Research on Time-of-use Electricity Price Model Based on Hierarchical Clustering-Price Elasticity Theory

Dong Jun; Wang Pei; Palidan Ainiwaer; Nie Shilin

doi:doi:10.11648/j.epes.20190804.12

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Research on Time-of-use Electricity Price Model Based on Hierarchical Clustering-Price Elasticity Theory

Dong Jun, Wang Pei, Palidan Ainiwaer, Nie Shilin

Published in American Journal of Electrical Power and Energy Systems (Volume 8, Issue 4)

Received: 10 July 2019 Accepted: 3 August 2019 Published: 15 August 2019

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Abstract

The peak-valley time-of-use electricity price can reduce the peak-valley difference of the power system, improve the load factor and operational reliability of the power system, and bring huge economic and social benefits. With the continuous development of society, the resident load will gradually become the main component of the power demand response. Therefore, studying the changes of residential load under the time-of-use electricity price policy is of great significance for the grid companies to better develop demand-side management strategies and carry out load forecasting work. Firstly, this paper combines fuzzy mathematics theory with hierarchical clustering algorithm to divide the peak-to-valley period of the resident load, which ensures the accuracy of the peak-valley period segmentation. Then the load response curve of residents under the condition of time-of-use electricity price is obtained using the electricity demand price elasticity matrix based on the electricity-electricity price elasticity theory. The results show that the time-of-use electricity price policy can motivate users to change their electricity consumption behavior and achieve the effect of peak-cutting and valley filling. The effectiveness of the proposed model and method is verified by numerical simulation. The results show that the time-of-use electricity price policy can motivate users to change their electricity consumption behavior and achieve the effect of peak-cutting and valley filling. The effectiveness of the proposed model and method is verified by numerical simulation.

Published in	American Journal of Electrical Power and Energy Systems (Volume 8, Issue 4)
DOI	10.11648/j.epes.20190804.12
Page(s)	95-103
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), 2019. Published by Science Publishing Group

Keywords

Hierarchical Clustering, Price Elasticity Matrix, Time Division, Time-of-use Tariff

References

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[3]	Ruan Wenjun, Wang Beibei, Li Yang, et al. [J]. Research on User Response Behavior under Peak-Valley Time-of-Use Price [J]. Power Grid Technology, 2012, 36 (7): 86-93.
[4]	Liu Yan, Tan Zhongfu, Qi Jianxun. Optimal model of TOU tariff design in peak and valley [J]. China Management Science, 2005, 13 (5): 87-92.
[5]	Goran Strbac. Demand side management: Benefits and challenges [J]. Energy Policy, 2008, 36 (12): 4419-4426.
[6]	Tang Yudong, Song Hongkun, Hu Funian, etal. Inves-tigation on TOU pricing principles [C]. Transmission and Distribution Conference and Exhibition: Dalian: IEEE/PES, 2005: 1-9.
[7]	Shu Hongchun, Dong Jun, Wu Shuijun, et al. Preliminary study on the implementation of Time-of-Use tariff in peak and valley in sales-side industries [J]. Power system automation, 2006, 30 (14): 36-40.
[8]	Tang Jie, Ren Zhen, Chen Liang, et al. A new peak-valley time-of-use pricing model and its simulation strategy [J]. Power automation equipment, 2006, 26 (8): 1-4.
[9]	Zhou Bo, Wang Bo, Gao Song and Dai Rui. Time-sharing tariff model based on user response [J]. Smart grid, 2016, (03): 307-311.
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APA Style

Dong Jun, Wang Pei, Palidan Ainiwaer, Nie Shilin. (2019). Research on Time-of-use Electricity Price Model Based on Hierarchical Clustering-Price Elasticity Theory. American Journal of Electrical Power and Energy Systems, 8(4), 95-103. https://doi.org/10.11648/j.epes.20190804.12

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ACS Style

Dong Jun; Wang Pei; Palidan Ainiwaer; Nie Shilin. Research on Time-of-use Electricity Price Model Based on Hierarchical Clustering-Price Elasticity Theory. Am. J. Electr. Power Energy Syst. 2019, 8(4), 95-103. doi: 10.11648/j.epes.20190804.12

