International Journal of Energy and Power Engineering

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Seasonal Peak Characteristic Comparison Analysis by Hourly Electricity Demand Model

Received: 09 May 2014    Accepted: 29 May 2014    Published: 10 June 2014
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Abstract

As driver variables may influence more than one area of electricity demand, knowing typical effect of the variables on certain demand areas is important. Utilities can use the information of managing power systems to meet electricity demand for different areas more effective. Based on the regression analysis approach, this study presents a peak demand characteristics comparison between Japanese residential and commercial areas in seasonal level by composing hourly electricity demand model for each area. Besides, a representative hour for off-peak demands is also analyzed. Similar variables (temperature, humidity, wind speed, and holidays) are applied to explain peak and off-peak of summer, autumn, winter, and spring in both areas. Results indicate key drivers for peak and off-peak demands are not same in the certain seasons for both areas. Obtained key variables tend to affect stronger peaks and off-peaks for residential than for commercial area in four observed seasons.

DOI 10.11648/j.ijepe.20140303.14
Published in International Journal of Energy and Power Engineering (Volume 3, Issue 3, June 2014)
Page(s) 132-138
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Characteristics Comparison, Seasonal Peak, Hourly Demand Model, Residential Area, Commercial Area

References
[1] A. Pardo, V. Meneu and E. Valor, “Temperature and Seasonality Influences on Spanish Electricity Load,” Energy Economics, Vol. 24, pp. 55–70, 2002.
[2] I. S. Qamber, “Peak Load Modeling for Kingdom of Bahrain”, Journal of Software Engineering and Applications, Vol. 5, No. 12B, pp. 46–49, 2012.
[3] J. C. Lam, H. L. Tang, and D. H. W. Li, “Seasonal Variations in Residential and Commercial Sector Electricity Consumption in Hong Kong”, Energy, Vol. 33, pp. 513–523, 2008.
[4] K. Wangpattarapong, S. Maneewan, N. Ketjoy and W. Rakwichian, “The Impacts of Climatic and Economic Factors on Residential Electricity Consumption of Bangkok Metropolis,” Energy and Buildings, Vol. 40, pp. 1419–1425, 2008.
[5] S. Mirasgedis, Y. Sarafidis, E. Geor-gopoulou, D. P. Lalas, M. Moschovits, F. Karagiannis and D. Papakonstantinou, “Models for Mid-Term Electricity Demand Forecasting Incorporating Weather Influences,” Energy, Vol. 31, pp. 208–227, 2006.
[6] S. R. Deeba, and Nahid-Al-Masood, “Correlation between Reliability and Weather Scenario: In Perspective of Bangladesh Power System”, International Journal of Energy and Power Engineering, Vol. 2, No. 3, pp. 109–113, 2013.
[7] S. B. Sadineni, and R. F. Boehm, “Measurements and Simulations for Peak Electrical Load Reduction in Cooling Dominated Cli-mate”, Energy, Vol. 37, pp. 689–697, 2012.
[8] Y. S. Akil, and H. Miyauchi, “Seasonal Peak Electricity Demand Characteristics: Japan Case Study”, International Journal of Energy and Power Engineering, Vol. 2, No. 3, pp. 136–142, 2013.
[9] B. E. Psiloglou, C. Giannakopoulos, S. Ma-jithia and M. Petrakis, “Factors Affecting Electricity Demand in Athens, Greece and London, UK: A Comparative Assessment,” Energy, Vol. 34, pp. 1855-1863, 2009.
[10] Japan Meteorological Agency (JMA). http://www.jma.go.jp/jma/indexe.html
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[12] EViews. http://www.eviews.com
Author Information
  • Dept. of Electrical Engineering, Hasanuddin University, Makassar 90245, Indonesia

  • Dept. of Frontier Technology for Energy and Devices, Kumamoto University, Kumamoto 860-8555, Japan

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  • APA Style

    Yusri Syam Akil, Hajime Miyauchi. (2014). Seasonal Peak Characteristic Comparison Analysis by Hourly Electricity Demand Model. International Journal of Energy and Power Engineering, 3(3), 132-138. https://doi.org/10.11648/j.ijepe.20140303.14

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    ACS Style

    Yusri Syam Akil; Hajime Miyauchi. Seasonal Peak Characteristic Comparison Analysis by Hourly Electricity Demand Model. Int. J. Energy Power Eng. 2014, 3(3), 132-138. doi: 10.11648/j.ijepe.20140303.14

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    AMA Style

    Yusri Syam Akil, Hajime Miyauchi. Seasonal Peak Characteristic Comparison Analysis by Hourly Electricity Demand Model. Int J Energy Power Eng. 2014;3(3):132-138. doi: 10.11648/j.ijepe.20140303.14

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  • @article{10.11648/j.ijepe.20140303.14,
      author = {Yusri Syam Akil and Hajime Miyauchi},
      title = {Seasonal Peak Characteristic Comparison Analysis by Hourly Electricity Demand Model},
      journal = {International Journal of Energy and Power Engineering},
      volume = {3},
      number = {3},
      pages = {132-138},
      doi = {10.11648/j.ijepe.20140303.14},
      url = {https://doi.org/10.11648/j.ijepe.20140303.14},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijepe.20140303.14},
      abstract = {As driver variables may influence more than one area of electricity demand, knowing typical effect of the variables on certain demand areas is important. Utilities can use the information of managing power systems to meet electricity demand for different areas more effective. Based on the regression analysis approach, this study presents a peak demand characteristics comparison between Japanese residential and commercial areas in seasonal level by composing hourly electricity demand model for each area. Besides, a representative hour for off-peak demands is also analyzed. Similar variables (temperature, humidity, wind speed, and holidays) are applied to explain peak and off-peak of summer, autumn, winter, and spring in both areas. Results indicate key drivers for peak and off-peak demands are not same in the certain seasons for both areas. Obtained key variables tend to affect stronger peaks and off-peaks for residential than for commercial area in four observed seasons.},
     year = {2014}
    }
    

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  • TY  - JOUR
    T1  - Seasonal Peak Characteristic Comparison Analysis by Hourly Electricity Demand Model
    AU  - Yusri Syam Akil
    AU  - Hajime Miyauchi
    Y1  - 2014/06/10
    PY  - 2014
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    DO  - 10.11648/j.ijepe.20140303.14
    T2  - International Journal of Energy and Power Engineering
    JF  - International Journal of Energy and Power Engineering
    JO  - International Journal of Energy and Power Engineering
    SP  - 132
    EP  - 138
    PB  - Science Publishing Group
    SN  - 2326-960X
    UR  - https://doi.org/10.11648/j.ijepe.20140303.14
    AB  - As driver variables may influence more than one area of electricity demand, knowing typical effect of the variables on certain demand areas is important. Utilities can use the information of managing power systems to meet electricity demand for different areas more effective. Based on the regression analysis approach, this study presents a peak demand characteristics comparison between Japanese residential and commercial areas in seasonal level by composing hourly electricity demand model for each area. Besides, a representative hour for off-peak demands is also analyzed. Similar variables (temperature, humidity, wind speed, and holidays) are applied to explain peak and off-peak of summer, autumn, winter, and spring in both areas. Results indicate key drivers for peak and off-peak demands are not same in the certain seasons for both areas. Obtained key variables tend to affect stronger peaks and off-peaks for residential than for commercial area in four observed seasons.
    VL  - 3
    IS  - 3
    ER  - 

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