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Forecasting System for Solar-Power Generation

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Recent Challenges in Intelligent Information and Database Systems (ACIIDS 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1371))

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Abstract

Environmental protection is a highly concerned and thought-provoking issue, and the way of generating electricity has become a major conundrum for all mankind. Renewable or green energy is an ideal solution for environmentally friendly (eco-friendly) power generation. Among all renewable energy, solar-power generation is low cost and small footprint, which make solar-power generation available around our lives. The major uncontrollable factor in the solar-power generation is the amount of solar radiation, which completely dominates the electricity generated by solar panel. In this paper, we design prediction models for solar radiation, using data mining techniques and machine learning algorithms, and derive precision prediction models (PPM) and light prediction models (LPM). Experimental results that the PPM (LPM) with random forest regression can obtain R-squared of 0.841 (0.828) and correlation coefficient of 0.917 (0.910). Compared with highly cited researches, our models outperform them in all measurements, which demonstrates the robustness and effectiveness of the proposed models.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan

    Jia-Hao Syu

  2. Department of Information and Finance Management, National Taipei University of Technology, Taipei, Taiwan

    Chi-Fang Chao & Mu-En Wu

Authors
  1. Jia-Hao Syu
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  2. Chi-Fang Chao
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  3. Mu-En Wu
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Corresponding author

Correspondence to Jia-Hao Syu .

Editor information

Editors and Affiliations

  1. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  2. Wrocław University of Science and Technology, Wrocław, Poland

    Krystian Wojtkiewicz

  3. King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand

    Rathachai Chawuthai

  4. Kielce University of Technology, Kielce, Poland

    Pawel Sitek

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Syu, JH., Chao, CF., Wu, ME. (2021). Forecasting System for Solar-Power Generation. In: Hong, TP., Wojtkiewicz, K., Chawuthai, R., Sitek, P. (eds) Recent Challenges in Intelligent Information and Database Systems. ACIIDS 2021. Communications in Computer and Information Science, vol 1371. Springer, Singapore. https://doi.org/10.1007/978-981-16-1685-3_6

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  • DOI: https://doi.org/10.1007/978-981-16-1685-3_6

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-1684-6

  • Online ISBN: 978-981-16-1685-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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