郭小龙, 杨桂兴, 张江飞, 袁铁江. 考虑时空特性与多指标约束的电力系统惯量需求评估[J]. 高电压技术, 2024, 50(1): 148-156. DOI: 10.13336/j.1003-6520.hve.20230189
引用本文: 郭小龙, 杨桂兴, 张江飞, 袁铁江. 考虑时空特性与多指标约束的电力系统惯量需求评估[J]. 高电压技术, 2024, 50(1): 148-156. DOI: 10.13336/j.1003-6520.hve.20230189
GUO Xiaolong, YANG Guixing, ZHANG Jiangfei, YUAN Tiejiang. Assessment of Inertia Demand in Power System Considering Spatio-temporal Characteristics and Multi-index Constraints[J]. High Voltage Engineering, 2024, 50(1): 148-156. DOI: 10.13336/j.1003-6520.hve.20230189
Citation: GUO Xiaolong, YANG Guixing, ZHANG Jiangfei, YUAN Tiejiang. Assessment of Inertia Demand in Power System Considering Spatio-temporal Characteristics and Multi-index Constraints[J]. High Voltage Engineering, 2024, 50(1): 148-156. DOI: 10.13336/j.1003-6520.hve.20230189

考虑时空特性与多指标约束的电力系统惯量需求评估

Assessment of Inertia Demand in Power System Considering Spatio-temporal Characteristics and Multi-index Constraints

  • 摘要: 针对传统惯量需求评估方法难以准确刻画高随机性新能源接入下电力系统运行方式多变导致惯量需求时空动态变化特点的问题,提出一种考虑时空特性与多指标约束的电力系统惯量需求评估方法。首先通过分析系统惯量需求影响因素,建立考虑新能源渗透率以及虚拟惯量的电力系统频率响应模型;其次,在传统频率响应指标的基础上,引入一次调频恢复频差约束,建立惯量需求评估模型;然后,在时间和空间两方面分别考虑系统参数和节点位置对惯量需求的影响,在不同场景下采用优化方法评估系统惯量需求;最后,分别针对传统电力系统和基于虚拟惯量的新能源发电系统开展算例分析,验证了所提方法的有效性和准确性。

     

    Abstract: Aiming at the problem that the traditional inertia demand assessment method is difficult to accurately describe the space-time dynamic change characteristics of the system inertia demand caused by the variable operation mode of the power system with high randomness, we propose a new power system inertia demand assessment method in which the space-time characteristics and multi index constraints are taken into consideration. Firstly, by analyzing the influencing factors of system inertia demand, a frequency response model of power system considering new energy penetration and virtual inertia is established.Secondly, based on the traditional frequency response index, the recovery frequency constraint is introduced to establish the inertia demand evaluation model. Then, the influence of system parameters and node location on the inertia demand in time and space is taken into consideration, and the optimization method is used to dynamically evaluate the inertia demand of the system in different scenarios. Finally, the effectiveness and accuracy of the proposed method are verified by the example analysis of the traditional power system and the renewable energy generation system based on virtual inertia.

     

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