Park comprehensive energy system low-carbon operation method based on Q learning

A technology of integrated energy system and operation method, applied in the field of low-carbon operation of park integrated energy system based on Q-learning, capable of solving problems such as non-linearity and non-convex solution model

Active Publication Date: 2021-03-30
STATE GRID FUJIAN POWER ELECTRIC CO ECONOMIC RES INST +1
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, there is a strong coupling in the conversion of energy in PIES, which may make the solution model of the PIES operation stra

Method used

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  • Park comprehensive energy system low-carbon operation method based on Q learning
  • Park comprehensive energy system low-carbon operation method based on Q learning
  • Park comprehensive energy system low-carbon operation method based on Q learning

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Embodiment Construction

[0096] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0097] It should be pointed out that the following detailed description is exemplary and is intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0098] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combina...

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Abstract

The invention relates to a park comprehensive energy system low-carbon operation method based on Q learning. The method comprises the steps: establishing a model PIES of a park comprehensive energy system based on the concept of an energy hub; considering the treatment cost of the PIES carbon dioxide emission, and establishing a mathematical optimization model of a PIES low-carbon economic operation strategy by taking the minimum daily operation cost of the PIES as a target; establishing a Markov decision process MDP corresponding to the optimization model, and correspondingly defining a statespace, an action space and a reward function of an MDP problem; and solving the MDP problem by adopting an improved Q learning algorithm, and carrying out initialization improvement on the Q value table by utilizing a reward function. According to the invention, low-carbon operation of the park comprehensive energy system can be realized.

Description

technical field [0001] The invention relates to the technical field of low-carbon operation of power systems, in particular to a method for low-carbon operation of park comprehensive energy systems based on Q-learning. Background technique [0002] With the increasingly prominent problems of energy shortage and environmental pollution, how to achieve sustainable development by means of energy conservation and emission reduction, improvement of energy utilization rate, and increase of the proportion of new energy sources is a more concerned issue in current research. The Park-level Integrated Energy System (PIES) came into being in this context. PIES is directly oriented to end energy users, and uses various energy conversion devices such as photovoltaic power generation, combined heat and power, and refrigerators to convert solar energy into clean energy. Energy is transformed into the form of energy required by users, thereby improving energy utilization and increasing the ...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06
CPCG06Q10/04G06Q10/06375G06Q50/06Y04S10/50
Inventor 郑洁云张林垚吴桂联宋倩芸陈浩林婷婷倪识远胡志坚陈志翁菖宏
Owner STATE GRID FUJIAN POWER ELECTRIC CO ECONOMIC RES INST
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