Demand side response load analysis method based on reinforcement learning algorithm

A demand response and load technology, applied in the field of demand side response load analysis based on reinforcement learning algorithm, can solve problems such as weak control and inability to flexibly respond to power grid fluctuations during peak power consumption, so as to reduce grid fluctuations and improve safety and reliability sexual effect

Pending Publication Date: 2022-06-28
GUIZHOU WANFENG ELECTRIC POWER CO LTD +2
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Problems solved by technology

[0002] The increasing diversification of lifestyles has made people's demand for electricity more and more large, resulting in weak load control on the traditional power generation side, unable to flexibly respond to power grid fluctuations caused by peak power consumption and impact loads

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  • Demand side response load analysis method based on reinforcement learning algorithm
  • Demand side response load analysis method based on reinforcement learning algorithm
  • Demand side response load analysis method based on reinforcement learning algorithm

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Embodiment Construction

[0049] The following is further described with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0050] In this embodiment, the demand-side response load analysis method based on the reinforcement learning algorithm includes:

[0051] Obtain the information on the adjustable load on the power consumption side of the power grid, the information on the spot market of electricity, and the power generation information on the power supply side;

[0052] Access to pre-built demand response models based on user selection;

[0053] Based on the demand response model, the user load dynamic transfer problem is transformed into a discrete in...

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Abstract

The invention discloses a demand side response load analysis method based on a reinforcement learning algorithm, and the method comprises the steps: obtaining the adjustable load information of a power utilization side of a power grid, the information of an electric power spot market, the power generation information of a power supply side unit, and a pre-constructed demand response model based on user selection; based on a demand response model, converting a user load dynamic transfer problem into a discrete infinite Markov decision problem; and solving the discrete infinite Markov decision problem by adopting a Q-learning algorithm based on adjustable load information of a power utilization side of a power grid, power spot market information and unit power generation information of a power supply side, and solving to obtain an optimal load transfer scheme in which the user participates in load transfer by taking the maximum discount reward of user load transfer as a target. According to the method, demand side load response analysis is carried out based on the Q-learning theory, decision reference can be provided for users to participate in demand side load response, load control is more effectively achieved, power grid fluctuation is reduced, and power grid operation safety and reliability are improved.

Description

technical field [0001] The invention relates to the technical field of automatic dispatching of electric power systems, in particular to a demand-side response load analysis method based on a reinforcement learning algorithm. Background technique [0002] The ever-increasing diversification of lifestyles has made people’s demand for electricity greater and greater, resulting in weak load control on the traditional power generation side, unable to flexibly cope with grid fluctuations caused by peak electricity consumption and shock loads. With the application of modern advanced information and communication technologies in smart grid systems, demand response (DR) quickly responds to the mismatch between supply and demand by adjusting the flexible loads on the user side, and has become an effective method to improve grid reliability and reduce energy costs. In the case of load-side participation under demand response, an effective intelligent control method is urgently needed ...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/06H02J3/00G06N20/00
CPCG06Q10/06315G06Q50/06H02J3/003G06N20/00
Inventor 刘启斌魏杰陈征
Owner GUIZHOU WANFENG ELECTRIC POWER CO LTD
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