Farmland Fertility Optimization for Designing of Interconnected Multi-machine Power System Stabilizer

Aliyu Sabo, Noor Izzri Abdul Wahab, Mohammad Lutfi Othman, Mai Zurwatul Ahlam Mohd Jaffar, Hamzeh Beiranvand

Abstract

This study describes the process of interconnected multi-machine power system stabilizer (PSS) optimization using a new intelligent technique called farmland fertility algorithm (FFA) to increase the stability of IEEE three machine nine bus power system and offset the low-frequency oscillations (LFOs) during a symmetrical 100 ms three-phase fault at bus 9. The FFA-PSS controller performance is compared with two familiar classical techniques, i.e. Genetic Algorithm (GA-PSS) and Particle Swarm Optimization (PSO-PSS) to confirm the capability of the proposed technique to realize improved system stability enhancement. The Eigenvalue simulation results with FFA produce stable Eigenvalues that increase the damping ratio of the Electromechanical Modes (EMs) to more than 0.1 with smaller overshoots and time to settle which shows the effectiveness of the method for multi-machine stability improvement. Also, the phasor simulation results show that the transient responses of the system rise time, settling time, peak time and peak magnitude were all impressively improved by an acceptable amount for the interconnected system with the proposed FFA-PSS thus, was able to control the LFOs effectively and produces enhanced performance compared to the GA and PSO based PSS. Similarly, the result validates the effectiveness of the proposed FFA tuned PSS for LFO control which demonstrates robustness, efficiency, and convergence speed ability than the classical GA and PSO tuning methods.

Keywords

Farmland fertility algorithm; Genetic algorithm; Low-frequency oscillation; Particle swarm optimization; Power system stabilizer.

Article Metrics

Abstract view : 439 times
PDF - 104 times

Full Text:

PDF

References

V. Veerasamy et al., A novel discrete wavelet transform-based graphical language classifier for identification of high-impedance fault in distribution power system, International Transactions on Electrical Energy Systems, February, 2020, 1–24.

M. Saadatmand, B. Mozafari, G. B. Gharehpetian and S. Soleymani, Optimal PID controller of large-scale PV farms for power systems LFO damping, International Transactions on Electrical Energy Systems, February, 2020, 1–14.

G. Tu, Y. Li, J. Xiang and J. Ma, Distributed power system stabiliser for multimachine power systems, IET Generation, Transmission & Distribution, 13(5), 2019, 603–612.

M. Singh, R. N. Patel and D. D. Neema, Robust tuning of excitation controller for stability enhancement using multi-objective metaheuristic firefly algorithm, Swarm and Evolutionary Computation, 44, 2019, 136–147.

B. Hekimoğlu, Robust fractional order PID stabilizer design for multi-machine power system using grasshopper optimization algorithm, Journal of the Faculty of Engineering and Architecture of Gazi University, 35(1), 2020, 165–180.

A. Faraji and A. Hesami Naghshbandy, A combined approach for power system stabilizer design using continuous wavelet transform and SQP algorithm, International Transactions on Electrical Energy Systems, 29(3), 2019, 1–18.

A. K. Gupta, K. Verma and K. R. Niazi, Robust coordinated control for damping low frequency oscillations in high wind penetration power system, International Transactions on Electrical Energy Systems, 29(5), 2019, 1–17.

A. Sabo, N. Izzri and A. Wahab, Rotor angle transient stability methodologies of power systems: A comparison, IEEE Student Conference on Research and Development (SCOReD), Malaysia, 2019, 1–6.

E. L. Miotto, P. B. De Araujo, E. D. V. Fortes, B. R. Gamino, L. Fabiano and B. Martins, Coordinated tuning of the parameters of pss and pod controllers using bioinspired algorithms, IEEE Transactions on Industry Applications, 54(4), 2018, 3845–3857.

H. Verdejo, R. Torres, V. Pino, W. Kliemann, C. Becker and J. Delpiano, Tuning of controllers in power systems using a heuristic-stochastic approach,” Energies, 12(12) 2325, 2019, 1–25.

