Transient Stability Preventive Control of Wind Farm Connected Power System Considering the Uncertainty

被引：0

作者：

Bian Y. ^{[1
]}

Wan X. ^{[1
]}

Zhou X. ^{[1
]}

机构：

[1] School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing

来源：

Energy Engineering: Journal of the Association of Energy Engineering | 2024年 / 121卷 / 06期

关键词：

chance-constrained programming; multi-objective PSO; Transient preventive control; TSCOPF; wind farm;

D O I：

10.32604/ee.2024.047678

中图分类号：

学科分类号：

摘要：

To address uncertainty as well as transient stability constraints simultaneously in the preventive control of wind farm systems, a novel three-stage optimization strategy is established in this paper. In the first stage, the probabilistic multi-objective particle swarm optimization based on the point estimate method is employed to cope with the stochastic factors. The transient security region of the system is accurately ensured by the interior point method in the second stage. Finally, the verification of the final optimal objectives and satisfied constraints are enforced in the last stage. Furthermore, the proposed strategy is a general framework that can combine other optimization algorithms. The proposed methodology is tested on the modified WSCC 9-bus system and the New England 39-bus system. The results verify the feasibility of the method. © 2024, Tech Science Press. All rights reserved.

引用

页码：1637 / 1656

页数：19

共 32 条

[1]

Ren J., Li B., Zhao M., Shi H., You H., Et al., A fast sequential transient stability preventive control approach driven by model interpretation, Electric Power Systems Research, 213, 2022, pp. 1-11, (2022)

[2]

Pizano-Martinez A., Fuerte-Esquivel C. R., Ruiz-Vega D., Global transient stability-constrained optimal power f low using SIME sensitivity analysis, IEEE PES General Meeting, pp. 1-8, (2010)

[3]

Geng G., Jiang Q., A two-level parallel decomposition approach for transient stability constrained optimal power f low, IEEE Transactions on Power Systems, 27, 4, pp. 2063-2073, (2012)

[4]

Xu Y., Chi Y., Yuan H., Stability-constrained optimization for modern power system operation and planning, (2023)

[5]

Xia S., Ding Z., Shahidehpour M., Chan K., Bu S., Et al., Transient stability-constrained optimal power f low calculation with extremely unstable conditions using energy sensitivity method, IEEE Transactions on Power Systems, 36, 1, pp. 355-365, (2020)

[6]

Xiang Y., Liu Y., Yang J., Yang W., A chance-constrained optimization model for determining renewables penetration limit in power systems, Electric Power Components and Systems, 44, 7, pp. 701-712, (2016)

[7]

Villegas C., Rios M. A., Probabilistic contingency severity index for dynamic reactive power planning, 2018 IEEE PES Transmission & Distribution Conference and Exhibition-Latin America, pp. 1-5, (2018)

[8]

Xia S., Luo X., Chan K. W., Zhou M., Li G., Probabilistic transient stability constrained optimal power f low for power systems with multiple correlated uncertain wind generations, IEEE Transactions on Sustainable Energy, 7, 3, pp. 1133-1144, (2016)

[9]

Lotfi H., Ghazi R., Optimal participation of demand response aggregators in reconfigurable distribution system considering photovoltaic and storage units, Journal of Ambient Intelligence and Humanized Computing, 12, pp. 2233-2255, (2021)

[10]

Lotfi H., Multi-objective energy management approach in distribution grid integrated with energy storage units considering the demand response program, International Journal of Energy Research, 44, 13, pp. 10662-10681, (2020)

← 1 2 3 4 →