| 引用本文: | 李利娟,吴军,刘红良,等.计及新能源影响静动态结合的电网脆弱节点辨识[J].电力系统保护与控制,2019,47(2):64-72.[点击复制] |
| LI Lijuan,WU Jun,LIU Hongliang,et al.Static and dynamic integration method on identifying vulnerability nodes considering new energy power[J].Power System Protection and Control,2019,47(2):64-72[点击复制] |
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| 摘要: |
| 随着新能源发电的快速增长，其所具有的随机性、波动性不确定给电网脆弱节点辨识带来了新的挑战。提出了一种考虑新能源不确定性的电网静动态结合的脆弱节点辨识方法。该方法在静态辨识中采用区间数表示新能源的不确定性，提出了基于区间直流潮流的最小切负荷模型计算各节点的区间静态脆弱性评估指标。在动态辨识中，提出基于单机等效延伸方法计算各节点的稳定性裕度，并根据稳定性裕度的正负对应计算各节点的动态脆弱性评估指标。最后建立基于熵权法的电网脆弱节点综合评估方法。IEEE-39节点算例仿真结果表明，该方法能准确快速地辨识新能源接入情况下电网中的脆弱节点。与已有脆弱节点辨识方法相比，该模型更符合新能源接入下电力系统实际运行情况。通过研究发现新能源的随机性、波动性不确定对节点脆弱性具有就近影响原则，为新能源电源在智能电网中的规划提供指导作用。 |
| 关键词: 连锁故障 新能源 暂态稳定性分析 不确定性 脆弱性 |
| DOI：10.7667/PSPC180093 |
| 投稿时间：2018-01-20修订日期：2018-03-21 |
| 基金项目:国家自然科学基金项目资助(51307148);中美国际科技合作项目资助(2016YFE0105300) |
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| Static and dynamic integration method on identifying vulnerability nodes considering new energy power |
| LI Lijuan,WU Jun,LIU Hongliang,LI Yuan,ZENG Taiyuan,ZHOU Jian,GONG Zheng |
| (College of Information Engineering, Xiangtan University, Xiangtan 411105, China;Hunan Key Laboratory for Computation and Simulation in Science and Engineering, Xiangtan 411105, China) |
| Abstract: |
| With the rapid growth of new energy power generation, its randomness and volatility bring new challenges to identify the vulnerability nodes in power grid. In this paper, a method of integration of static state and dynamic state on identifying vulnerability nodes considering new energy power is proposed. In the static identification, the interval numbers are used to express the uncertainty of new energy. The interval minimum load shedding model based on interval direct current power flow is proposed to calculate the interval static vulnerability assessment index. In the dynamic identification, the energy margin of each node is calculated by the extension method of Single Machine Equivalence (SIME) method, and the dynamic vulnerability assessment index is obtained according to the positive or negative of energy margin. Finally, the weights of two indexes are obtained by the entropy weight method, and the vulnerability index of each node is evaluated. The simulation results of IEEE 39-bus system show that the proposed method can accurately and quickly identify the vulnerability nodes under the condition of new energy injected into the power grid. Compared with the existing vulnerability identification methods, the proposed method is closer to actual operation of the power system. The results show that the randomness and volatility of new energy has a far greater impact on near nodes, which provides guidance for the planning of the new energy power supply in the smart grid. This work is supported by National Natural Science Foundation of China (No. 51307148) and Sino-US international Science and Technology Cooperation Project (No. 2016YFE0105300). |
| Key words: cascading failure new energy transient stability uncertainty vulnerability |
