Assessment of voltage stability based on power transfer stability index using computational intelligence models
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...
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          | Published in | International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering Vol. 11; no. 4; p. 2790 | 
|---|---|
| Main Authors | , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        Yogyakarta
          IAES Institute of Advanced Engineering and Science
    
        01.08.2021
     | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 2088-8708 2722-256X 2722-2578 2722-2578 2088-8708  | 
| DOI | 10.11591/ijece.v11i4.pp2790-2797 | 
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| Abstract | 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 Vi, δi, Pd, Qd 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 algorithms (CA-NN). The MATLAB utilized to obtain most of the results. | 
    
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| AbstractList | 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 Vi, δi, Pd, Qd 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 algorithms (CA-NN). The MATLAB utilized to obtain most of the results. | 
    
| Author | Hussein, Husham Idan Salman, Ghassan Abdullah Ghadban, Ahmed Majeed  | 
    
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| Copyright | Copyright IAES Institute of Advanced Engineering and Science Aug 2021 | 
    
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| DOI | 10.11591/ijece.v11i4.pp2790-2797 | 
    
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| Snippet | 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... | 
    
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| SubjectTerms | Algorithms Artificial intelligence Power transfer Stability analysis Voltage collapse Voltage stability  | 
    
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| Title | Assessment of voltage stability based on power transfer stability index using computational intelligence models | 
    
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