Saturated Electricity Power Analysis Based on Logistic Curve Model

Huiru Zhao; Sen Guo; Jia Zhou; Huijuan Huo; Wanlei Xue

doi:doi:10.11648/j.ijepe.s.2014030601.11

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Saturated Electricity Power Analysis Based on Logistic Curve Model

Huiru Zhao, Sen Guo, Jia Zhou, Huijuan Huo, Wanlei Xue

Published in International Journal of Energy and Power Engineering (Volume 3, Issue 6-1)

Received: 16 July 2014 Accepted: 22 July 2014 Published: 20 August 2014

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Abstract

Power load forecasting is the foundation of urban power grid planning, and saturated electricity power is a key indicator for determining the ultimate power grid scale when performing the urban power grid planning. Taken Hubei province as the empirical example, the saturated electricity power is studied by employing Logistic curve model in this paper. Firstly, the electricity power consumption and annual maximum power load of Hubei province are forecasted; then, the saturated time and scale are determined according to the judgment criteria of electricity power saturation. The calculation result shows the electricity power of Hubei province will reach saturation at 2042-2043, and the electricity power consumption and annual maximum power load will reach to 377.89 billion kWh and 66.2499 million kW, respectively.

Published in	International Journal of Energy and Power Engineering (Volume 3, Issue 6-1) This article belongs to the Special Issue Energy Conservation and Management
DOI	10.11648/j.ijepe.s.2014030601.11
Page(s)	1-5
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

Saturated Power Load, Logistic Curve Model, Forecasting, Hubei Province

References

[1]	Cui Kai, Li Jing-ru, Zhao Biao, et al. Research on City Saturated Load and its Forecast Methods [J]. Electric Power Technologic Economics, 2008, 20(6): 34-38.
[2]	Jiang Xin-qin, Li Xi-lan. City future saturated load forecasting based model of saturated load density [J]. Journal of Fuzhou University (Natural Science Edition), 2008, 36(4): 532-536
[3]	He Yongxiu, Wu Liangqi, Dai Aiying, et al. Combined saturation load forecast model based on system dynamics and econometrics [J]. Power Demand Side Management, 2010, 12(1): 21-25.
[4]	Wang Jing, Feng Xian-shi, Guo Hong-zhen. Urban load saturation forecast based on ant cellular automata theory [J]. Electric Power, 2011, 44(7): 17-20.
[5]	Wang Fang-dong, Lin Han, Li Chuan-dong, et al. Research on Saturated Load Macroscopically Forecast Based on Saturated Situation Analysis of Economy Curve [J]. East China Electric Power, 2010, 38(10): 1485-1490.
[6]	Wang Wei, FAang Ting-ting. The application of per⁃person electricity consumption method in saturation load forecasting [J]. Power Demand Side Management, 2012, 14(1): 21-23.
[7]	Zhang Jian-ping, Liu Jie-feng, Chen Yi-dong, et al. Saturated Load Forecasting Based on Per Capita Electricity Consumption and Per Capita Electricity Load[J]. East China Electric Power, 2014, 42(4): 661-664.
[8]	Lemeshow S, Hosmer D W. A review of goodness of fit statistics for use in the development of logistic regression models [J]. American Journal of Epidemiology, 1982, 115(1): 92-106.
[9]	Mood C. Logistic regression: Why we cannot do what we think we can do, and what we can do about it [J]. European Sociological Review, 2010, 26(1): 67-82.
[10]	Liu Jiefeng. The Research of Saturation Load Analysis Techniques and its Application [D]. Shanghai: Shanghai Jiaotong University, 2013.

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APA Style

Huiru Zhao, Sen Guo, Jia Zhou, Huijuan Huo, Wanlei Xue. (2014). Saturated Electricity Power Analysis Based on Logistic Curve Model. International Journal of Energy and Power Engineering, 3(6-1), 1-5. https://doi.org/10.11648/j.ijepe.s.2014030601.11

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ACS Style

Huiru Zhao; Sen Guo; Jia Zhou; Huijuan Huo; Wanlei Xue. Saturated Electricity Power Analysis Based on Logistic Curve Model. Int. J. Energy Power Eng. 2014, 3(6-1), 1-5. doi: 10.11648/j.ijepe.s.2014030601.11

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AMA Style

Huiru Zhao, Sen Guo, Jia Zhou, Huijuan Huo, Wanlei Xue. Saturated Electricity Power Analysis Based on Logistic Curve Model. Int J Energy Power Eng. 2014;3(6-1):1-5. doi: 10.11648/j.ijepe.s.2014030601.11

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@article{10.11648/j.ijepe.s.2014030601.11,
  author = {Huiru Zhao and Sen Guo and Jia Zhou and Huijuan Huo and Wanlei Xue},
  title = {Saturated Electricity Power Analysis Based on Logistic Curve Model},
  journal = {International Journal of Energy and Power Engineering},
  volume = {3},
  number = {6-1},
  pages = {1-5},
  doi = {10.11648/j.ijepe.s.2014030601.11},
  url = {https://doi.org/10.11648/j.ijepe.s.2014030601.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.s.2014030601.11},
  abstract = {Power load forecasting is the foundation of urban power grid planning, and saturated electricity power is a key indicator for determining the ultimate power grid scale when performing the urban power grid planning. Taken Hubei province as the empirical example, the saturated electricity power is studied by employing Logistic curve model in this paper. Firstly, the electricity power consumption and annual maximum power load of Hubei province are forecasted; then, the saturated time and scale are determined according to the judgment criteria of electricity power saturation. The calculation result shows the electricity power of Hubei province will reach saturation at 2042-2043, and the electricity power consumption and annual maximum power load will reach to 377.89 billion kWh and 66.2499 million kW, respectively.},
 year = {2014}
}

