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考虑解析化动态频率约束的输-储协同鲁棒规划方法

A robust coordinated planning method for transmission system and storage considering analytical frequency dynamics constraints

  • 摘要: 为应对海上风电出力不确定性对电力系统频率安全与输电网规划带来的挑战,提出了一种考虑解析化动态频率约束的输-储协同鲁棒规划方法。首先,构建了包含输电网上层规划与下层运行调度的双层优化框架,上层以系统投资与运行总成本最小为目标,规划满足负载率约束的输电线路;下层考虑输电网与储能系统(energy storage system,ESS)的协同运行,并引入频率响应特性建模,确保系统在扰动下具备动态频率安全性。随后,利用强对偶理论将双层模型转化为易于求解的单层模型。进一步,采用对抗场景生成(adversarial scenario generation,ASG)方法构建极端风险场景,基于1-∞范数混合不确定集描述海上风电与负荷的概率分布不确定性,并利用条件风险价值(conditional value-at-risk,CVaR)度量其带来的风险损失,从而建立输-储协同分布鲁棒优化模型,同时使用列与约束生成(column and constraint generation,C&CG)算法进行求解。基于IEEE 24节点系统的仿真结果表明,该方法在提升系统频率安全性的同时,能够有效缓解线路重载问题,得到经济性与鲁棒性兼顾的规划方案。

     

    Abstract: To address the challenges posed by the uncertainty of offshore wind power output to power system frequency security and transmission network planning, this paper proposes a transmission-storage coordinated robust planning method considering analytical dynamic frequency constraints. First, a bi-level optimization framework is formulated, consisting of upper-level transmission network planning and lower-level operation scheduling; the upper level aims to minimize the total system investment and operation cost while planning transmission lines that satisfy load rate constraints, and the lower level considers the coordinated operation of the transmission network and energy storage system (ESS) with frequency response modeling to guarantee dynamic frequency security under disturbances. Then, the bi-level model is transformed into a tractable single-level model via strong duality theory. Furthermore, an adversarial scenario generation (ASG) method is employed to construct extreme risk scenarios, the probabilistic uncertainty of offshore wind power and load is characterized by a 1-∞ norm hybrid uncertainty set, and conditional value-at-risk (CVaR) is adopted to quantify the corresponding risk loss, based on which a transmission-storage coordinated distributionally robust optimization model is established and solved by the column-and-constraint generation (C&CG) algorithm. Simulation results on the IEEE 24-bus system demonstrate that the proposed method can enhance system frequency security, effectively alleviate line overloading, and yield planning schemes with favorable economic efficiency and robustness.

     

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