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复杂断面约束下交直流混联送端电网直流回降保供调控策略

段龙翔 刘挺坚 刘友波 邱高 叶希 高剑

电力系统自动化2025,Vol.49Issue(10):165-175,11.
电力系统自动化2025,Vol.49Issue(10):165-175,11.DOI:10.7500/AEPS20240420001

复杂断面约束下交直流混联送端电网直流回降保供调控策略

Regulation Strategy of DC Backdown and Supply Guarantee in AC-DC Hybrid Sending-end Power Grid Under Complex Section Constraints

段龙翔 1刘挺坚 1刘友波 1邱高 1叶希 2高剑2

作者信息

  • 1. 四川大学电气工程学院,四川省 成都市 610065
  • 2. 国网四川省电力公司,四川省 成都市 610041
  • 折叠

摘要

Abstract

Due to the double impact of intermittent renewable energy shortage and regional peak load,the transmission network with rich clean energy will face the pressure of supply guarantee.Existing research rarely considers the role of DC power reduction in supply guarantee at the sending end.However,the AC section transmission capacity is coupled with the DC transmission power in the hybrid transmission mode of clean energy generation bases,and it is necessary to coordinate the complex relationship among the DC power reduction,AC section power control and load demand gap during supply guarantee and regulation.Therefore,a stepped control model for DC tie-lines is established.Considering the coupling relationship between DC transmission power and sending-end AC section limits,the conditional section constraints are built.The load importance is quantified by using power loss penalty factors,the renewable energy output uncertainty impact is analyzed through extreme scenario methods,and the nonlinear factors of logical judgement in conditional section constraint are relaxed to enhance model solving efficiency.Case analysis demonstrates that the proposed strategy can overcome adverse factors such as renewable energy capacity gaps and transmission channel bottlenecks for effective supply guarantee.

关键词

复杂断面约束/交直流混联电网/可再生能源/保供/极端场景/松弛法

Key words

complex section constraint/AC-DC hybrid power grid/renewable energy/supply guarantee/extreme scenario/relaxation method

引用本文复制引用

段龙翔,刘挺坚,刘友波,邱高,叶希,高剑..复杂断面约束下交直流混联送端电网直流回降保供调控策略[J].电力系统自动化,2025,49(10):165-175,11.

基金项目

国家自然科学基金资助项目(52307124). This work is supported by National Natural Science Foundation of China(No.52307124). (52307124)

电力系统自动化

OA北大核心

1000-1026

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