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主动配电网多元主体灵活性和随机性的转换机制与刻画方法

张梓麒 陈中

电力系统自动化2024,Vol.48Issue(13):79-88,10.
电力系统自动化2024,Vol.48Issue(13):79-88,10.DOI:10.7500/AEPS20230907004

主动配电网多元主体灵活性和随机性的转换机制与刻画方法

Transformation Mechanisms and Characterization Methods for Flexibility and Uncertainty in Active Distribution Networks with Multiple Entities

张梓麒 1陈中1

作者信息

  • 1. 东南大学电气工程学院,江苏省南京市 210096
  • 折叠

摘要

Abstract

In the context of energy transition,large-scale distributed photovoltaic(PV),energy storage systems and interactive loads are integrated into the distribution network.In dispatching and optimization models,due to differences in resource characteristics,various entities,such as distribution networks and end-users,possess the potential to act as flexible control variables or may still exhibit randomness.These entities may demonstrate flexibility when their load interaction capabilities are strong,energy storage capacities are high,and prediction errors are low;conversely,they may exhibit uncertainty.Firstly,this paper investigates transformation mechanisms of flexibility and uncertainty and derives general transformation conditions between control variables and parameters of various entities based on robust optimization results with aggregated power.Secondly,considering the optimal controllable or uncertain range of power aggregation under temporal coupling,a two-stage robust optimization approach is employed to delineate the controllable range of control variables and the uncertain interval of parameters.Finally,case studies are conducted to validate the effectiveness of the transformation conditions and characterization methods,which provides support for the modeling and rapid solving of multi-level coordinated optimization problems in the power grid.

关键词

灵活性/随机性/两阶段鲁棒优化/主动配电网/多层级协同

Key words

flexibility/uncertainty/two-stage robust optimization/active distribution network/multi-level coordination

引用本文复制引用

张梓麒,陈中..主动配电网多元主体灵活性和随机性的转换机制与刻画方法[J].电力系统自动化,2024,48(13):79-88,10.

基金项目

国家自然科学基金资助项目(52077035). This work is supported by National Natural Science Foundation of China(No.52077035). (52077035)

电力系统自动化

OA北大核心CSTPCD

1000-1026

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