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.
Highlights
With the development of smart grids, demand response has gradually received people's attention
The time-of-use price policy refers to motivating the users to change the power consumption behavior through the price signal to achieve the effect of load transfer and peak-filling, which plays an important role in ensuring the safe operation of the power grid and improving the reliability of the power system [3]
With the continuous development of the economy and society and improvement of people's living standard, the wide application of various household appliances has increased the demand for electricity consumption of residents
Summary
With the development of smart grids, demand response has gradually received people's attention. Liu Yan and Zhongfu Tan et al [4] have established a user response model for time-of-use electricity price with reference to the response model of general users, and proposed a method for time-of-use electricity prices based on different time periods. They only made a rough division based on other literature's experience in peak-to-valley research, and did not give a specific method of dividing the peak-to-valley period. A method for segmentation of peak-to-valley period of residential residents' load curve is presented in this paper, and the clustering of time points at 96 time points is considered, which has a fine time granularity and enriches the theoretical study of residential load participation in electricity price response
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