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基于线性化潮流的安全约束机组组合方法
引用本文:岑海凤,许苑,李涛,陈坤,郑温剑,李志刚.基于线性化潮流的安全约束机组组合方法[J].电测与仪表,2022,59(8):97-104.
作者姓名:岑海凤  许苑  李涛  陈坤  郑温剑  李志刚
作者单位:广东电网广州供电局,广东电网广州供电局,广东电网广州供电局,广东电网广州供电局,华南理工大学,华南理工大学
摘    要:在安全约束机组组合(security-constrained unit commitment, SCUC)问题中,通常需要考虑N-1条件下的网络安全约束。由于支路开断分布系数(line outage distribution factor, LODF)良好的计算效率,学者常将其应用于N-1故障分析中。但是利用LODF并不能计算故障后的电压与无功分布。因此文中基于一种线性化潮流模型推导了与其对应的改进支路开断分布系数,并将该系数应用于SCUC中。算例结果表明,所提出的模型较传统基于LODF的模型能提供更加安全的发电计划。而对于绝大多数(95%以上)的N-1故障,得到的发电计划能在使用交流潮流进行安全校验时保证可行性。

关 键 词:线性化潮流  支路开断分布系数  混合整数线性规划  安全约束机组组合  灵敏度分析
收稿时间:2020/5/17 0:00:00
修稿时间:2020/6/3 0:00:00

Security Constrained Unit Commitment Based on State-Independent Linear Power Flow
cen hai feng,xu yuan,li tao,chen kun,zheng wen jian and li zhi gang.Security Constrained Unit Commitment Based on State-Independent Linear Power Flow[J].Electrical Measurement & Instrumentation,2022,59(8):97-104.
Authors:cen hai feng  xu yuan  li tao  chen kun  zheng wen jian and li zhi gang
Affiliation:Guangzhou Power Supply,Guangzhou Power Supply,Guangzhou Power Supply,Guangzhou Power Supply,South China University of Technology,South China University of Technology
Abstract:The N-1 criterion is universally taken as the security constraints in the security-constrained unit commitment (SCUC) problem. The line outage distribution factors (LODFs) is widely used in the N-1 continency for its state independence and computational efficiency. However, the LODF based model fails to consider reactive power and voltage magnitude. This paper bridges this gap by developing the modified line outage distribution factors (MLODFs) based on a linear power flow model. Additionally, we apply this model to formulate the SCUC problem. The simulation results show that the proposed model can provide a more accurate and secure generation schedule than the LODF based model while ensuring the AC feasibility for most N-1 contingency.
Keywords:linear power flow model  line outage distribution factor  mixed-integer linear programming  security constrained unit commitment  sensitivity analysis
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