DocumentCode :
3352327
Title :
Dual Heuristic Programming Based Control of SSSC in Power Systems
Author :
Zhang, Jianhua ; Zhang, Aiguo ; Shang, Jingfu
Author_Institution :
Sch. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing
fYear :
2009
fDate :
27-31 March 2009
Firstpage :
1
Lastpage :
4
Abstract :
Power system installed with SSSC is a large-scale nonlinear, indeterminist, multivariable system, and the traditional PI controller has a limited application in some cases because of its non-adaptive parameters. This paper presents the design of a neuron-controller for a SSSC that augments the conventional PI controller. The neuron controller uses adaptive critic design (ACD) with emphasis on dual heuristic programming (DHP). A studying example is carried out to estimate good robustness and adaptability of the proposed controller in the Matlab dynamic simulation platform. Results are presented to show that the DHP based neuron controller performs is better than the conventional PI controller, especially when the system conditions and configuration change. The numerical simulation results of using this method in one SSSC connected to power system verified the adaptability and feasibility of the proposed control strategy in power flow control of power systems.
Keywords :
PI control; control engineering computing; heuristic programming; neurocontrollers; power system interconnection; Matlab dynamic simulation platform; SSSC; adaptive critic design; dual heuristic programming-based control; multivariable system; neuron-controller; nonlinear system; power flow control; power systems; static synchronous series compensator; traditional PI controller; Control systems; Large-scale systems; MIMO; Neurons; Nonlinear control systems; Power system control; Power system dynamics; Power system simulation; Power systems; Programmable control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-2486-3
Electronic_ISBN :
978-1-4244-2487-0
Type :
conf
DOI :
10.1109/APPEEC.2009.4918295
Filename :
4918295
Link To Document :
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