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Dynamic Stochastic Optimal Power Flow Considering Spatial Correlation of Wind Speed Based on Simplified Pair Copula

机译:基于简化对谱的风速空间相关性动态随机最佳功率流动

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With large-scale wind power integrating into power grid, it's increasingly important to consider uncertainty factors into power system operation scheduling. In actual operation, wind power outputs are relatively strong correlation. It will bring larger computational error without considering these factors. Current researches are inadequate to model multiple dependent wind power outputs. Recently, presented stochastic optimal power flow models have lower computational efficiency and not able to assure the convergence. To solve these problems, a second-order cone dynamic stochastic optimal power flow model is proposed based on Simplified Pair Copula model. In this model, original non-linear models are transformed into SOCP models after constructing multiple correlated wind power outputs. Improved point estimate method and GUROBI are used to solve this model. Comparing with the program without considering the correlation of wind speed, the proposed method is proved to be effectiveness and practicability.
机译:通过集成电网的大型风力电力,将不确定性因素视为电力系统运行调度越来越重要。在实际操作中,风力输出相对强烈的相关性。在不考虑这些因素的情况下,它将带来更大的计算错误。目前的研究不足以模拟多个依赖风力输出。最近,呈现随机最佳功率流动模型具有较低的计算效率,不能保证收敛。为了解决这些问题,基于简化对Copula模型提出了一种二阶锥动态随机最佳功率流模型。在该模型中,在构造多个相关的风力输出之后,原始的非线性模型转换为SOCP模型。改进的点估计方法和Gurobi用于解决该模型。与该程序相比,不考虑风速的相关性,所提出的方法被证明是有效性和实用性。

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