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TY  - JOUR
T1  - Saturated Electricity Power Analysis Based on Logistic Curve Model
AU  - Huiru Zhao
AU  - Sen Guo
AU  - Jia Zhou
AU  - Huijuan Huo
AU  - Wanlei Xue
Y1  - 2014/08/20
PY  - 2014
N1  - https://doi.org/10.11648/j.ijepe.s.2014030601.11
DO  - 10.11648/j.ijepe.s.2014030601.11
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  - 5
PB  - Science Publishing Group
SN  - 2326-960X
UR  - https://doi.org/10.11648/j.ijepe.s.2014030601.11
AB  - Power load forecasting is the foundation of urban power grid planning, and saturated electricity power is a key indicator for determining the ultimate power grid scale when performing the urban power grid planning. Taken Hubei province as the empirical example, the saturated electricity power is studied by employing Logistic curve model in this paper. Firstly, the electricity power consumption and annual maximum power load of Hubei province are forecasted; then, the saturated time and scale are determined according to the judgment criteria of electricity power saturation. The calculation result shows the electricity power of Hubei province will reach saturation at 2042-2043, and the electricity power consumption and annual maximum power load will reach to 377.89 billion kWh and 66.2499 million kW, respectively.
VL  - 3
IS  - 6-1
ER  -

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Author Information

Huiru Zhao

School of Economics and Management, North China Electric Power University, Beijing, 102206, China
Sen Guo

School of Economics and Management, North China Electric Power University, Beijing, 102206, China
Jia Zhou

School of Economics and Management, North China Electric Power University, Beijing, 102206, China
Huijuan Huo

School of Economics and Management, North China Electric Power University, Beijing, 102206, China
Wanlei Xue

State Grid Shandong Electric Power Company, Power Economy & Technology Research Institute, Jinan City, Shandong Province, 250002, China

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Plain Text BibTeX RIS

APA Style

Huiru Zhao, Sen Guo, Jia Zhou, Huijuan Huo, Wanlei Xue. (2014). Saturated Electricity Power Analysis Based on Logistic Curve Model. International Journal of Energy and Power Engineering, 3(6-1), 1-5. https://doi.org/10.11648/j.ijepe.s.2014030601.11

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ACS Style

Huiru Zhao; Sen Guo; Jia Zhou; Huijuan Huo; Wanlei Xue. Saturated Electricity Power Analysis Based on Logistic Curve Model. Int. J. Energy Power Eng. 2014, 3(6-1), 1-5. doi: 10.11648/j.ijepe.s.2014030601.11

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AMA Style

Huiru Zhao, Sen Guo, Jia Zhou, Huijuan Huo, Wanlei Xue. Saturated Electricity Power Analysis Based on Logistic Curve Model. Int J Energy Power Eng. 2014;3(6-1):1-5. doi: 10.11648/j.ijepe.s.2014030601.11

Copy | Download

@article{10.11648/j.ijepe.s.2014030601.11,
  author = {Huiru Zhao and Sen Guo and Jia Zhou and Huijuan Huo and Wanlei Xue},
  title = {Saturated Electricity Power Analysis Based on Logistic Curve Model},
  journal = {International Journal of Energy and Power Engineering},
  volume = {3},
  number = {6-1},
  pages = {1-5},
  doi = {10.11648/j.ijepe.s.2014030601.11},
  url = {https://doi.org/10.11648/j.ijepe.s.2014030601.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.s.2014030601.11},
  abstract = {Power load forecasting is the foundation of urban power grid planning, and saturated electricity power is a key indicator for determining the ultimate power grid scale when performing the urban power grid planning. Taken Hubei province as the empirical example, the saturated electricity power is studied by employing Logistic curve model in this paper. Firstly, the electricity power consumption and annual maximum power load of Hubei province are forecasted; then, the saturated time and scale are determined according to the judgment criteria of electricity power saturation. The calculation result shows the electricity power of Hubei province will reach saturation at 2042-2043, and the electricity power consumption and annual maximum power load will reach to 377.89 billion kWh and 66.2499 million kW, respectively.},
 year = {2014}
}

Copy | Download

TY  - JOUR
T1  - Saturated Electricity Power Analysis Based on Logistic Curve Model
AU  - Huiru Zhao
AU  - Sen Guo
AU  - Jia Zhou
AU  - Huijuan Huo
AU  - Wanlei Xue
Y1  - 2014/08/20
PY  - 2014
N1  - https://doi.org/10.11648/j.ijepe.s.2014030601.11
DO  - 10.11648/j.ijepe.s.2014030601.11
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  - 5
PB  - Science Publishing Group
SN  - 2326-960X
UR  - https://doi.org/10.11648/j.ijepe.s.2014030601.11
AB  - Power load forecasting is the foundation of urban power grid planning, and saturated electricity power is a key indicator for determining the ultimate power grid scale when performing the urban power grid planning. Taken Hubei province as the empirical example, the saturated electricity power is studied by employing Logistic curve model in this paper. Firstly, the electricity power consumption and annual maximum power load of Hubei province are forecasted; then, the saturated time and scale are determined according to the judgment criteria of electricity power saturation. The calculation result shows the electricity power of Hubei province will reach saturation at 2042-2043, and the electricity power consumption and annual maximum power load will reach to 377.89 billion kWh and 66.2499 million kW, respectively.
VL  - 3
IS  - 6-1
ER  -

Copy | Download