İnceleme Makalesi

A Review of State-of-the-Art Techniques for Power Flow Analysis

Cilt: 4 Sayı: 1 21 Haziran 2023
Alıyu Sabo , Kamaluddeen Ibrahım Kanya *, Nazıru Shu'aıbu , Chıgozıe Onyema , Ahmed Alıyu , Hadıza Tanko , Sama'ıla Kwasau
PDF İndir
TR EN

A Review of State-of-the-Art Techniques for Power Flow Analysis

Öz

A Review of State-of-the-Art Techniques for Power Flow Analysis (PFA) which are newly proposed is presented in this paper. However, some of the existing classical methods for the Power Flow Analysis such as Newton-Raphson method, Gauss-Seiadel method, and Fast Decoupled Power Flow Technique were also discussed so as to give a background and a wider view of the improvements recorded so far. From the findings, State-of-the-Art Techniques such as Particle Swamp Optimization Algorithm for optimal Power Flow Incorporating Wind Farms, Hybrid Firefly and Particle Swamp Optimization Algorithm, Mann Iteration Process Technique for III-Conditioned System, and Modified Gauss-Seidel (MGS) method have shown superiority over and above the existing classical methods when it comes to accuracy, convergence speed and overall efficiency. Particularly, there are two newly proposed methods for dc grids namely Direct Matrix–Current Application and Direct Matrix-Impedance Approximation methods that stand out as regards accuracy, convergence and computational speed which means they can be used in planning, optimization and analysis purposes. Furthermore, MGS was validated using a 6-bus system in 3 cases. Each case had less than 25 iterations and the maximum voltage magnitude, phase angle and system frequency error in all the cases studied were less than 0.01%, 0.1% and 0.001% respectively.

Anahtar Kelimeler

Power Flow, Newton-Raphson, Gaus-Siedel, Fast Decoupled

Kaynakça

  1. [1] M. Z. Islam et al., “Optimal Power Flow using a Novel Harris Hawk Optimization Algorithm to Minimize Fuel Cost and Power loss,” 2019 IEEE Conf. Sustain. Util. Dev. Eng. Technol. CSUDET 2019, no. November, pp. 246–250, 2019, doi: 10.1109/CSUDET47057.2019.9214591.
  2. [2] V. Veerasamy et al., “A novel RK4-Hopfield Neural Network for Power Flow Analysis of power system,” Appl. Soft Comput. J., vol. 93, p. 106346, 2020, doi: 10.1016/j.asoc.2020.106346.
  3. [3] S. B. Efe and M. Cebecİ, “Power flow analysis by Artificial Neural Network,” vol. 2, no. 6, pp. 204–208, 2013, doi: 10.11648/j.ijepe.20130206.11.
  4. [4] V. Veerasamy, R. Ramachandran, M. Thirumeni, and B. Madasamy, “Load flow analysis using generalised Hopfield neural network,” 2018, doi: 10.1049/iet-gtd.2017.1211.
  5. [5] Z. Li and J. Yu, “Approximate Linear Power Flow Using Logarithmic Transform of Voltage Magnitudes With Reactive Power and Transmission Loss Consideration,” vol. 33, no. 4, pp. 4593–4603, 2018.
  6. [6] B. G. Risi, F. Riganti-Fulginei, and A. Laudani, “Modern Techniques for the Optimal Power Flow Problem: State of the Art,” Energies, vol. 15, no. 17, 2022, doi: 10.3390/en15176387.
  7. [7] N. H. Van Der Blij et al., “Improved Power Flow Methods for DC Grids,” IEEE Int. Symp. Ind. Electron., vol. 2020-June, no. 734796, pp. 1135–1140, 2020, doi: 10.1109/ISIE45063.2020.9152570.
  8. [8] S. I. Evangeline, “Particle Swarm Optimization Algorithm for Optimal Power Flow Incorporating Wind Farms,” 2019 IEEE Int. Conf. Intell. Tech. Control. Optim. Signal Process., pp. 1–4, 2019, doi: 10.1109/INCOS45849.2019.8951385.
  9. [9] A. Khan, H. Hizam, N. I. bin A. Wahab, and M. L. Othman, “Optimal power flow using hybrid firefly and particle swarm optimization algorithm,” PLoS One, vol. 15, no. 8 August, pp. 1–21, 2020, doi: 10.1371/journal.pone.0235668.
  10. [10] W. A. Alsulami, “Fast and Accurate Load Flow Solution for On-line Applications Using ANN,” vol. I, no. June, 2017.

Kaynak Göster

APA
Sabo, A., Ibrahım Kanya, K., Shu’aıbu, N., Onyema, C., Alıyu, A., Tanko, H., & Kwasau, S. (2023). A Review of State-of-the-Art Techniques for Power Flow Analysis. Journal of Science, Technology and Engineering Research, 4(1), 36-43. https://doi.org/10.53525/jster.1233034
AMA
1.Sabo A, Ibrahım Kanya K, Shu’aıbu N, vd. A Review of State-of-the-Art Techniques for Power Flow Analysis. Journal of Science, Technology and Engineering Research. 2023;4(1):36-43. doi:10.53525/jster.1233034
Chicago
Sabo, Alıyu, Kamaluddeen Ibrahım Kanya, Nazıru Shu’aıbu, vd. 2023. “A Review of State-of-the-Art Techniques for Power Flow Analysis”. Journal of Science, Technology and Engineering Research 4 (1): 36-43. https://doi.org/10.53525/jster.1233034.
EndNote
Sabo A, Ibrahım Kanya K, Shu’aıbu N, Onyema C, Alıyu A, Tanko H, Kwasau S (01 Haziran 2023) A Review of State-of-the-Art Techniques for Power Flow Analysis. Journal of Science, Technology and Engineering Research 4 1 36–43.
IEEE
[1]A. Sabo vd., “A Review of State-of-the-Art Techniques for Power Flow Analysis”, Journal of Science, Technology and Engineering Research, c. 4, sy 1, ss. 36–43, Haz. 2023, doi: 10.53525/jster.1233034.
ISNAD
Sabo, Alıyu - Ibrahım Kanya, Kamaluddeen - Shu’aıbu, Nazıru - Onyema, Chıgozıe - Alıyu, Ahmed - Tanko, Hadıza - Kwasau, Sama’ıla. “A Review of State-of-the-Art Techniques for Power Flow Analysis”. Journal of Science, Technology and Engineering Research 4/1 (01 Haziran 2023): 36-43. https://doi.org/10.53525/jster.1233034.
JAMA
1.Sabo A, Ibrahım Kanya K, Shu’aıbu N, Onyema C, Alıyu A, Tanko H, Kwasau S. A Review of State-of-the-Art Techniques for Power Flow Analysis. Journal of Science, Technology and Engineering Research. 2023;4:36–43.
MLA
Sabo, Alıyu, vd. “A Review of State-of-the-Art Techniques for Power Flow Analysis”. Journal of Science, Technology and Engineering Research, c. 4, sy 1, Haziran 2023, ss. 36-43, doi:10.53525/jster.1233034.
Vancouver
1.Alıyu Sabo, Kamaluddeen Ibrahım Kanya, Nazıru Shu’aıbu, Chıgozıe Onyema, Ahmed Alıyu, Hadıza Tanko, Sama’ıla Kwasau. A Review of State-of-the-Art Techniques for Power Flow Analysis. Journal of Science, Technology and Engineering Research. 01 Haziran 2023;4(1):36-43. doi:10.53525/jster.1233034