DocumentCode :
506653
Title :
Research on tie-line power adjustment of interconnected power system based on sensitivity analysis and neural network
Author :
Jiekang, Wu ; Junfeng, Han ; Cheng, Jiang
Author_Institution :
Sch. of Electr. Eng., Guangxi Univ., Nanning, China
Volume :
2
fYear :
2009
fDate :
20-22 Nov. 2009
Firstpage :
40
Lastpage :
44
Abstract :
Considering distinct locations and inhomogeneous power plants playing different roles and effecting on the interconnected power system, as well as the purpose of pursuing best efficiency and stability for the whole interconnected power system, this paper presents a new method based on sensitivity analysis and neural network to solve the power regulation on tie-line in the interconnected power system. The sensitivity coefficients for the power plants relating to tie-line can be calculated and simulated by back propagation neural network, before which the appropriate samples setting of power plants should be acquired adequately from operating BPA software. The effectiveness of the proposed method is demonstrated on IEEE 30-bus system comprising of plants units of actual power grid in different regions and compared with some conventional approaches. The simulation results show that the proposed new approach is able to obtain higher quality solutions efficiently than the conventional approaches.
Keywords :
backpropagation; neural nets; power grids; power system interconnection; power system stability; IEEE 30-bus system; backpropagation neural network; power grids; power regulation; power system interconnection; power system stability; sensitivity analysis; tie-line power adjustment; Neural networks; Power generation; Power grids; Power system analysis computing; Power system economics; Power system interconnection; Power system security; Power system simulation; Power system stability; Sensitivity analysis; Interconnected power system; Neural Network; Sensitivity Analysis; Tie-line;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
Type :
conf
DOI :
10.1109/ICICISYS.2009.5358075
Filename :
5358075
Link To Document :
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