Multi-time-scale active and reactive coordinated optimization scheduling method and system for active power distribution network

A multi-time scale, coordinated optimization technology, applied in the field of distribution network, can solve non-optimal problems, achieve the effects of enhancing adaptability, improving scheduling accuracy, and ensuring stability

Active Publication Date: 2021-10-19
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

This will directly lead to the optimization result of the previous stage is not optimal for the next stage, especially in the stage before the set time interval of determining the output of the slow adjustment resource and the set time interval of the actual real-time stage reference value

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  • Multi-time-scale active and reactive coordinated optimization scheduling method and system for active power distribution network
  • Multi-time-scale active and reactive coordinated optimization scheduling method and system for active power distribution network
  • Multi-time-scale active and reactive coordinated optimization scheduling method and system for active power distribution network

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Embodiment 1

[0089] Such as figure 1 As shown, the active power distribution network multi-time scale active and reactive power coordination optimization scheduling method provided in this embodiment includes:

[0090] (1) In the day-ahead stage, the uncertainty of renewable energy is described based on typical scenarios, and the start-stop state and output state of each regulation resource in the active distribution network are optimized.

[0091] In the specific implementation, in the day-ahead stage, the scheduling cycle is 24h, and the time resolution is 1h. The scenario method is used to solve the stochastic programming problem. First, a large number of forecast scenarios are generated by sampling the resulting conditional distribution using Latin hypercube sampling. Then, the original scene is reduced by using the synchronous back-generation reduction method to generate a typical scene with a certain probability. Based on the generated typical scenarios, the uncertainty of renewab...

Embodiment 2

[0213] This embodiment provides a multi-time scale active and reactive power coordination and optimization dispatching system for an active distribution network, which specifically includes the following modules:

[0214] Scheduling module before setting the time interval, which is used to describe the uncertainty of renewable energy based on typical scenarios in the stage before setting the time interval, and to analyze the start-stop status and output of each regulation resource in the active distribution network state is optimized;

[0215] A scheduling module within a set time interval, which is used to use multiple Correlation models to estimate the power prediction error to modify the power prediction value in the set time interval, and coordinate the quick response resources in the active distribution network based on the revised power prediction value in the set time interval;

[0216] The real-time scheduling module is used for performing rolling optimization on the ou...

Embodiment 3

[0219] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the above-mentioned multi-time-scale active and reactive power coordination optimization scheduling method for active power distribution network is realized. step.

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Abstract

The invention belongs to the field of power distribution networks, and provides a multi-time-scale active and reactive coordinated optimization scheduling method and system for an active power distribution network. The method comprises the following steps: in a pre-stage of a set time interval, describing the uncertainty of renewable energy sources based on a typical scene, and optimizing the start-stop state and the output state of each adjustment resource in the active power distribution network; in a stage within a set time interval, according to an optimization result of each adjustment resource in the active power distribution network before the set time interval and an updated power prediction value within the set time interval, using a multi-correlation model to estimate a power prediction error so as to correct the power prediction value within the set time interval, and coordinating fast response resources in the active power distribution network based on the corrected power predicted value within the set time interval; and in the real-time stage, performing rolling optimization on output of quick response resources in the active power distribution network by adopting model prediction control. The adaptability of the active power distribution network to renewable energy sources is improved.

Description

technical field [0001] The invention belongs to the field of distribution networks, and in particular relates to a multi-time-scale active and reactive power coordination optimization scheduling method and system for an active distribution network. 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] As the penetration rate of renewable energy sources (RES) increases, the complexity of power system operation control also increases, especially in the distribution network (DN). In order to cope with the challenges brought by renewable energy, researchers have proposed many dispatching strategies based on flexible control of distributed energy resources (DERs). The traditional DN is gradually being replaced by active distribution network (ADN). [0004] Due to the high resistance / reactance ratio of DN, the traditional active-reactive power decou...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06H02J3/46H02J3/48H02J3/50
CPCG06Q10/04G06Q10/06312G06Q10/06315G06Q50/06H02J3/466H02J3/48H02J3/50H02J2203/20Y04S10/50Y02E40/70
Inventor 王成福陈帅王勇董晓明
Owner SHANDONG UNIV
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