Identification of Critical Parameters Affecting Voltage and Angular Stability Considering Load-Renewable Generation Correlations

被引:60
作者
Qi, Buyang [1 ]
Hasan, Kazi N. [1 ]
Milanovic, Jovica, V [1 ]
机构
[1] Univ Manchester, Sch Elect & Elect Engn, Manchester M60 1QD, Lancs, England
基金
英国工程与自然科学研究理事会;
关键词
Copula method; power system computation; renewable generation; sensitivity analysis; small-disturbance stability; transient stability; voltage stability; SMALL-DISTURBANCE STABILITY; SMALL-SIGNAL STABILITY; POWER-SYSTEMS; ENHANCEMENT; PROBABILITY; NETWORKS; RANKING; ENERGY; MODEL;
D O I
10.1109/TPWRS.2019.2891840
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
080906 [电磁信息功能材料与结构]; 082806 [农业信息与电气工程];
摘要
The renewable energy source based generating technologies and flexible demand and storage devices exhibit significant temporal and spatial uncertainties in generating and loading profiles and introduce additional level of uncertainty in network operation. The dynamic behaviors of such a network can be affected and the stable operation may be compromised. This paper proposes a probabilistic analysis approach for the evaluation of the effect of uncertain parameters on power system voltage and angular stability. Load margin, the damping of critical eigenvalues and the transient stability index have been chosen as the relevant stability indices for voltage stability, small-disturbance stability, and transient stability analysis, respectively. The Morris screening sensitivity analysis method coupled with a multivariate Gaussian copula to account for parameter correlations is used for the priority ranking of uncertain parameters. The approach is illustrated on a number of case studies using modified IEEE 68-bus NETS-NYPS test system. The results obtained in this paper reveal that the critical parameters appear as groups if the input dataset is correlated, and, hence even a parameter (which may be uninfluential individually) can have a significant impact on system dynamic behavior due to its correlation with other influential parameters.
引用
收藏
页码:2859 / 2869
页数:11
相关论文
共 47 条
[1]
Adrees Atia, 2016, 2016 Power Systems Computation Conference (PSCC), P1, DOI 10.1109/PSCC.2016.7540912
[2]
Adrees A, 2016, IEEE INT POWER ELEC, P257, DOI 10.1109/IPEMC.2016.7512295
[3]
Maximum penetration level of wind generation considering power system security limits [J].
Ahmadi, H. ;
Ghasemi, H. .
IET GENERATION TRANSMISSION & DISTRIBUTION, 2012, 6 (11) :1164-1170
[4]
[Anonymous], 2017, P 2 ACM IEEE S EDG C
[5]
[Anonymous], FUT EN SCEN UK GAS E
[6]
[Anonymous], 2000, SENSITIVITY ANAL
[7]
Stochastic Modeling for the Next Day Domestic Demand Response Applications [J].
Bina, M. Tavakoli ;
Ahmadi, Danial .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2015, 30 (06) :2880-2893
[8]
Probabilistic Analysis of Small-Signal Stability of Large-Scale Power Systems as Affected by Penetration of Wind Generation [J].
Bu, S. Q. ;
Du, W. ;
Wang, H. F. ;
Chen, Z. ;
Xiao, L. Y. ;
Li, H. F. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2012, 27 (02) :762-770
[9]
Impact of Increased Penetration of DFIG-Based Wind Turbine Generators on Transient and Small Signal Stability of Power Systems [J].
Gautam, Durga ;
Vittal, Vijay ;
Harbour, Terry .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2009, 24 (03) :1426-1434
[10]
Online Identification of Power System Dynamic Signature Using PMU Measurements and Data Mining [J].
Guo, Tingyan ;
Milanovic, Jovica V. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2016, 31 (03) :1760-1768