| 引用本文: | 孙宁杰,王德林,魏久林,等.基于SDM-Prony和改进GWO算法的多机PSS参数最优设计[J].电力系统保护与控制,2019,47(10):88-95. |
| SUN Ningjie,WANG Delin,WEI Jiulin,et al.Optimal design of multi-machine PSS parameters based on SDM-Prony and improved GWO algorithm[J].Power System Protection and Control,2019,47(10):88-95 |
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| 基于SDM-Prony和改进GWO算法的多机PSS参数最优设计 |
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孙宁杰1,王德林1,魏久林1,康积涛1,周 鑫2,吴水军3,和 鹏2
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(1.西南交通大学电气工程学院, 四川 成都 610031;2.云南电网有限责任公司电力科学研究院，云南 昆明 650217; 3.云南电力试验研究院(集团)有限公司，云南 昆明 650217)
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| 摘要: |
| 异步联网后的云南电网动态稳定性问题突出，考虑到云南电网水轮机组众多的特点，为了在抑制低频振荡的同时抑制“无功反调”现象，选用PSS2B稳定器进行参数优化整定。针对灰狼算法后期收敛速度慢的缺点，引入动态权重策略，平衡全局搜索和局部搜索能力，提高寻优精度。首先利用SDM-Prony对振荡信号进行机电模式辨识，然后通过改进GWO算法迭代寻优最佳PSS参数，最后搭建了云南电网东南地区部分电网。通过两种方式下的时域仿真校验，验证了优化PSS2B参数能够有效地提高系统对振荡的阻尼，具有一定的鲁棒性和适用性。 |
| 关键词: 水轮机组 PSS2B 参数优化 SDM-Prony GWO |
| DOI：10.7667/PSPC20191012 |
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| 基金项目:国家自然科学基金项目资助(51477143);中国南方电网项目(Ｋ-YNKJXM -20160159) |
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| Optimal design of multi-machine PSS parameters based on SDM-Prony and improved GWO algorithm |
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SUN Ningjie1,WANG Delin1,WEI Jiulin1,KANG Jitao1,ZHOU Xin2,WU Shuijun3,HE Peng2
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(1. School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China;2. Yunnan Power Grid Co., Ltd. Electric Power Research Institute, Kunming 650217, China;3. Yunnan Electric Power Test & Research Institute (Group) Co. Ltd., Kunming 650217, China)
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| Abstract: |
| The dynamic stability problem of Yunnan power grid after asynchronous networking is serious. Considering the characteristics of the numerous turbines in Yunnan Power Grid, PSS2B stabilizer is used for parameter optimization and setting in order to suppress the phenomenon of “reactive power reverse” while suppressing low frequency oscillation. For the shortcomings of slow convergence of grey wolf algorithm in the late stage, a dynamic weighting strategy is introduced to balance global search and local search capabilities and improve the accuracy of optimization. First, this paper uses SDM-Prony to perform electromechanical mode identification on the oscillation signal. Then it iteratively optimizes the optimal PSS parameters by improving the GWO algorithm. Finally, some power grids in the southeastern region of Yunnan Power Grid are built. Through the time-domain simulation checking in two ways, it is verified that the optimized parameters of PSS2B can effectively improve the damping of the system, and it has certain robustness and applicability. This work is supported by National Natural Science Foundation of China (No. 51477143) and China Southern Grid Project (No. K-YNKJXM-20160159). |
| Key words: water turbine PSS2B parameter optimization SDM-Prony GWO |
