期刊名称：International Journal on Electrical Engineering and Informatics
印刷版ISSN：2085-6830
出版年度：2015
卷号：7
期号：1
DOI：10.15676/ijeei.2015.7.1.12
出版社：School of Electrical Engineering and Informatics
摘要：In this paper, a scenario based optimal power flow (OPF) is presented consideringeconomic (operation cost minimization) and security objective functions. Security objectivefunctions include both reliability and system transient stability improvement. Energy notsupplied (ENS) cost is considered as the criterion for system reliability and critical clearingtime (CCT) is considered as the criterion for power system dynamic stability. In order toreduce the computational burden of the proposed method, off-line training of neural network isused to determine CCT based on the system operating point. For this purpose, CCT parameteris calculated in Dig silent Software environment for various operating points of system and adata set is obtained to train neural network. In the proposed method, it is tried to improvedynamic stability of system, as well as decreasing the operation cost in post contingency statethrough optimal load shedding and generation rescheduling. Genetic algorithm (GA) is used asthe optimization tool. The proposed framework is tested on IEEE 39-bus test system andresults show efficiency of the proposed method.
