大规模风电集群接入对电力系统自组织临界态影响机理及其辨识方法研究

With rising of wind power Permeability and increasing of grid connected 10 million kilowatts wind power bases in China, large-scale development and grid cluster connected wind power bring new uncertainties on the safe operation of power blackouts and cascading failures defense. To improve grid security and defense ability and adapt the development of wind power clusters grid-connect, the subject research the defense of power system cascading failure based on self-organized criticality including four-fold. First, large-scale wind power cluster equivalents aggregation model is built, and cluster grid-connected characteristics is analyzed based on the model including the large-scale wind power cluster multi-scale output features, operating characteristics, structural characteristics; Second, Self-organized critical state evaluation system based on physical indicators entropies is put forward, by which power system self-organized critical state influence mechanism is researched on large-scale wind power cluster grid-connected; Third, the self-organized criticality state identification method and model is proposed through establishing cascading failure simulation model, in which the main factors considered by us are as follows: cluster grid-connected characteristics, wind farm group element hidden failure model and wind farm/wind power unit common-mode trip. Finally, combining with the physical digital simulation and actual large-scale wind power base operating data, effectiveness of the model is also verified. It provides a theoretical basis and guidance for cascading failure defense and dispatching operation of power system including grid-connect wind power.

我国风电渗透率的不断攀升和千万千瓦风电基地集群并网趋势的日益显著对电网安全运行及连锁故障大停电防御带来了新的不确定性因素。本课题以风电集群并网为背景，以提高电网连锁故障安全防御水平为目标，从电力系统自组织临界性角度出发，首先通过建立风电集群等值聚合模型，对大规模风电集群多尺度出力特性、结构特性等集群并网特性进行分析；其次通过建立电力系统自组织临界态多熵值物理指标评估体系，研究大规模风电集群接入对电力系统自组织临界态影响机理；再次通过建立考虑风电集群并网特性和风电场隐性失效及风电场/风电机组共模跳闸的连锁故障仿真模型，提出含大规模风电集群并网电力系统自组织临界态辨识方法及辨识模型；最后通过物理数字仿真和实际大规模风电基地运行数据对含大规模风电集群并网电力系统自组织临界态辨识模型进行有效性验证。从而为含大规模风电集群接入的电力系统连锁故障防御和集群风电调度运行提供理论依据和方法指导。

我国风电渗透率的不断攀升和大规模风电集群并网趋势的日益显著对电网安全运行及连锁故障防御带来了新的挑战。本课题以风电集群并网为背景，以提高电网连锁故障防御水平为目标，对大规模风电集群接入对电网自组织临界态影响机理及辨识方法进行了研究。.首先，建立了大规模风电集群等值聚合模型，并基于此，研究了风电集群出力特性和并网结构特性，首次从风电“集群”的角度分析了风电接入对电网潮流分布及网络关键结构参量的影响机理；并基于此，从指标分析的角度，首次揭示了风电集群接入对电网自组织临界演化过程的影响机理；并提出了电网自组织临界态多熵值评估体系，可进行多影响因素共同作用对电网自组织临界演化影响的综合分析；.然后，基于风电机组共模跳闸机理，建立了考虑风电场群元件隐性失效概率的连锁故障仿真模型，可更加真实的反映含风电集群接入电网的连锁故障演化过程；首次将LVQ神经网络智能算法运用至电网自组织临界辨识，建立了含大规模风电集群接入电网的自组织临界辨识模型，提出了可进行风电集群波动特性跟踪及风电渗透率调整的复杂电网自组织临界态辨识方法，显著提高了含大规模风电集群接入电网自组织临界辨识准确率；首次提出电网自组织靠近度指标，实现了含大规模集群接入电网自组织临界演化的量化表征；.最后，以甘肃酒泉大规模风电基地为研究背景，仿真验证了所提大规模风电集群静态等值聚合模型的准确性、大规模风电集群接入对电力系统自组织临界态影响机理及辨识方法的有效性。.本项目研究成果可推广至全国具有风电基地的各级电网，能够有效发现含大规模风电集群接入电网薄弱环节，为电网安全预警、连锁故障预防控制提供理论方法，亦可为研究制定大电网安稳控制策略提供技术依据，具有重要的理论和实用价值。项目目前获得省部级奖励4项，已发表SCI检索论文4篇，EI检索论文9篇，中文核心期刊论文3篇，国际会议论文2篇；发明专利授权3项,受理5项，培养博士3人，硕士4人。