Research on emergency control method considering severity of overheating of overload line
DOI:10.19783/j.cnki.pspc.181135
Key Words:emergency control  heat accumulation limit value  power sensitivity matrix  minimized economic compensation  particle swarm optimization
Author NameAffiliationE-mail
MAO Sijie Shanxi Key Lab of Power System Operation and Control, Taiyuan University of Technology, Taiyuan 030024, China  
JIA Yanbing* Shanxi Key Lab of Power System Operation and Control, Taiyuan University of Technology, Taiyuan 030024, China jybtyut@163.com 
ZHANG Qi* Shanxi Key Lab of Power System Operation and Control, Taiyuan University of Technology, Taiyuan 030024, China  
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Abstract:The existing emergency control algorithm doesn’t consider the limit of generator adjustment speed when developing the emergency control scheme, and can’t flexibly adjust the control scheme according to the overload degree of the overload line, which may cause the practicality of the emergency control scheme poor, therefore, a method that takes into account the severity of the heating of overload line is proposed. Firstly, the heating model of the overload line in control process is established, and the heat accumulation limit value of the overload line is defined to describe the dispatcher's expectation to eliminate the line overload. Secondly, on the basis of power sensitivity matrix, active power circulating on the overload line is adjusted with the output of the generator and the load-cutting and cutting machine, so as to realize the calculation of the heat of the overload line during control period. Finally, with the goal of minimizing economic compensation, an optimization model is established, and the model is solved by simulated annealing particle swarm optimization. The obtained scheme can utilize the advantages of low cost of adjusting the output of the generator and short time of cutting the load and the generator, which has stronger practicability. The correctness and superiority of this method are verified in the IEEE39-node system. This work is supported by National Key Research and Development Program of China (No. 2018YFB0904700) and National Natural Science Foundation of China (No. 51777132).
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