M. Jokarzadeh, M. Abedini, and A. Seifi, Improving power system damping using a combination of optimal control theory and differential evolution algorithm, ISA Transactions, 90, 2019, 169–177.

T. Guesmi, A. Farah, H. H. Abdallah and A. Ouali, Robust design of multimachine power system stabilizers based on improved non-dominated sorting genetic algorithms,” Electrical Engineering, 100(3), 2018, 1351–1363.

D. Wang, N. Ma, M. Wei and Y. Liu, Parameters tuning of power system stabilizer PSS4B using hybrid particle swarm optimization algorithm, International Transactions on Electrical Energy Systems, 28(9), 2018, 1–17.

B. Dasu, M. Sivakumar and R. Srinivasarao, Interconnected multi-machine power system stabilizer design using whale optimization algorithm, Protection and Control of Modern Power Systems, 4(2), 2019, 1–11.

S. Ekinci and B. Hekimoǧlu, Parameter optimization of power system stabilizer via salp swarm algorithm, 5th International Conference on Electrical and Electronic Engineering (ICEEE 2018), Istanbul, Turkey, 2018, 143–147.

S. Ekinci, A. Demiroren, and B. Hekimoglu, Parameter optimization of power system stabilizers via kidney-inspired algorithm, Transactions of the Institute of Measurement and Control, 41(5), 2019, 1405–1417.

N. M. A. Ibrahim, B. E. Elnaghi, H. A. Ibrahim and H. E. A. Talaat, Performance assessment of bacterial foraging based power system stabilizer in multi-machine power system, International Journal of Intelligent Systems and Applications, 11(7), 2019, 43–53.

S. Ekinci, “Optimal design of power system stabilizer using sine cosine algorithm, Journal of the Faculty of Engineering and Architecture of Gazi University, 34(3), 2019, 1329–1350.

L. Chaib, A. Choucha and S. Arif, Optimal design and tuning of novel fractional order PID power system stabilizer using a new metaheuristic bat algorithm, Ain Shams Engineering Journal, 8, 2017, 113–125.

D. Chitara, K. R. Niazi, A. Swarnkar and N. Gupta, Cuckoo search optimization algorithm for designing of a multimachine power system stabilizer, IEEE Transactions on Industry Applications, 54(4), 2018, 3056–3065.

S. Ekinci and A. Demiroren, Modeling, simulation, and optimal design of power system stabilizers using ABC algorithm, Turkish Journal of Electrical Engineering & Compututer Sciences, 24, 2016, 1532–1546.

H. Beiranvand and E. Rokrok, General relativity search algorithm: A global optimization approach, International Journal of Computational Intelligence and Applications, 14(3), 2015, 1550017 (29 pages).

H. Shayanfar and F. S. Gharehchopogh, Farmland fertility: A new metaheuristic algorithm for solving continuous optimization problems, Applied Soft Computing, 71, 2018, 728–746.

A. A. Z. Diab, S. I. El-ajmi, H. M. Sultan and Y. B. Hassan, Modified farmland fertility optimization algorithm for optimal design of a grid-connected hybrid renewable energy system with fuel cell storage: case study of Ataka, Egypt, International Journal of Advanced Computer Science and Applications, 10(8), 2019, 119–132.

D. Mondal, A. Chakrabarti and A. Sengupta, Power System Small Signal Stability Analysis and Control. New York, USA: Academic Press, 2014.

H. Beiranvand and E. Rokrok, MatSim: A Matpower and simulink based tool for power system dynamics course education, 31th Power System Conference, Tehran, Iran, 2016, 1–6.

P. W. Sauer, M. A. Pai and J. H. Chow, Power System Dynamics and Stability With Synchrophasor Measurement and Power System Toolbox, USA: Wiley-IEEE Press, 2018.

Refbacks

  • There are currently no refbacks.