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1.南京邮电大学先进技术研究院,江苏省南京市 210023
2.东南大学电气工程学院,江苏省南京市 210096
Received:26 January 2021,
Revised:2021-06-15,
Published Online:13 September 2021,
Published:25 October 2021
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黄煜,徐青山,夏元兴等.考虑自适应传输备用的含风电电力系统双层随机调度方法[J].电力系统自动化,2021,45(20):29-37.
HUANG Yu,XU Qingshan,XIA Yuanxing,et al.Bi-level Stochastic Scheduling Method for Power System with Wind Power Considering Adaptive Transmission Reserve[J].Automation of Electric Power Systems,2021,45(20):29-37.
黄煜,徐青山,夏元兴等.考虑自适应传输备用的含风电电力系统双层随机调度方法[J].电力系统自动化,2021,45(20):29-37. DOI: 10.7500/AEPS20210126008.
HUANG Yu,XU Qingshan,XIA Yuanxing,et al.Bi-level Stochastic Scheduling Method for Power System with Wind Power Considering Adaptive Transmission Reserve[J].Automation of Electric Power Systems,2021,45(20):29-37. DOI: 10.7500/AEPS20210126008.
大规模风电接入增加了电网发生输电阻塞的概率。为克服确定性阻塞管理方法在应对系统随机扰动上的不足,基于考虑阻塞风险的机会约束规划条件,提出一种计及风电不确定性的传输备用自适应量化方法,构建了包含自适应传输备用的双层随机调度模型。该模型将线路传输备用纳入上层的机组组合模型中,针对下层的经济再调度问题,采用改进点估计法求得线路实时潮流的统计分布特性,并将结果返回上层模型以动态调整备用需求大小。同时,基于下层模型的Karush-Kuhn-Tucher最优条件,将双层优化结构合并为单层,并最终转化为便于求解的混合整数规划问题。最后,通过IEEE RTS-24节点测试算例验证了所提模型和方法能够有效缓解传输阻塞,提高风电消纳和备用可用性。
Large-scale wind power integration increases the probability of transmission congestion in power grids. In order to overcome the disadvantages of deterministic methods for congestion management when facing system random perturbations
based on chance-constrained programming conditions considering congestion risk
this paper proposes an adaptive approach for quantifying transmission reserves by taking the wind power uncertainty into account. A bi-level stochastic scheduling model with adaptive transmission reserves is developed. This model incorporates the line transmission reserve into the upper-level unit commitment (UC) model. Aiming at the economic rescheduling problem at the lower level
the improved point estimation method is used to obtain the statistical distribution characteristics of the real-time power flow of the line
and the result is returned to the upper model to dynamically adjust the size of the reserve demand. At the same time
based on the Karush-Kuhn-Tucher (KKT) optimal condition of the underlying model
the bi-level optimal structure is merged into a single layer
and finally transformed into a mixed-integer programming problem that is easy to solve. Finally
the IEEE RTS 24-bus testing case verifies that the proposed model and method can effectively alleviate transmission congestion and improve wind power consumption and reserve availability.
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