Time-of-use electricity price pricing method considering key indexes and yield management

Abstract

The invention relates to a time-of-use electricity price pricing method considering key indexes and yield management. The method includes the following steps: establishing a response function of an electricity price and an electricity quantity according to historical data; obtaining the electricity price of each time period according to set values of the key indexes; calculating electricity consumption distribution of each time period and the actual value of each key index; and performing closed loop feedback adjustment on the set value of each key indexes and repeating the abovementioned processes till difference between the set value and the actual value of each key index is small enough, thereby obtaining an optimal time-of-use electricity price pricing strategy. Compared with existing research, the method allows to divide one day into any number of time periods; a price demand response function is subjected to interval processing; a yield management theory and time-of-use electricity price are combined, so that calculation of electricity consumption is more scientific and reasonable. The time-of-use electricity price pricing method provided by the invention can satisfy a requirement for a proportional relation between the electricity price of each time period and the electricity quantity, and can also effectively control the total power supply volume, improves the power supply income, and guides a power load to be distributed in a balanced manner in time.

Description

technical field [0001] The invention relates to the field of electric power technology, in particular to a time-of-use electricity price pricing method considering key indicators and revenue management. Background technique [0002] The time-of-use pricing strategy is a pricing method widely used in residential electricity consumption and industrial electricity consumption. Its main advantage is to realize the reasonable distribution of electric energy in time, reduce the fluctuation of electric load, and contribute to the stability of the power grid. It is of great significance for safety and security, and it will also improve the comprehensive utilization rate of power supply system equipment. [0003] Existing studies are carried out based on different objectives and backgrounds. However, the rationality of the premise assumptions relied on by some literatures is worthy of further discussion. The following three examples can be used to illustrate: (1) The relationship fun...

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Problems solved by technology

[0003] Existing studies are carried out based on different objectives and backgrounds. However, the rationality of the premise assumptions relied on in some literatures is worthy of further discussion. The following three examples can be used to illustrate: (1) The relationship function between electricity price and electricity (such as the response matrix) The setting is not reasonable, reducing the degree of freedom of the problem

(2) There are insufficient reasons for assuming that the total electricity consumption remains constant

Pricing policy adjustments will definitely cause changes in user response, so it is normal for the total power consumption to differ from before policy adjustments

(3) It is unreasonable to presuppose the adjusted average electricity price as the annual average electricity price before adjustment, which adds additional constraints and is not conducive to the optimization of pricing schemes

In addition, the existing research rarely involves the algorithm of using specific indicators as the target and making the set value coincide with the actual value through the closed-loop feedback adjustment process, which is not conducive to the accurate and reasonable calculation of electricity consumption and power supply revenue in each period. control

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