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AMA Style

Dong Jun, Wang Pei, Palidan Ainiwaer, Nie Shilin. Research on Time-of-use Electricity Price Model Based on Hierarchical Clustering-Price Elasticity Theory. Am J Electr Power Energy Syst. 2019;8(4):95-103. doi: 10.11648/j.epes.20190804.12

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@article{10.11648/j.epes.20190804.12,
  author = {Dong Jun and Wang Pei and Palidan Ainiwaer and Nie Shilin},
  title = {Research on Time-of-use Electricity Price Model Based on Hierarchical Clustering-Price Elasticity Theory},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {8},
  number = {4},
  pages = {95-103},
  doi = {10.11648/j.epes.20190804.12},
  url = {https://doi.org/10.11648/j.epes.20190804.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20190804.12},
  abstract = {The peak-valley time-of-use electricity price can reduce the peak-valley difference of the power system, improve the load factor and operational reliability of the power system, and bring huge economic and social benefits. With the continuous development of society, the resident load will gradually become the main component of the power demand response. Therefore, studying the changes of residential load under the time-of-use electricity price policy is of great significance for the grid companies to better develop demand-side management strategies and carry out load forecasting work. Firstly, this paper combines fuzzy mathematics theory with hierarchical clustering algorithm to divide the peak-to-valley period of the resident load, which ensures the accuracy of the peak-valley period segmentation. Then the load response curve of residents under the condition of time-of-use electricity price is obtained using the electricity demand price elasticity matrix based on the electricity-electricity price elasticity theory. The results show that the time-of-use electricity price policy can motivate users to change their electricity consumption behavior and achieve the effect of peak-cutting and valley filling. The effectiveness of the proposed model and method is verified by numerical simulation. The results show that the time-of-use electricity price policy can motivate users to change their electricity consumption behavior and achieve the effect of peak-cutting and valley filling. The effectiveness of the proposed model and method is verified by numerical simulation.},
 year = {2019}
}

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TY  - JOUR
T1  - Research on Time-of-use Electricity Price Model Based on Hierarchical Clustering-Price Elasticity Theory
AU  - Dong Jun
AU  - Wang Pei
AU  - Palidan Ainiwaer
AU  - Nie Shilin
Y1  - 2019/08/15
PY  - 2019
N1  - https://doi.org/10.11648/j.epes.20190804.12
DO  - 10.11648/j.epes.20190804.12
T2  - American Journal of Electrical Power and Energy Systems
JF  - American Journal of Electrical Power and Energy Systems
JO  - American Journal of Electrical Power and Energy Systems
SP  - 95
EP  - 103
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20190804.12
AB  - The peak-valley time-of-use electricity price can reduce the peak-valley difference of the power system, improve the load factor and operational reliability of the power system, and bring huge economic and social benefits. With the continuous development of society, the resident load will gradually become the main component of the power demand response. Therefore, studying the changes of residential load under the time-of-use electricity price policy is of great significance for the grid companies to better develop demand-side management strategies and carry out load forecasting work. Firstly, this paper combines fuzzy mathematics theory with hierarchical clustering algorithm to divide the peak-to-valley period of the resident load, which ensures the accuracy of the peak-valley period segmentation. Then the load response curve of residents under the condition of time-of-use electricity price is obtained using the electricity demand price elasticity matrix based on the electricity-electricity price elasticity theory. The results show that the time-of-use electricity price policy can motivate users to change their electricity consumption behavior and achieve the effect of peak-cutting and valley filling. The effectiveness of the proposed model and method is verified by numerical simulation. The results show that the time-of-use electricity price policy can motivate users to change their electricity consumption behavior and achieve the effect of peak-cutting and valley filling. The effectiveness of the proposed model and method is verified by numerical simulation.
VL  - 8
IS  - 4
ER  -

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Author Information

Dong Jun

School of Economics and Management, North China Electric Power University, Beijing, China
Wang Pei

School of Economics and Management, North China Electric Power University, Beijing, China
Palidan Ainiwaer

School of Economics and Management, North China Electric Power University, Beijing, China
Nie Shilin

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

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Plain Text BibTeX RIS

APA Style

Dong Jun, Wang Pei, Palidan Ainiwaer, Nie Shilin. (2019). Research on Time-of-use Electricity Price Model Based on Hierarchical Clustering-Price Elasticity Theory. American Journal of Electrical Power and Energy Systems, 8(4), 95-103. https://doi.org/10.11648/j.epes.20190804.12

