Time-of-use electricity price determining method based on load characteristic classification

Abstract

The invention discloses a time-of-use electricity price determining method based on load characteristic classification. The method comprises the following steps that data standardization preprocessing is carried out; data after preprocessing are subjected to clustering analysis through a fuzzy c mean value clustering algorithm, and average power load curves of various power consumers are obtained; the power load curves of all the power consumers are divided according to peak-common-trough periods; the demand response degree is analyzed; the power utilization influence degree is analyzed; and according to the demand response degree and the power utilization influence degree of various power consumers, a time-of-use electricity price adjusting mode is determined, the adjusting principle is that the peak-trough electricity price difference ratio and the demand response degree of various power consumers are in inverse relation, and the peak-trough electricity price difference ratio and the power utilization influence degree is in direct ratio relation. Power load data are subjected to clustering analysis, power consumers are classified according to the load characteristics, time-of-use electricity price based on power consumer load characteristic classification is achieved, and important effect is achieved on traditional time-of-use electricity price adjusting.

Description

technical field [0001] The invention relates to a method for determining a time-of-use electricity price, in particular to a method for determining a time-of-use electricity price based on load characteristic classification. Background technique [0002] Judging from the current implementation of peak-valley time-of-use electricity prices in China, the policy has achieved a certain effect in shifting peaks and filling valleys, but there are still insufficient and over-responses from users. Insufficient user response will fail to achieve the purpose of shifting peaks and filling valleys and increasing the load rate of the power grid, while excessive user response will cause peak-valley time drift or peak-valley time inversion, which will damage the interests of power companies. The reason for this phenomenon is that the classification of power users is based on demand analysis, according to the nature of power users and the needs of marketing business, and most of the time-of...

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Problems solved by technology

Therefore, different power users have different load characteristics and responses to time-of-use electricity prices, and implementin

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