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Estimating Hourly Profiles of Insolation based on Weekly Weather Forecast

Received: 25 August 2014     Accepted: 12 September 2014     Published: 27 October 2014
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Abstract

In this paper, the authors present a simple procedure of estimating weekly profiles of insolation for photovoltaic (PV) power generation output of a roof-top PV system. The model is based on the historical data of solar insolation and weather conditions. Weather conditions are classified into representative patterns such as sunny, cloudy, and rainy, and corresponding hourly profile of insolation is obtained as the most likely values under each weather condition. The system uses the text weather forecast and the probability of precipitation information as input to obtain the estimated weekly profile of insolation. From the results presented here it is shown that such a simple profile can be useful for rating the storage batteries and scheduling electric vehicle charging to better utilize the PV-generated electricity.

Published in International Journal of Energy and Power Engineering (Volume 3, Issue 6-2)

This article belongs to the Special Issue Distributed Energy Generation and Smart Grid

DOI 10.11648/j.ijepe.s.2014030602.11
Page(s) 1-6
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), 2014. Published by Science Publishing Group

Keywords

Solar Photovoltaic Power Generation, Insolation, Weather Patterns, Probability of Precipitation, Regression

References
[1] A. Molderink, V. Bakker, M. G. C. Bosman, J. L. Hurink, and G. J. M. Smit, "Management and Control of Domestic Smart Grid Technology," IEEE Trans. Smart Grid, Vol. 1, No. 2, September 2010, pp. 109-119.
[2] H. Kanchev, D. Lu, F. Colas, V. Lazarov, and B. Francois, “Energy Management and Operational Planning of a Microgrid With a PV-Based Active Generator for Smart Grid Applications,” IEEE Trans. Ind. Electronics, Vol. 58, No. 10, Oct. 2011, pp. 4583-4592.
[3] K. Yoshimi, et al., “Practical Storage and Utilization of Household Photovoltaic Energy by Electric Vehicle Battery,” presented at IEEE 2012 Innovative Smart Grid Technologies Conference, Washington DC, Jan. 2012.
[4] M. Kolhe, "Techno-Economic Optimum Sizing of a Stand-Alone Solar Photovoltaic System," IEEE Trans. Energy Conversion, Vol. 24, No. 2, June 2009, pp.511-519.
[5] T. Hiyama and K. Kitabayashi, “Neural network based estimation of maximum power generation from PV module using environmental information,” IEEE Transactions on Energy Conversion, Vol. 12, No. 3, Sept. 1997, pp. 241 - 247.
[6] A. Mellit, A.H. Arab, N. Khorissi,; H. Salhi, “An ANFIS-based Forecasting for Solar Radiation Data from Sunshine Duration and Ambient Temperature,” IEEE 2007 Power Engineering Society General Meeting, June 2007, pp. 1-6.
[7] E. Lorenz, J. Hurka, D. Heinemann, and H.G. Beyer, “Irradiance Forecasting for the Power Prediction of Grid-Connected Photovoltaic Systems,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 2, No. 1, March 2009, pp. 2 - 10.
[8] C. Tao, S. Duan, and C. Chen, “Forecasting power output for grid-connected photovoltaic power system without using solar radiation measurement,” IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG), 2010 2, June 2010, pp. 773 - 777.
[9] Japan Meteorological Agency web site: http://www.jma.go.jp/
[10] T. Niimura, et al., “Profiling Residential PV Output based on Weekly Weather Forecast for Home Energy Management System,” presented at IEEE 2012 Power Engineering General Meeting, San Diego, USA, July 2012. .
[11] National Weather Service of USA, "Is It Going to Rain Today? Understanding The Weather Forecast." [Online] Available: http://www.utexas.edu/depts/grg/kimmel/nwsforecasts.html
[12] UK Met Office, The science of 'probability of precipitation, [Online] Available: http://www.metoffice.gov.uk/news/ in-depth/science-behind-probability-of-precipitation.
[13] New Energy and Industrial Technology Development Organization (NEDO) of Japan, Standard Data for Photovoltaic Power Generation (MET-PV3). [Online] Available: http://www.nedo.go.jp/library/ shiryou_application.html
[14] ForecastWatch.com, Weather forecast accuracy details for US Cities, Intellovations. [Online] Available: http://www.forecastadvisor.com/
[15] Ibid., Analysis of Short-Term Probability of Precipitation Forecasts. [Online] Available: http://www.forecastwatch.com/static/Short_Term_POP_Accuracy_2007.pdf
Cite This Article
  • APA Style

