for real-time monitoring of weather and power generation. By comparing actual and expected power generation data, the system can adjust equipment maintenance and cleaning schedules. It is designed to automatically alert staff members to take appropriate action when anomalous power generation data is continuously transmitted. Additionally, the system sends an alert for on-site inspection and removal of any abnormal situations to increase the stability of solar power generation. This study employs deep learning and IoT data collection to provide the knowledge necessary for intelligent decision-making and increased stability in solar power generation. Â JEL classification numbers: C43, F68, H41.

Suggested Citation

  • Cheng-Wen Lee & Wen-Chuan Wu, 2024. "Developing Information Gateway for Intelligent Decision-Making and Stability in Solar Power Generation," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 14(1), pages 1-2.
    • Handle: RePEc:spt:admaec:v:14:y:2024:i:1:f:14_1_2
    as

    Download full text from publisher

    File URL: http://www.scienpress.com/Upload/AMAE%2fVol%2014_1_2.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Majid Hosseini & Satya Katragadda & Jessica Wojtkiewicz & Raju Gottumukkala & Anthony Maida & Terrence Lynn Chambers, 2020. "Direct Normal Irradiance Forecasting Using Multivariate Gated Recurrent Units," Energies, MDPI, vol. 13(15), pages 1-15, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Isaac Gallardo & Daniel Amor & Álvaro Gutiérrez, 2023. "Recent Trends in Real-Time Photovoltaic Prediction Systems," Energies, MDPI, vol. 16(15), pages 1-17, July.
    2. Ouyang, Tiancheng & Pan, Mingming & Huang, Youbin & Tan, Xianlin & Qin, Peijia, 2023. "Thermodynamic design and power prediction of a solar power tower integrated system using neural networks," Energy, Elsevier, vol. 278(PA).

    More about this item

    Keywords

    Solar energy; IoT monitoring; RNN; LSTN; Abnormal return.;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • F68 - International Economics - - Economic Impacts of Globalization - - - Policy
    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spt:admaec:v:14:y:2024:i:1:f:14_1_2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Eleftherios Spyromitros-Xioufis (email available below). General contact details of provider: http://www.scienpress.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.