Main Article Content

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.

Article Details

How to Cite
Dong Jun, Wang Pei, Ainiwaer, P., & Nie Shilin. (2019). Research on Time-of-use Electricity Price Model Based on Hierarchical Clustering-Price Elasticity Theory. Thematics Journal of Geography, 8(6), 01-23. Retrieved from https://thematicsjournals.org/index.php/tjg/article/view/8160