Research on Tiered Tap Electricity Price

Abstract:

Under the condition of global energy crisis and environmental degradation, the electric power industry which supports the development of economy and society is facing unprecedented challenges and opportunities. There is no doubt that we should save energy and decrease the emission. A method is proposed in this paper to determine the electricity price and consumption based on the early warning mechanism and the penalty function. Firstly, the analysis of the tiered tap electricity price without any constraints based on probability is introduced. Then, we take the early warning mechanism into consideration so that the consumers can be aware of the electricity consumption clearly and modify their electricity consumption according to their own economic conditions. Thirdly, we add tier tap price with the penalty function, which makes the electricity price become a variate and more useful to encourage consumers to save energy. Finally, we give an example to illustrate the effectiveness of the models built in this paper.

• Periodical: Applied Mechanics and Materials (Volumes 448-453)
• Pages: 4285-4291
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.448-453.4285
• Online since: October 2013
• Authors: Xin Zhang, Qin Zhen Huang*
• Keywords: Early Warning Mechanism, Penalty Function Method, Tiered Pricing

References

[1] C. zhang, Suggestions and Blueprint of China's Multi-grade Electricity Pricing System, Sino-Global Energy, vol. 05, p.1–6, (2010).

[2] J.A.P. , Lopes and F.J. Soares, Integration of electric vehicles in the electric power system, Proceedings of the IEEE, vol. 99, p.168 – 183, (2011).

[3] Y. Li, Q. Luo, Y. Song, and C. Lei, Study on the tier tap determining of basic residential electricity consumption based on demand response, IEEE ASSP Magazine, vol. 4, p.1–5, (2012).

DOI: 10.1109/appeec.2012.6307455

[4] N. Ding, J. Wu, and Y. Zou., Research of peak and valley time period partition approach and TOU price on DSM, Automation of Electric Power Systems, vol. 25, p.9–12, (2001).

[5] F. Hu, Y. Tang, and Y. Zou., The mechanism of the TOU price based on the bi-linkage of purchase and sale prices, Proceedings of CSEE, vol. 27, p.61–66, (2007).

[6] Q. Zhang, X. Wang, J. Wang, and L. Liu, Decision model analysis of season-of-use price, Automation of Electric Power Systems, vol. 31, p.7–11, (2007).

[7] Y. Xiao, H. Wang, and J. Yang, Thinking on multigrade price of residents in shanghai, Prices Monthly, p.15–18, (2009).

[8] R. G. Bittle, R. Valesano, and G. Thaler, The effects of daily cost feedback on residential electricity consumption, SAGE journals, vol. 3, p.187–2012, (2001).

DOI: 10.1177/014544557932004

[9] H. Huang, L. Zhang, H. Qiao, and N. Du, A method to determine grade-shaped electricity consumption levels for residential area based on variable-density clustering, Power System Technology, p.111–116, (2010).

[10] S. Yu and J. Xu, Research on multigrade price of living electricity for residents in Zhejiang, Popular Utilization of Electricity, vol. 6, p.9–11, (2008).