Wind-solar-storage complementary system demand response strategy based on correlation analysis

Abstract

A wind-solar-storage complementary system demand response strategy based on correlation analysis comprises the following steps: selecting a load tracking coefficient to analyze the correlation betweenvarious power supply signals and loads in a wind-solar-storage complementary system; establishing a demand response basic theoretical model based on a demand price elasticity theory; establishing a wind-solar-storage complementary demand response optimization model based on correlation analysis; and solving the established wind-solar-storage complementary demand response optimization model by adopting a particle swarm algorithm. An electricity price strategy is used as a random particle, and an optimal real-time electricity price strategy is solved by continuously optimizing the indexes including the load peak-valley difference, the average electricity price difference and the load tracking coefficient after the demand response, so that a load curve is matched with a wind-solar-storage complementary power generation curve to the maximum extent, and the purpose of fully consuming the output of the wind power on the power generation side is achieved. According to the invention, full consumption of new energy on the power generation side can be realized.

Description

technical field [0001] The invention relates to the technical field of demand response for a wind-solar-storage complementary power generation system, in particular to a demand response strategy for a wind-solar-storage complementary system based on correlation analysis. Background technique [0002] The rapid development of clean energy has eased the increasingly severe environmental problems and energy crisis, but it has also brought many problems. New energy sources such as wind power and photovoltaics are easily affected by the external environment, resulting in fluctuations and randomness in their power generation, which poses a huge challenge to the consumption of clean energy. [0003] Aiming at the technology of multi-energy complementary system to promote new energy consumption, the current research is mainly to carry out scheduling optimization on the side of multi-energy complementary joint system to overcome the uncertainty of new energy power generation, and use...

AI Technical Summary

Problems solved by technology

Secondly, the consideration of the demand response model is not comprehensive enough, and it fails to fully include the factors that have the greatest impact on users

At the same time, the general model aims at the best economic benefits of users or power grids, and seldom considers the interrelationship and influence of load changes and multi-energy complementary system power generation, and cannot fully reflect the improvement of energy consumption.

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