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

Yıl 2023, Cilt: 4 Sayı: 1, 36 - 43, 21.06.2023

Alıyu Sabo Kamaluddeen Ibrahım Kanya Nazıru Shu'aıbu Chıgozıe Onyema Ahmed Alıyu Hadıza Tanko Sama'ıla Kwasau

https://doi.org/10.53525/jster.1233034

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] 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] 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] 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] 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] 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] 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] 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] 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] 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] W. A. Alsulami, “Fast and Accurate Load Flow Solution for On-line Applications Using ANN,” vol. I, no. June, 2017.
• [11] V. Basetti, S. S. Rangarajan, C. K. Shiva, S. Verma, R. E. Collins, and T. Senjyu, “A quasi-oppositional heap-based optimization technique for power flow analysis by considering large scale photovoltaic generator,” Energies, vol. 14, no. 17, 2021, doi: 10.3390/en14175382.
• [12] M. Tostado-véliz, S. Kamel, T. Alquthami, and S. Member, “A three-stage algorithm based on a Semi- Implicit approach for solving the Power-Flow in realistic large-scale ill-conditioned systems,” 2020, doi: 10.1109/ACCESS.2020.2975058.
• [13] M. Tostado-véliz, H. M. Hasanien, S. Member, and R. A. Turky, “Mann-Iteration Process for Power Flow Calculation of Large-Scale Ill-Conditioned Systems : Theoretical Analysis and Numerical Results,” vol. XX, pp. 1–12, 2021, doi: 10.1109/ACCESS.2021.3114969.
• [14] S. Abhyankar and A. J. Flueck, “Fast Power Flow Analysis using a Hybrid Current-Power Balance Formulation in Rectangular Coordinates,” no. 1.
• [15] F. Mumtaz, M. H. Syed, M. Al Hosani, and H. H. Zeineldin, “A Simple and Accurate Approach to Solve the Power Flow for Balanced Islanded Microgrids,” pp. 1–5.
• [16] L. P. System, Z. Liu, Y. Song, Y. Chen, S. Huang, and M. Wang, “Batched Fast Decoupled Load Flow for,” 2018 Int. Conf. Power Syst. Technol., no. 201804270000856, pp. 1775–1780, 2018.
• [17] R. Gono and Z. Leonowicz, “A New Approach Newton-Raphson Load Flow Analysis in Power System Networks with STATCOM,” no. August, 2020, doi: 10.1007/978-3-030-14907-9.