Voltage Stability Assessment using Artificial Neural Network

被引:0
作者
Sharma, Ankit Kumar [1 ]
Saxena, Akash [2 ]
Soni, Bhanu Pratap [3 ]
Gupta, Vikas [3 ]
机构
[1] Jaipur Natl Univ, Dept Elect Engn, Jaipur 302017, Rajasthan, India
[2] Swami Keshvanand Inst Technol, Dept Elect Engn, Jaipur 302017, Rajasthan, India
[3] Malaviya Natl Inst Technol, Dept Elect Engn, Jaipur 302017, Rajasthan, India
来源
2018 IEEMA ENGINEER INFINITE CONFERENCE (ETECHNXT) | 2018年
关键词
ANN; FVSI; FFBPN; LR; RBFN; IEEE Bus Test-System; MSE; Regression; FLOW;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In deregulated environment voltage stability has become very important factor for the purpose of analysis. In this paper some important features associated with voltage stability use in power system have discussed. Line Stability index is used for estimation of the maximum loadability and in other words index is used to recognise the weak bus in electrical power system. In this paper Artificial Neural Networks (ANNs) are used for assessment of voltage stability or to confirm secure and insecure mode of the power system. The input data of neural network are yield from the Newton-Raphson (NR) load flow analysis in the platform of MATLAB R2015b. The result obtained from the N-R method also validates through Feed-Forward Back Propagation (FFBP) Layer Recurrent (LR) and Radial Basis Function Network (RBFN) in terms of accuracy to foresee the status of the power system. The effectiveness of the analyzed methods is validated through IEEE 14 test system and IEEE 30 test bus system, using Fast Voltage Stability Index (FVSI).
引用
收藏
页数:5
相关论文
共 50 条
  • [41] An improved Artificial Neural Network using Arithmetic Optimization Algorithm for damage assessment in FGM composite plates
    Khatir, Samir
    Tiachacht, Samir
    Cuong Le Thanh
    Ghandourah, Emad
    Mirjalili, Seyedali
    Wahab, Magd Abdel
    COMPOSITE STRUCTURES, 2021, 273
  • [42] Using artificial neural network models for groundwater level forecasting and assessment of the relative impacts of influencing factors
    Lee, Sanghoon
    Lee, Kang-Kun
    Yoon, Heesung
    HYDROGEOLOGY JOURNAL, 2019, 27 (02) : 567 - 579
  • [43] Assessment of Relationship Between Static and Dynamic Load Using Regression Analysis and Artificial Neural Network Model
    Abulkareem, Ahmed H.
    SOIL TESTING, SOIL STABILITY AND GROUND IMPROVEMENT, 2018, : 269 - 283
  • [44] Cross-Correlation Estimation in Artificial Neural Network for Uncertainty Assessment
    Carratu, Marco
    Gallo, Vincenzo
    Laino, Valter
    Liguori, Consolatina
    Pietrosanto, Antonio
    Lundgren, Jan
    2024 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE, I2MTC 2024, 2024,
  • [45] Optimization of Reactive Power and Voltage Control in Power System Using Hybrid Artificial Neural Network and Particle Swarm Optimization
    Kanata, Sabhan
    Sianipar, Gibson H. M.
    Maulidevi, Nur Ulfa
    2018 2ND INTERNATIONAL CONFERENCE ON APPLIED ELECTROMAGNETIC TECHNOLOGY (AEMT), 2018, : 67 - 72
  • [46] Prediction of Pile Axial Bearing Capacity Using Artificial Neural Network and Random Forest
    Tuan Anh Pham
    Hai-Bang Ly
    Van Quan Tran
    Loi Van Giap
    Huong-Lan Thi Vu
    Hong-Anh Thi Duong
    APPLIED SCIENCES-BASEL, 2020, 10 (05):
  • [47] Dynamic Behavior Forecast of an Experimental Indirect Solar Dryer Using an Artificial Neural Network
    Becerro, Angel Tlatelpa
    Martinez, Ramiro Rico
    Lopez-Vidana, Erick Cesar
    Palacios, Esteban Montiel
    Segundo, Cesar Torres
    Pacheco, Jose Luis Gadea
    AGRIENGINEERING, 2023, 5 (04): : 2423 - 2438
  • [48] STABILITY AND SEEPAGE OF EARTH DAMS WITH TOE FILTER (CALIBRATED WITH ARTIFICIAL NEURAL NETWORK)
    Jamel, Asmaa Abdul Jabbar
    Ali, Muataz Ibrahim
    JOURNAL OF ENGINEERING SCIENCE AND TECHNOLOGY, 2021, 16 (05): : 3712 - 3725
  • [49] Voltage Stability Monitoring Using Reduced Network and Measurement Transformation
    Ashraf, Syed Mohammad
    Chakrabarti, S.
    2015 AUSTRALASIAN UNIVERSITIES POWER ENGINEERING CONFERENCE (AUPEC), 2015,
  • [50] Predictions of apple bruise volume using artificial neural network
    Zarifneshat, Saeed
    Rohani, Abbas
    Ghassemzadeh, Hamid Reza
    Sadeghi, Morteza
    Ahmadi, Ebrahim
    Zarifneshat, Masoud
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2012, 82 : 75 - 86