Multi-energy microgrid optimal configuration method based on deep joint generation of source-load-temperature scenarios

A technology of scene depth and optimized configuration, applied in design optimization/simulation, resources, instruments, etc., can solve the problem that the scene is difficult to cover the potential demand of extreme energy consumption, so as to improve the economy and reliability of energy supply, and improve the reliability of energy supply. The effect of strong adaptability and applicability

Active Publication Date: 2022-05-24
NORTHEAST DIANLI UNIVERSITY
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Problems solved by technology

However, most of the current research does not consider the extreme weather conditions (temperature) with less historical data, and the scenarios are limited and it is difficult to cover the potential demand for extreme energy consumption.

Method used

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  • Multi-energy microgrid optimal configuration method based on deep joint generation of source-load-temperature scenarios
  • Multi-energy microgrid optimal configuration method based on deep joint generation of source-load-temperature scenarios
  • Multi-energy microgrid optimal configuration method based on deep joint generation of source-load-temperature scenarios

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Embodiment Construction

[0059] The following takes the multi-energy microgrid as an example to illustrate an optimal configuration method of multi-energy microgrid based on the depth of source-load-temperature scenario.

[0060]An optimal configuration method of the multi-energy microgrid based on the depth of the source-load-temperature scenario of the embodiment sets three optimal configuration methods: (1) the correlation between solar irradiation and power consumption behavior is 0.0004, i.e., there is no correlation; (2) the correlation between solar irradiation and power consumption behavior is 0.2255, i.e., the maximum positive correlation; (3) the correlation between solar irradiation and electricity consumption behavior is -0.2572 users, i.e., the maximum negative correlation; (4) Users with a correlation of -0.1004 for solar irradiation and electricity consumption behavior; (5) users with a correlation of solar irradiation and electricity consumption behavior for 0.1003.

[0061] Table 1 shows ...

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Abstract

The present invention is a multi-energy micro-grid optimal configuration method based on the deep joint generation of source-load-temperature scenes, which is characterized in that it includes determining typical weather types and extreme temperature types, and carrying out source-load configuration for typical weather types and extreme weather types. ‑Temperature scene in-depth joint generation and scene reduction, establishment of multi-energy micro-grid system model, establishment of multi-energy micro-grid system optimal configuration model with the goal of the lowest total annualized cost, solves the problem of using different scene generation methods in the existing technology to carry out multiple When optimizing the configuration of the energy system, it is impossible to consider the coupling between new energy measurement and multi-energy demand side and the limited extreme scenarios that make it difficult to cover the potential demand for extreme energy consumption. It has the advantages of scientific and reasonable method, strong applicability, good effect, and can improve the economy and energy supply reliability of the multi-energy micro-grid system.

Description

Technical field [0001] The present invention relates to a multi-energy microgrid system, is a multi-energy microgrid optimization configuration method based on the depth of the source - load - temperature scenario, applied to the optimal configuration of multi-energy microgrid system. Background [0002] The coupling relationship of the equipment inside the multi-energy microgrid system is complex and non-linear, and unlike the traditional microgrid, the multi-energy microgrid system is more complex in optimizing the configuration. In addition, the main power generation equipment in the multi-energy microgrid system is mainly distributed renewable energy such as photovoltaic panels. Distributed renewable energy power generation devices are seriously affected by weather, have strong volatility and uncertainty, and there is a large mismatch in the timing of local user energy loads, which cannot meet user energy demand at all times。 And the local temperature will directly affect the...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06G06F30/20G06K9/62
CPCG06Q10/04G06Q10/06315G06Q50/06G06F30/20G06F18/23
Inventor 黄南天王文婷蔡国伟包佳瑞琦杨冬锋孔令国吴银银杨学航张祎祺张良王燕涛黄大为
Owner NORTHEAST DIANLI UNIVERSITY
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