Journal of Shandong University(Engineering Science) ›› 2019, Vol. 49 ›› Issue (5): 9-16.doi: 10.6040/j.issn.1672-3961.0.2019.096

• Engineering—Special Topic on Artificial Intelligence Application • Previous Articles     Next Articles

Optimization method for parallel coordination restoration strategy of asynchronous power grid

Xueping GU(),Chao YANG*(),Haiping LIANG,Yuanbo WANG,Shaoyan LI   

  1. School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, Hebei, China
  • Received:2019-03-11 Online:2019-10-20 Published:2019-10-18
  • Contact: Chao YANG E-mail:xpgu@ncepu.edu.cn;shutong05@126.com
  • Supported by:
    国家自然科学基金资助项目(51277076);中央高校基金科研业务费专项资金资助项目(2018MS085)

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Abstract:

Aiming at asynchronous power grid restoration after a blackout, an optimization method of parallel coordinated restoration strategy was proposed. This method adopted the thinking of serial and parallel restoration, used the high voltage direct current (HVDC) to coordinate sending end and receiving end power grids, and finally restored whole power system. Based on determining each AC subnet as a sending role or receiving role, the source characteristic of converter station in sending end gird and the load characteristic of converter station in receiving end gird were analysed. An optimization model for parallel coordinated restoration of asynchronous power grid was established, and the coordinated restoration process of HVDC, sending end and receiving end power grids were emphatically studied. The multi-population genetic algorithm (MPGA) was used to solve this model, then the optimal restoration scheme and the optimal starting time of HVDC were obtained. An asynchronous power grid example which was constructed based on the IEEE 39 bus system was given to verify the proposed method. The results showed that this optimization method was feasible, and it was suitable for the formulation of asynchronous power grid restoration scheme.

Key words: asynchronous power grid, HVDC, determination of sending end and receiving end, parallel coordinated restoration, multi-population genetic algorithm

CLC Number: 

  • TM76

Fig.1

Power supply and load characteristic curves ofconverter station"

Fig.2

Flow chart of the algorithm"

Fig.3

The example of asynchronous power grid based on IEEE 39 bus system"

Table 1

Unit parameters of the IEEE 39 bus system"

节点编号 PGN/MW 暂态电抗/p.u. df/(Hz·(p.u.)-1) 爬坡率K/(MW·h-1) 并网耗时/min
30 250 0.031 3.40 150.0 10
31 650 0.070 7.94 390.0 0
32 650 0.053 7.94 390.0 30
33 632 0.044 4.61 379.2 30
34 508 0.132 4.61 304.8 30
35 650 0.050 7.94 390.0 30
36 560 0.049 4.61 336.0 30
37 540 0.057 7.94 324.0 30
38 830 0.057 7.94 498.0 30
39 1 000 0.060 3.40 600.0 30

Table 2

Optimal restoration scheme"

阶段编号 送端 受端
电源节点 恢复时间/min 恢复支路及编号 电源节点 恢复时间/min 恢复支路及编号
1 31 0 31 0
2 39 40 14、12、15、16、17 32 38 14、13、18、20
3 30 56 2、1、5 30 58 10、8、6、3、5
4 37 90 4、41 37 92 4、41
5 38 136 40、44、46 39 106 1、2
6 32 176 11、13、10、18、20 38 142 40、44、46
7 33 220 8、6、7、30、26、27、33 33 182 9、24、25、27、33
8 34 254 41、32、34 35 218 28、35、37
9 35 296 9、28、25、24、35、37 36 252 36、39
10 36 332 29、38、39 34 286 32、34
11 42、31、45、43、19、23、21、22、3、36 11、42、12、45、21、43、17、16、29、26、19、15、30、23、7、38、31、22
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