基于SDM-Prony和改进GWO算法的多机PSS参数最优设计
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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。
The dynamic stability problem of Yunnan power grid after asynchronous networking is serious. Considering the characteristics of the numerous turbines in Yunnan Power Grid, PSS2 B 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 PSS2 B can effectively improve the damping of the system, and it has certain robustness and applicability.
The dynamic stability problem of Yunnan power grid after asynchronous networking is serious. Considering the characteristics of the numerous turbines in Yunnan Power Grid, PSS2 B 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 PSS2 B can effectively improve the damping of the system, and it has certain robustness and applicability.
引文
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[20]王德林,王晓茹.不均匀连续体电力系统中的机电波传播[J].中国电机工程学报,2010,30(34):78-85.WANG Delin,WANG Xiaoru.Electromechanical wave propagation in non-uniform continuum power systems[J].Proceedings of the CSEE,2010,30(34):78-85.
[21]李林,宋宗勋,李峰,等.抑制区域间低频振荡的UPFC模糊滑膜控制器[J].电力系统保护与控制,2017,45(10):104-109.LI Lin,SONG Zongxun,LI Feng,et al.UPFC fuzzy synovial controller for suppressing inter-region low frequency oscillations[J].Power System Protection and Control,2017,45(10):104-109.
[22]李生虎,孙琪,石雪梅,等.基于区域极点配置的风电系统弱阻尼低频振荡模式抑制[J].电力系统保护与控制,2017,45(20):14-20.LI Shenghu,SUN Qi,SHI Xuemei,et al.Suppression of low-damping low-frequency oscillation mode for wind power system based on regional pole assignment[J].Power System Protection and Control,2017,45(20):14-20.
[2]杜斌,张丹,张军民,等.异步联网后云南电网的稳定特性与控制措施[J].南方电网技术,2016,10(7):13-16,23.DU Bin,ZHANG Dan,ZHANG Junmin,et al.Stability characteristics and control measures of Yunnan Power Grid after asynchronous networking[J].Southern Power System Technology,2016,10(7):13-16,23.
[3]彭俊春,周懋文.异步联网后电网频率稳定影响因素研究[J].云南电力技术,2017,45(2):107-109.PENG Junchun,ZHOU Maowen.Research on the influencing factors of grid frequency stability after asynchronous networking[J].Yunnan Electric Power Technology,2017,45(2):107-109.
[4]沈利平,付廷勤,王茂元.PSS模型比较、反调试验及现场应用[J].水电厂自动化,2009,30(2):14-17.SHEN Liping,FU Tingqin,WANG Maoyuan.PSS model comparison,anti-regulation test and field application[J].Automation of Hydroelectric Power,2009,30(2):14-17.
[5]郭成,李群湛,王德林.基于Prony和改进PSO算法的多机PSS参数优化[J].电力自动化设备,2009,29(3):16-21.GUO Cheng,LI Qunzhan,WANG Delin.Multi-machine PSS parameter optimization based on Prony and improved PSO algorithm[J].Electric Power Automation Equipment,2009,29(3):16-21.
[6]张程,金涛.基于ISPM和SDM-Prony算法的电力系统低频振荡模式辨识[J].电网技术,2016,40(4):1209-1216.ZHANG Cheng,JIN Tao.Low-frequency oscillation identification of power system based on ISPM and SDM-Prony algorithm[J].Power System Technology,2016,40(4):1209-1216.
[7]牛振勇.基于进化策略的多机系统PSS参数优化[J].中国电机工程学报,2004,24(2):22-27.NIU Zhenyong.Optimization of PSS parameters for multi-machine systems based on evolution strategy[J].Proceedings of the CSEE,2004,24(2):22-27.
[8]ABIDO M A.Parameter optimization of multi mchine power system stabilizers using genetic local search[J].Electrical Power and Energy Systems,2001,23(8):785-794.
[9]刘蔚.一种提高多小水电群送出能力的PSS参数协调优化方法[J].电力系统保护与控制,2015,43(4):44-49.LIU Wei.A coordinated optimization method for PSSparameters to improve the delivery capacity of multiple small hydropower groups[J].Power System Protection and Control,2015,43(4):44-49.
