基于海上风电集群并网的统一潮流控制器与储能协同优化配置研究

Collaborative Optimal Configuration of UPFC and Energy Storage Based on Grid-connected Offshore Wind Power Clusters

  • 摘要: 随着“碳中和,碳达峰”目标的提出,大规模、高容量、强随机性、清洁低碳的海上风电场集群并网,由于缺乏潮流调控手段,输电网将会出现潮流分布不均、断面输电能力达到瓶颈等问题,进而导致了严重的弃风现象。统一潮流控制器(unified power flow controller,UPFC)可以主动控制潮流分布以解决断面输电能力出现瓶颈的问题,同时储能装置可以起到提升电网灵活性、激励新能源消纳的作用。针对海上风电集群并网带来的一系列挑战,提出将基于海上风电集群并网的UPFC与储能协同优化配置方法,将UPFC和储能装置的选址和定容同时作为决策变量,并考虑海上风电出力的不确定性和时序相关性,提出UPFC与储能协同配置的分布鲁棒优化方法。然后,采用二阶锥凸松弛、大M法等技术将原混合整数非凸非线性规划模型转化成混合整数二阶锥规划模型,以实现高效求解。最后,以某个209节点的海上风电集群并网的输电系统为算例进行仿真计算,验证所提模型和算法的有效性。

     

    Abstract: With the proposal of "carbon neutralization and carbon peaking", along with the accesss of the large-scale, high-capacity, strong randomness, clean and low-carbon offshore wind farms to the grid, the power transmission network faces challenges such as uneven power flow distribution, section transmission capacity bottlenecks and other issues due to the lack of power flow control means, resulting in serious wind curtailment. The unified power flow controller (UPFC) can actively regulate the power flow distribution to solve the bottleneck issue of section transmission capacity, while the energy storage device can improve the flexibility of the power grid and stimulate new energy consumption. In view of a series of challenges brought by offshore wind power cluster grid connection, a collaborative optimization configuration method of UPFC and energy storage based on offshore wind power cluster grid connection is proposed. It takes the location and capacity of UPFC and energy storage devices as decision variables at the same time, and considers the uncertainty and time correlation of offshore wind power output. As a result, a distributionally robust collaborative optimization configuration method of UPFC and energy storage distribution is proposed. The original mixed integer non convex nonlinear programming model is then converted into a mixed integer second-order cone programming model by using second-order cone convex relaxation, large M method and other techniques to achieve efficient solution. Finally, the proposed model and method are validated through a case study of a 209-bus offshore wind power transmission system.

     

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