scholarly journals Assessment of voltage stability based on power transfer stability index using computational intelligence models

2021 ◽  
Vol 11 (4) ◽  
pp. 2790
Author(s):  
Ahmed Majeed Ghadban ◽  
Ghassan Abdullah Salman ◽  
Husham Idan Hussein
Keyword(s):  
Computational Intelligence ◽  
Input Data ◽  
Voltage Stability ◽  
Stability Index ◽  
Hybrid Algorithms ◽  
Voltage Collapse ◽  
Power Transfer ◽  
Intelligence Models ◽  
Weak Bus ◽  
Two Hybrid

<span>In this paper, the importance of voltage stability is explained, which is a great problem in the EPS. The estimation of VS is made a priority so as to make the power system stable and prevent it from reaching voltage collapse. The power transfer stability index (PTSI) is used as a predictor utilized in a PSN to detect the instability of voltages on weakened buses. A PSI is used to obtain a voltage assessment of the PSNs. Two hybrid algorithms are developed. The (CA-NN) and the (PSO-NN). After developing algorithms, they are compared with the actual values of PTSI NR method. The algorithms installed on the 24 bus Iraqi PS. The actual values of PTSI are the targets needed. They are obtained from the NR algorithm when the input data is V<sub>i</sub>, δ<sub>i</sub>, P<sub>d</sub>, Q<sub>d</sub> for the algorithm. The results indicate that a weak bus that approaches voltage collapse and all results were approximately the same. There is a slight difference with the actual results and demonstrated classical methods are slower and less accurate than the hybrid algorithms. It also demonstrates the validation and effectiveness of algorithms (CA-NN, and PSO-NN) for assessing voltage-prioritizing </span><span>algorithms</span><span> (CA-NN). The MATLAB utilized to obtain most of the results.</span>

Voltage Stability Index of Radial Distribution Networks by Considering Distributed Generator for Different Types of Loads

2016 ◽  
Vol 5 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Tapan Kumar Chattopadhyay ◽  
Sumit Banerjee ◽  
Chandan Kumar Chanda
Keyword(s):  
Stability Analysis ◽  
Radial Distribution ◽  
Distribution Systems ◽  
Voltage Stability ◽  
Stability Index ◽  
Distribution Networks ◽  
Voltage Collapse ◽  
Distributed Generator ◽  
Voltage Stability Index ◽  
Different Types

The paper presents an approach on voltage stability analysis of distribution networks for loads of different types. A voltage stability index is proposed for identifying the node, which is most sensitive to voltage collapse. It is shown that the node, at which the value of voltage stability index is maximum, is more sensitive to voltage collapse. For the purpose of voltage stability analysis, constant power, constant current, constant impedance and composite load modeling are considered. Distributed generation can be integrated into distribution systems to meet the increasing load demand. It is seen that with the insertion of distributed generator (DG), load capability limit of the feeder has increased for all types of loads. By using this voltage stability index, one can measure the level of voltage stability of radial distribution systems and thereby appropriate action may be taken if the index indicates a poor level of stability. The effectiveness of the proposed method is demonstrated through two examples.

scholarly journals Weak bus-constrained PMU placement for complete observability of a connected power network considering voltage stability indices

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Rohit Babu ◽  
Saurav Raj ◽  
Biplab Bhattacharyya
Keyword(s):  
New England ◽  
Voltage Stability ◽  
Programming Model ◽  
Stability Index ◽  
Load Flow ◽  
Electrical Network ◽  
Power Network ◽  
Measurement Units ◽  
Pmu Placement ◽  
Weak Bus

AbstractPhasor measurement units (PMUs) are preferred for installation at weak buses in a power network. Therefore, the weak buses need to be located and the strategic locations of PMUs identified to ensure network observability. Thus, the primary aim of this work is to identify the placements of the maximum number of PMUs installed at the weak buses in the electrical network. The voltage collapse proximity indicator, line stability index, fast voltage stability index, and a new voltage stability indicator utilizing load flow measurement are used to determine the weak buses. A novel deterministic methodology based on a binary-integer linear programming model is then proposed to determine the optimal locations of PMUs. The effect of a single PMU outage considering the weak buses is also demonstrated. The effectiveness of the developed approach is tested and validated on the standard IEEE 14-, 118-, 300-, and New England 39-bus systems. The obtained results are also compared to those using different weak bus methodologies.

scholarly journals Voltage collapse prediction using artificial neural network

2021 ◽  
Vol 11 (1) ◽  
pp. 124
Author(s):  
Samuel Isaac ◽  
Soyemi Adebola ◽  
Awelewa Ayokunle ◽  
Katende James ◽  
Awosope Claudius
Keyword(s):  
Neural Network ◽  
Voltage Stability ◽  
Stability Index ◽  
Voltage Collapse ◽  
Feed Forward Neural Network ◽  
Voltage Stability Index ◽  
Voltage Instability ◽  
Collapse Prediction ◽  
R Value ◽  
Bus System

Unalleviated voltage instability frequently results in voltage collapse; which is a cause of concern in power system networks across the globe but particularly in developing countries. This study proposed an online voltage collapse prediction model through the application of a machine learning technique and a voltage stability index called the new line stability index (NLSI_1). The approach proposed is based on a multilayer feed-forward neural network whose inputs are the variables of the NLSI_1. The efficacy of the method was validated using the testing on the IEEE 14-bus system and the Nigeria 330-kV, 28-bus National Grid (NNG). The results of the simulations indicate that the proposed approach accurately predicted the voltage stability index with an R-value of 0.9975 with a mean square error (MSE) of 2.182415x10<sup>−5</sup> for the IEEE 14-bus system and an R-value of 0.9989 with an MSE of 1.2527x10<sup>−7</sup> for the NNG 28 bus system. The results presented in this paper agree with those found in the literature.

scholarly journals Voltage Collapse Prediction of IEEE 30-Bus system

2021 ◽  
Vol 28 (1) ◽  
pp. 98-112
Author(s):  
Mohammed Ibrahim ◽  
Abdulsattar Jasim
Keyword(s):  
Power System ◽  
Modal Analysis ◽  
Voltage Stability ◽  
Stability Index ◽  
Maximum Load ◽  
Voltage Collapse ◽  
Analysis Method ◽  
The Stability ◽  
Stability Indices ◽  
Participation Factor

Voltage collapse in the power system occurs as a result of voltage instability, thus which lead to a blackout, and this is a constant concern for network workers and customers alike. In this paper, voltage collapse is studied using two approved methods: the modal analysis method and voltage stability indices. In the modal analysis method, the eigenvalues were calculated for all the load buses, through which it is possible to know the stability of the power system, The participation factor was also calculated for the load buses, which enables us to know the weakest buses in the system. As for the Voltage stability Indices method, two important indices were calculated, which are: Fast Voltage Stability Index (FVSI) and Line stability index (Lmn). These two indices give a good visualization of the stability of the system and the knowledge of the weakest buses, as well as the Maximum load-ability of the load buses. The above mentioned two methods were applied using software code using MATLAB \ R2018a program to the IEEE 30-Bus test system. In the modal analysis, the buses which have the maximum participation factor are 26, 29, and 30 this indicates that they are the weakest in the system. as well as in the voltage stability indices. These buses have the lowest maximum load ability which demonstrates the possibility of using both methods or one of them to study the voltage collapse.

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