scholarly journals Risk-based security assessment of power system voltage drop: a case study of Nigerian 330KV 41-bus transmission grid

2018 ◽  
Vol 37 (3) ◽  
pp. 735
Author(s):  
U. N. Asibeluo ◽  
T. C. Madueme
2011 ◽  
Vol 467-469 ◽  
pp. 1175-1181
Author(s):  
An Jia Mao ◽  
Jin He

Modern power system has been gradually developed into a complex system with the features of multi-level structure, multi-time scale, a variety of control parameters, wide-area, open, uncertainties, non-autonomous and it is difficult to indicate the security level of power system by a single index. Therefore, power system security assessment based on theory of comprehensive assessment is developed rapidly in recent years. However, traditional comprehensive assessment method considers few about the balance of the indices, when there are great differences between the value of the indices, it is easy to take place the phenomenon that the small indices has been “submerged”, which will influence the rationality of the comprehensive evaluation result. In this paper, a comprehensive assessment model which considers the influence of the index balance is established. By introducing the balance coefficient, the model can amend the original judgment matrix and the weight obtained by traditional AHP method. Since the coordinated and balanced situation of the indices have been reflected in the evaluation process, the results of the assessment model proposed in this paper has more scientific nature and more credibility. Finally, an example is provided to validate the model in this paper.


Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1581
Author(s):  
Deepak Kumar Gupta ◽  
Amitkumar V. Jha ◽  
Bhargav Appasani ◽  
Avireni Srinivasulu ◽  
Nicu Bizon ◽  
...  

The automatic load frequency control for multi-area power systems has been a challenging task for power system engineers. The complexity of this task further increases with the incorporation of multiple sources of power generation. For multi-source power system, this paper presents a new heuristic-based hybrid optimization technique to achieve the objective of automatic load frequency control. In particular, the proposed optimization technique regulates the frequency deviation and the tie-line power in multi-source power system. The proposed optimization technique uses the main features of three different optimization techniques, namely, the Firefly Algorithm (FA), the Particle Swarm Optimization (PSO), and the Gravitational Search Algorithm (GSA). The proposed algorithm was used to tune the parameters of a Proportional Integral Derivative (PID) controller to achieve the automatic load frequency control of the multi-source power system. The integral time absolute error was used as the objective function. Moreover, the controller was also tuned to ensure that the tie-line power and the frequency of the multi-source power system were within the acceptable limits. A two-area power system was designed using MATLAB-Simulink tool, consisting of three types of power sources, viz., thermal power plant, hydro power plant, and gas-turbine power plant. The overall efficacy of the proposed algorithm was tested for two different case studies. In the first case study, both the areas were subjected to a load increment of 0.01 p.u. In the second case, the two areas were subjected to different load increments of 0.03 p.u and 0.02 p.u, respectively. Furthermore, the settling time and the peak overshoot were considered to measure the effect on the frequency deviation and on the tie-line response. For the first case study, the settling times for the frequency deviation in area-1, the frequency deviation in area-2, and the tie-line power flow were 8.5 s, 5.5 s, and 3.0 s, respectively. In comparison, these values were 8.7 s, 6.1 s, and 5.5 s, using PSO; 8.7 s, 7.2 s, and 6.5 s, using FA; and 9.0 s, 8.0 s, and 11.0 s using GSA. Similarly, for case study II, these values were: 5.5 s, 5.6 s, and 5.1 s, using the proposed algorithm; 6.2 s, 6.3 s, and 5.3 s, using PSO; 7.0 s, 6.5 s, and 10.0 s, using FA; and 8.5 s, 7.5 s, and 12.0 s, using GSA. Thus, the proposed algorithm performed better than the other techniques.


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