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ACS Style

Dong Jun; Wang Pei; Palidan Ainiwaer; Nie Shilin. Research on Time-of-use Electricity Price Model Based on Hierarchical Clustering-Price Elasticity Theory. Am. J. Electr. Power Energy Syst. 2019, 8(4), 95-103. doi: 10.11648/j.epes.20190804.12

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AMA Style

Dong Jun, Wang Pei, Palidan Ainiwaer, Nie Shilin. Research on Time-of-use Electricity Price Model Based on Hierarchical Clustering-Price Elasticity Theory. Am J Electr Power Energy Syst. 2019;8(4):95-103. doi: 10.11648/j.epes.20190804.12

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@article{10.11648/j.epes.20190804.12,
  author = {Dong Jun and Wang Pei and Palidan Ainiwaer and Nie Shilin},
  title = {Research on Time-of-use Electricity Price Model Based on Hierarchical Clustering-Price Elasticity Theory},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {8},
  number = {4},
  pages = {95-103},
  doi = {10.11648/j.epes.20190804.12},
  url = {https://doi.org/10.11648/j.epes.20190804.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20190804.12},
  abstract = {The peak-valley time-of-use electricity price can reduce the peak-valley difference of the power system, improve the load factor and operational reliability of the power system, and bring huge economic and social benefits. With the continuous development of society, the resident load will gradually become the main component of the power demand response. Therefore, studying the changes of residential load under the time-of-use electricity price policy is of great significance for the grid companies to better develop demand-side management strategies and carry out load forecasting work. Firstly, this paper combines fuzzy mathematics theory with hierarchical clustering algorithm to divide the peak-to-valley period of the resident load, which ensures the accuracy of the peak-valley period segmentation. Then the load response curve of residents under the condition of time-of-use electricity price is obtained using the electricity demand price elasticity matrix based on the electricity-electricity price elasticity theory. The results show that the time-of-use electricity price policy can motivate users to change their electricity consumption behavior and achieve the effect of peak-cutting and valley filling. The effectiveness of the proposed model and method is verified by numerical simulation. The results show that the time-of-use electricity price policy can motivate users to change their electricity consumption behavior and achieve the effect of peak-cutting and valley filling. The effectiveness of the proposed model and method is verified by numerical simulation.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Research on Time-of-use Electricity Price Model Based on Hierarchical Clustering-Price Elasticity Theory
AU  - Dong Jun
AU  - Wang Pei
AU  - Palidan Ainiwaer
AU  - Nie Shilin
Y1  - 2019/08/15
PY  - 2019
N1  - https://doi.org/10.11648/j.epes.20190804.12
DO  - 10.11648/j.epes.20190804.12
T2  - American Journal of Electrical Power and Energy Systems
JF  - American Journal of Electrical Power and Energy Systems
JO  - American Journal of Electrical Power and Energy Systems
SP  - 95
EP  - 103
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20190804.12
AB  - The peak-valley time-of-use electricity price can reduce the peak-valley difference of the power system, improve the load factor and operational reliability of the power system, and bring huge economic and social benefits. With the continuous development of society, the resident load will gradually become the main component of the power demand response. Therefore, studying the changes of residential load under the time-of-use electricity price policy is of great significance for the grid companies to better develop demand-side management strategies and carry out load forecasting work. Firstly, this paper combines fuzzy mathematics theory with hierarchical clustering algorithm to divide the peak-to-valley period of the resident load, which ensures the accuracy of the peak-valley period segmentation. Then the load response curve of residents under the condition of time-of-use electricity price is obtained using the electricity demand price elasticity matrix based on the electricity-electricity price elasticity theory. The results show that the time-of-use electricity price policy can motivate users to change their electricity consumption behavior and achieve the effect of peak-cutting and valley filling. The effectiveness of the proposed model and method is verified by numerical simulation. The results show that the time-of-use electricity price policy can motivate users to change their electricity consumption behavior and achieve the effect of peak-cutting and valley filling. The effectiveness of the proposed model and method is verified by numerical simulation.
VL  - 8
IS  - 4
ER  -

Copy | Download