Electricity pricing method based on multi-time-scale demand response model

Abstract

The utility model relates to an electricity pricing method based on a multi-time-scale demand response model, and the method includes the steps of constructing the multi-time-scale demand response model, initializing a system, and obtaining original data and required data for optimization; establishing a model of the electricity pricing method, and determining an objective function, an optimization variable and a constraint condition; and finally, using the particle swarm optimization algorithm as the electricity pricing model algorithm. The modeling of the invention considers consumer psychology, and combines a long-term demand model and a short-term demand model together through a demand elasticity matrix to establish a demand side response model with multiple time scales. The inventionprovides a new idea for demand response modeling, and provides a reference for the formulation of electricity price.

Description

technical field [0001] The invention relates to an electricity price pricing method oriented to demand side response modeling. Background technique [0002] In order to solve the problems of power supply and demand mismatch and load peaks in the current power system, further optimize the structure and operation mode of the power system, and meet people's urgent needs for better power supply, my country has launched a new round of power reform. The No. 9 document of Xindiangai puts forward the power operation mode of "controlling the middle and releasing the two ends". By introducing a competition mechanism on the electricity sales side, the electricity price can reflect the relationship between cost and supply and demand, and the demand side can respond effectively in terms of policies and mechanisms. It provides a better implementation space, so that it can better solve the problems in the power system. [0003] There are many problems in the existing power system planning...

AI Technical Summary

Problems solved by technology

First of all, the short-lived huge demand for electricity during peak hours has caused a lot of waste of resources

The construction of power infrastructure at this stage is usually determined according to the peak of power demand, and a certain space needs to be reserved for the growth of power demand, resulting in a large waste of resources at peak times; secondly, when the maximum price set by the government is already lower than the marginal supply cost When people don't save resources

In this case, the supply side becomes passive, and it is better to choose to increase the supply than to reduce the demand.

Finally, distributed power sources such as wind power, photovoltaics, tides, and biomass energy are connected to the grid. Due to their own volatility, randomness, and intermittent nature, the peak-to-valley difference will increase after grid connection, reducing the efficiency of power transmission and the quality of power. will also be affected

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