Neural net based determination of generator-shedding requirements in electric power systems

1992 ◽  
Vol 139 (5) ◽  
pp. 427 ◽  
Author(s):  
M. Djukanovic ◽  
D.J. Sobajic ◽  
Y.-H. Pao
Keyword(s):  
Power Systems ◽  
Electric Power ◽  
Electric Power Systems ◽  
Neural Net

scholarly journals Determination of Critically Objects of Electric Power Systems from the Position of Energy Security

2018 ◽  
Vol 58 ◽  
pp. 03009 ◽  
Author(s):  
Dmitry Krupenev
Keyword(s):  
Power Systems ◽  
Power System ◽  
Electric Power ◽  
Energy Security ◽  
Electric Power Systems ◽  
Time Interval ◽  
Factors Affecting ◽  
Interconnected Power System ◽  
The Given

The paper deal the problem of definition and ranking of critical objects (CO) in electric power systems (EPS). The identification of the CO is necessary for the timely adoption of measures to organize the provision of the required level of energy security of the region where the object is location. The adequacy model is used for determine the critical objects of EPS, within the framework of which the simulation of the functioning of EPS during the given time interval is carried out, taking into account the main random factors affecting its operation. Approbation of the proposed approach is presented on the interconnected power system.

scholarly journals Flexibility and Operating Reserves in Electric Power Systems

2020 ◽  
Vol 209 ◽  
pp. 02001
Author(s):  
Elena Aksaeva ◽  
Anna Glazunova
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Electric Power ◽  
Time Horizon ◽  
Renewable Energy Sources ◽  
Probabilistic Method ◽  
Electric Power Systems ◽  
Energy Sources ◽  
Cumulative Probability

Maintaining the efficiency of electric power systems (EPSs) requires some flexibility margin, which decreases in the case of adopting a variety of renewable energy sources (RESs). For this reason, the determination of the EPS flexibility several hours ahead becomes especially urgent. In this study, the flexibility of a 5-node EPS with a four-minute load change during a 6-hour time horizon is calculated. To this end, a probabilistic method based on the analysis of the cumulative probability of the available flexibility is used.

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