王 丹, 佟晶晶, 刘文霞, 张建华. 计及不确定性的分散式风电场与地区电网协调无功优化调度方法[J]. 现代电力, 2016, 33(4): 30-37.
引用本文: 王 丹, 佟晶晶, 刘文霞, 张建华. 计及不确定性的分散式风电场与地区电网协调无功优化调度方法[J]. 现代电力, 2016, 33(4): 30-37.
WANG Dan, TONG Jingjing, LIU Wenxia, ZHANG Jianhua. Coordinated Optimization Scheduling of Reactive Power for Distributed Wind Farms and Regional Network Under Uncertainty[J]. Modern Electric Power, 2016, 33(4): 30-37.
Citation: WANG Dan, TONG Jingjing, LIU Wenxia, ZHANG Jianhua. Coordinated Optimization Scheduling of Reactive Power for Distributed Wind Farms and Regional Network Under Uncertainty[J]. Modern Electric Power, 2016, 33(4): 30-37.

计及不确定性的分散式风电场与地区电网协调无功优化调度方法

Coordinated Optimization Scheduling of Reactive Power for Distributed Wind Farms and Regional Network Under Uncertainty

  • 摘要: 针对地区电网中分散式风电多点接入导致的电压波动问题,本文提出了考虑不确定性的分散式风电与地区电网协调控制的无功优化调度方法。首先计及风速不确定性和风电场内接线,构建了分散风电场无功可调容量预测模型;在此基础上,将风电出力和负荷不确定性处理为区间约束,提出了地区电网的双层无功优化模型,上层以地区电网网损最小为优化目标,下层用来寻找电网运行的最恶劣场景,使得在满足电压运行要求的同时降低网损,兼顾安全性与经济性;最后采用遗传算法与内点法相结合的方法对模型进行求解,并以某地区电网为算例,MATLAB计算结果验证了所提策略的可行性和有效性。

     

    Abstract: In order to solve the voltage fluctuation problem in regional power network caused by the integration of distributed wind generation, a coordinated controlling optimization method for reactive power between regional grid and distributed wind power plant is proposed in this paper. A model for calculating the reactive power regulation capacity of wind farm is constructed firstly by considering the wind speed uncertainty and the wiring in wind farm. On this basis, by treating the uncertainty of wind output and load as the interval constraint, a bi-level reactive power optimization model of regional network is proposed, in which the upper-level is to minimize the power loss and the lower-level is to find the worst operation scenario of regional network, which reduce the losses while meeting the voltage operation requirements. In the end, the Genetic Algorithm and interior point method are used to solve the model, and by taking a regional power network as an example, the feasibility and effectiveness of the strategy are verified by MATLAB results.

     

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