[10]张子泳,仉梦林,李莎.基于多目标粒子群算法的电力系统环境经济调度研究[J].电力系统保护与控制,2017,45(10):1-10.ZHANG Ziyong,ZHANG Menglin,LI Sha.Research on environmental economic dispatch of power system based on multi-objective particle swarm optimization[J].Power System Protection and Control,2017,45(10):1-10.
[11]SULAIMAN M H,MUSTAFFA Z,MOHAMED M R,et al.Using the grey wolf optimizer for solving optimal reactive power dispatch problem[J].Applied Soft Computing,2015,32(6):286-292.
[12]刘子全,高磊,赵娴,等.一种可有效提高临界增益的改进型电力系统稳定器[J].中国电机工程学报,2015,35(8):1875-1881.LIU Ziquan,GAO Lei,ZHAO Xian,et al.An improved power system stabilizer that can effectively improve the critical gain[J].Proceedings of the CSEE,2015,35(8):1875-1881.
[13]李莹.PSS2A中加速功率合成环节的原理分析及现场参数整定原则[C]//2013年中国电机工程学会年会论文集,中国电机工程学会,2013:5.LI Ying.Principle analysis of acceleration power synthesis in PSS2A and principles of field parameter tuning[C]//Proceedings of the 2013 Annual Meeting of the Chinese Society for Electrical Engineering,Chinese Society of Electromechanical Engineering,2013:5.
[14]吴跨宇,卢岑岑,吴龙,等.一种新型双信号电力系统稳定器及其仿真研究[J].电网技术,2016,40(5):1462-1468.WU Kuayu,LU Cencen,WU Long,et al.A novel dual-signal power system stabilizer and its simulation study[J].Power System Technology,2016,40(5):1462-1468.
[15]PILOT M,BRANICKI W,JEDRZEJEWSKIW,et al.Phylogeo-graphic history of grey wolves in Europe[J].BMC Evolutionary Biology,2010,10(1685):1-11.
[16]MURO C,ESCOBEDO R,SPECTOR L,et al.Wolf-pack(Canislupus)hunting strategies emerge from simple rules in computational simulations[J].Behavioural Processes,2011,88(3):192-197.
[17]郭振洲,刘然,拱长青,等.基于灰狼算法的改进研究[J].计算机应用研究,2017,34(12):3603-3606,3610.GUO Zhenzhou,LIU Ran,GONG Changqing,et al.Improved research based on grey wolf algorithm[J].Research of Computers,2017,34(12):3603-3606,3610.
[18]刘前进,许慧铭,施超.基于人工蜂群算法的多目标最优潮流问题的研究[J].电力系统保护与控制,2015,43(8):1-7.LIU Qianjin,XU Huiming,SHI Chao.Research on multi-objective optimal power flow problem based on artificial bee colony algorithm[J].Power System Protection and Control,2015,43(8):1-7.
[19]王德林,王晓茹.电力系统中机电扰动的传播特性分析[J].中国电机工程学报,2007,27(19):18-24.WANG Delin,WANG Xiaoru.Analysis of propagation characteristics of electromechanical disturbance in power system[J].Proceedings of the CSEE,2007,27(19):18-24.
[20]王德林,王晓茹.不均匀连续体电力系统中的机电波传播[J].中国电机工程学报,2010,30(34):78-85.WANG Delin,WANG Xiaoru.Electromechanical wave propagation in non-uniform continuum power systems[J].Proceedings of the CSEE,2010,30(34):78-85.
[21]李林,宋宗勋,李峰,等.抑制区域间低频振荡的UPFC模糊滑膜控制器[J].电力系统保护与控制,2017,45(10):104-109.LI Lin,SONG Zongxun,LI Feng,et al.UPFC fuzzy synovial controller for suppressing inter-region low frequency oscillations[J].Power System Protection and Control,2017,45(10):104-109.
[22]李生虎,孙琪,石雪梅,等.基于区域极点配置的风电系统弱阻尼低频振荡模式抑制[J].电力系统保护与控制,2017,45(20):14-20.LI Shenghu,SUN Qi,SHI Xuemei,et al.Suppression of low-damping low-frequency oscillation mode for wind power system based on regional pole assignment[J].Power System Protection and Control,2017,45(20):14-20.