    Takahide Niimura, Noriaki Sakamoto, Kazuhiro Ozawa. (2014). Estimating Hourly Profiles of Insolation based on Weekly Weather Forecast. International Journal of Energy and Power Engineering, 3(6-2), 1-6. https://doi.org/10.11648/j.ijepe.s.2014030602.11

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    ACS Style

    Takahide Niimura; Noriaki Sakamoto; Kazuhiro Ozawa. Estimating Hourly Profiles of Insolation based on Weekly Weather Forecast. Int. J. Energy Power Eng. 2014, 3(6-2), 1-6. doi: 10.11648/j.ijepe.s.2014030602.11

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    AMA Style

    Takahide Niimura, Noriaki Sakamoto, Kazuhiro Ozawa. Estimating Hourly Profiles of Insolation based on Weekly Weather Forecast. Int J Energy Power Eng. 2014;3(6-2):1-6. doi: 10.11648/j.ijepe.s.2014030602.11

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  • @article{10.11648/j.ijepe.s.2014030602.11,
      author = {Takahide Niimura and Noriaki Sakamoto and Kazuhiro Ozawa},
      title = {Estimating Hourly Profiles of Insolation based on Weekly Weather Forecast},
      journal = {International Journal of Energy and Power Engineering},
      volume = {3},
      number = {6-2},
      pages = {1-6},
      doi = {10.11648/j.ijepe.s.2014030602.11},
      url = {https://doi.org/10.11648/j.ijepe.s.2014030602.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.s.2014030602.11},
      abstract = {In this paper, the authors present a simple procedure of estimating weekly profiles of insolation for photovoltaic (PV) power generation output of a roof-top PV system. The model is based on the historical data of solar insolation and weather conditions. Weather conditions are classified into representative patterns such as sunny, cloudy, and rainy, and corresponding hourly profile of insolation is obtained as the most likely values under each weather condition. The system uses the text weather forecast and the probability of precipitation information as input to obtain the estimated weekly profile of insolation. From the results presented here it is shown that such a simple profile can be useful for rating the storage batteries and scheduling electric vehicle charging to better utilize the PV-generated electricity.},
     year = {2014}
    }
    

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  • TY  - JOUR
    T1  - Estimating Hourly Profiles of Insolation based on Weekly Weather Forecast
    AU  - Takahide Niimura
    AU  - Noriaki Sakamoto
    AU  - Kazuhiro Ozawa
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    PY  - 2014
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    DO  - 10.11648/j.ijepe.s.2014030602.11
    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  - 1
    EP  - 6
    PB  - Science Publishing Group
    SN  - 2326-960X
    UR  - https://doi.org/10.11648/j.ijepe.s.2014030602.11
    AB  - In this paper, the authors present a simple procedure of estimating weekly profiles of insolation for photovoltaic (PV) power generation output of a roof-top PV system. The model is based on the historical data of solar insolation and weather conditions. Weather conditions are classified into representative patterns such as sunny, cloudy, and rainy, and corresponding hourly profile of insolation is obtained as the most likely values under each weather condition. The system uses the text weather forecast and the probability of precipitation information as input to obtain the estimated weekly profile of insolation. From the results presented here it is shown that such a simple profile can be useful for rating the storage batteries and scheduling electric vehicle charging to better utilize the PV-generated electricity.
    VL  - 3
    IS  - 6-2
    ER  - 

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Author Information
  • Faculty of Economics, Hosei University, Machida, Japan

  • Faculty of Economics, Hosei University, Machida, Japan

  • Faculty of Economics, Hosei University, Machida, Japan

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