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1.山东大学电气工程学院,山东省济南市 250061
2.电网智能化调度与控制教育部重点实验室(山东大学),山东省济南市 250061
周瑜(1996—),男,硕士研究生,主要研究方向:电力系统优化调度。E-mail:17865195506@163.com
李正烁(1988—),男,通信作者,博士,教授,博士生导师,主要研究方向:输配电网协同能量管理、分布式能源优化调度。E-mail:zsli@sdu.edu.cn
收稿日期:2020-04-20,
修回日期:2020-08-31,
网络出版日期:2020-10-30,
纸质出版日期:2021-03-10
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周瑜,李正烁.双馈风力发电场无功支撑范围的鲁棒估计[J].电力系统自动化,2021,45(5):86-96.
ZHOU Yu,LI Zhengshuo.Robust Estimation of Reactive Power Support Range of DFIG Wind Farm[J].Automation of Electric Power Systems,2021,45(5):86-96.
周瑜,李正烁.双馈风力发电场无功支撑范围的鲁棒估计[J].电力系统自动化,2021,45(5):86-96. DOI: 10.7500/AEPS20200420004.
ZHOU Yu,LI Zhengshuo.Robust Estimation of Reactive Power Support Range of DFIG Wind Farm[J].Automation of Electric Power Systems,2021,45(5):86-96. DOI: 10.7500/AEPS20200420004.
双馈异步发电机无功功率在一定范围内可调,双馈风力发电场可作为新型无功源向电网提供无功支撑。由于风电场内网络约束的非线性以及双馈风力发电机有功功率的不确定性,难以准确估计双馈风力发电场的无功支撑范围,对此提出鲁棒估计方法。首先建立基于两阶段鲁棒优化的无功支撑范围估计模型,其中第1阶段优化给出候选的最大无功支撑范围,第2阶段优化检查在各种不确定场景下,风电场是否均可提供候选范围内的无功功率。为便于求解,通过锥松弛和对偶转化将非凸的第2阶段问题转化为凸优化问题,并通过罚因子保证松弛解的精确性。基于列约束生成算法求解该鲁棒优化模型,得到最大无功支撑范围。最后给出风电场作为无功源参与电网无功优化的策略。算例证明了所提方法可以准确估计风电场的无功支撑范围以及策略的可行性。
The reactive power of the doubly-fed induction generator (DFIG) is adjustable within a certain range
so the DFIG wind farm can be used as a new reactive power resource to provide necessary reactive power support to power grids. Due to the nonlinearity of network constraints in wind farms and the uncertainty of the active power of DFIGs
it is difficult to accurately estimate the reactive power support range of DFIG wind farms. A robust estimation method is proposed to solve this problem. Firstly
an estimation model of reactive power support range based on two-stage robust optimization is established. The first-stage optimization gives the candidate maximum reactive power support range
and the second-stage optimization checks whether the wind farm could provide the reactive power in the candidate range in different uncertain scenarios. To facilitate the solution
the nonconvex second-stage problems are transformed into convex optimization problems by cone relaxation and dual transformation
and the accuracy of the relaxation solution is guaranteed by the penalty factor. Then the robust optimization model is solved based on the column-and-constraint generation algorithm to obtain the maximum reactive power support range. Finally
the strategy of the wind farm as a reactive prosumer is given to participate in the reactive power optimization of the power grid. The case study shows that the proposed method can accurately estimate the reactive power support range of the wind farm
and the proposed strategy is feasible.
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