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Electricity-gas-heat energy storage collaborative planning method and system considering wind power uncertainty

An uncertain, thermal energy storage technology, applied in wind power generation, electrical components, information technology support systems, etc., can solve the problems of not considering the influence of wind power, neglect of coupling characteristics, incomplete interaction, etc., to simplify the interweaving of source and load relationship effect

Active Publication Date: 2021-05-28
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in integrated energy systems, the coupling characteristics of electricity, heat, and gas are usually ignored, and some studies have not considered the impact of wind power uncertainty
[0006] So far, few studies have focused on the coordinated planning of electricity, gas, and thermal multi-energy storage considering wind power and network constraints; at the same time, the research at this stage is not comprehensive on the interaction between different energy storage methods

Method used

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  • Electricity-gas-heat energy storage collaborative planning method and system considering wind power uncertainty
  • Electricity-gas-heat energy storage collaborative planning method and system considering wind power uncertainty
  • Electricity-gas-heat energy storage collaborative planning method and system considering wind power uncertainty

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Embodiment 1

[0065] In one or more embodiments, a collaborative planning method for electric-gas-thermal energy storage considering the uncertainty of wind power is disclosed, and a collaborative planning model for multiple types of electric-gas-thermal energy storage is established; The goal is to solve the model and obtain the optimal planning result considering the uncertainty of the wind field. By comparing the total cost and energy storage configuration results in different scenarios, the interaction among multi-energy storage is analyzed.

[0066] Specifically include the following steps:

[0067] Step S101: classify and process wind power historical data according to seasonality, and obtain a limited set of typical scenarios with set probabilities;

[0068] Specifically, in order to ensure the accuracy of the wind power stochastic model, it is necessary to conduct a large amount of wind power data and obtain typical scenarios with a certain probability. Scenario method such as f...

Embodiment 2

[0154] In one or more embodiments, an electric-gas-thermal energy storage collaborative planning system considering wind power uncertainty is disclosed, including:

[0155] The scenario division module is used to classify and process wind power historical data according to seasonality, and obtain a limited set of typical scenarios with set probabilities;

[0156] The collaborative planning module is used to consider the energy conversion relationship constraints of electric loads, gas loads and thermal loads for each scenario, and to establish a collaborative planning model of electric-gas-thermal multi-type energy storage with the goal of economic optimization;

[0157] The planning result output module is used to solve the model to obtain the optimal planning result considering the uncertainty of the wind field.

[0158] The specific implementation manners of the above modules have been described in the first embodiment, and will not be repeated here.

Embodiment 3

[0160] In one or more embodiments, a terminal device is disclosed, which includes a processor and a computer-readable storage medium, the processor is used to implement instructions; the computer-readable storage medium is used to store multiple instructions, and the instructions are suitable for The processor loads and executes the electric-gas-thermal energy storage collaborative planning method considering wind power uncertainty described in the first embodiment.

[0161] In some other embodiments, a computer-readable storage medium is disclosed, in which a plurality of instructions are stored, and the instructions are suitable for being loaded by a processor of a terminal device and executing the wind power uncertainty consideration described in Embodiment 1. Electric-gas-thermal energy storage collaborative planning method.

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Abstract

The invention discloses an electricity-gas-heat energy storage collaborative planning method and system considering wind power uncertainty. The method comprises the steps: carrying out the classification processing of wind power historical data according to seasons, and obtaining a finite number of typical scene sets with a set probability; for each scene, considering energy conversion relation constraints of an electric load, a gas load and a thermal load, and establishing an electric-gas-thermal multi-type energy storage collaborative planning model by taking economic optimization as a target; and solving the model to obtain an optimal planning result considering the uncertainty of the wind field. According to the method, the wind power uncertainty model is established by adopting a scene method from the time dimension and by taking seasons as scene distinction. A scene in one year is decomposed into typical scenes in different seasons. In a wind power typical scene, economy and flexibility of the multi-energy storage planning method are verified.

Description

technical field [0001] The invention relates to the technical field of comprehensive energy storage optimization, in particular to an electric-gas-thermal energy storage collaborative planning method and system considering the uncertainty of wind power. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] Renewable energy is developing rapidly, and wind power, as a typical renewable energy, has made a significant contribution to improving environmental pollution. However, the integration of large-scale and uncertain wind power poses great challenges to the integrated energy system. Due to the anti-peaking characteristics of wind power, it is difficult for the system to accept more wind power. As a flexible resource, energy storage can effectively increase the consumption of renewable energy. It can alleviate energy demand during peak periods ...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q10/04G06Q50/06G06F17/11G06F17/16G06F17/18H02J3/00H02J3/28H02J3/38H02J3/48
CPCG06Q10/06315G06Q10/04G06Q50/06G06F17/11G06F17/16G06F17/18H02J3/008H02J3/381H02J3/48H02J3/28H02J2203/20H02J2300/28Y04S10/50Y02E70/30Y02E10/76
Inventor 王成福李博文董晓明
Owner SHANDONG UNIV
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