Power system steady state security analysis using vector processing computers

1992 ◽  
Vol 7 (4) ◽  
pp. 1451-1455 ◽  
Author(s):  
D.M. Anderson ◽  
B.F. Wollenberg
Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5260
Author(s):  
Sunoh Kim ◽  
Jin Hur

As renewable energy resources such as wind and solar power are developing and the penetration of electric vehicles (EVs) is increasingly integrated into existing systems, uncertainty and variability in power systems have become important issues. The charging demands for EVs and wind power output are recognized as highly variable generation resources (VGRs) with uncertainty, which can cause unexpected disturbances such as short circuits. This can deteriorate the reliability of existing power systems. In response, research is required to identify the uncertainties presented by VGRs and is required to examine the ability of power system models to reflect those uncertainties. The deterministic method, which is the most basic method that is currently in use, does not reflect the uncertainty of system components. Therefore, this paper proposes a probabilistic method to assess the steady-state security of power systems, reflecting the uncertainty of VGRs using Monte Carlo simulation (MCS). In the proposed method, the empirical EVs charging demand and wind power output data are modeled as a probability distribution, and then MCS is performed, integrating the power system operation to represent the steady-state security as a probability index. To verify the method proposed in this paper, a security analysis was performed based on the systems in Jeju Island, South Korea, where the penetration of wind power and EVs is expanding rapidly.


Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 148
Author(s):  
Lili Wu ◽  
Ganesh K. Venayagamoorthy ◽  
Jinfeng Gao

Power system steady-state security relates to its robustness under a normal state as well as to withstanding foreseeable contingencies without interruption to customer service. In this study, a novel cellular computation network (CCN) and hierarchical cellular rule-based fuzzy system (HCRFS) based online situation awareness method regarding steady-state security was proposed. A CCN-based two-layer mechanism was applied for voltage and active power flow prediction. HCRFS block was applied after the CCN prediction block to generate the security level of the power system. The security status of the power system was visualized online through a geographic two-dimensional visualization mechanism for voltage magnitude and load flow. In order to test the performance of the proposed method, three types of neural networks were embedded in CCN cells successively to analyze the characteristics of the proposed methodology under white noise simulated small disturbance and single contingency. Results show that the proposed CCN and HCRFS combined situation awareness method could predict the system security of the power system with high accuracy under both small disturbance and contingencies.


2010 ◽  
Vol 23 (1) ◽  
pp. 119-138
Author(s):  
Dragan Popovic

The basic objective of this paper is to present the relevant methodological and practical aspects of two efficient procedures for initialization of steady-state security analyses of electric power interconnection. The first procedure gives the load flow solution for known initial generators scheduling and the second one gives the load-flow solution in conditions of bilateral or multilateral exchange programs realization. Those procedures are fully consistent with the specially developed procedure for steady-state security analysis, which is based on successive solutions of load-flow in characteristic post-dynamic quasi-stationary states, occurring after the considered disturbances. The efficiency of proposed procedures is demonstrated on the example of real electric power interconnection in the Balkan area. .


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