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Performance assessment of the two metaheuristic techniques and their Hybrid for power system stability enhancement with PV-STATCOM

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Abstract

The paper demonstrates a comprehensive performance assessment of the two metaheuristic swarm-based optimization algorithms namely PSO (Particle swarm optimization), BFOA (Bacterial foraging optimization algorithm), and the hybrid PSO-BFOA optimizer for the alleviation and control of the power oscillations in a two-area four generator system integrated with a large-scale PV-farm. After sunset, the PV-plant operates as VSC (Voltage Source Converter)-STATCOM (Static synchronous compensator) using its overall inverting capabilities for the power system stability improvement. While in the daytime during the faults, the PV-farm immediately stops the active power production and behaves as PV-STATCOM until the normal operating conditions are resumed. The modified version of Kundur’s two-area system comprising of a large-scale PV-farm is simulated with MATLAB software. An innovative control strategy employing the two PI controllers distinctly controls the DC-AC currents of the PV-STATCOM. The series compensation is set to an optimal value of 85% and subjected to a 3-φ fault. Zero mechanical dampings, along with extra disturbances of 20% variation in reference voltage and electromagnetic torque are introduced to flaunt the worst damping scenarios. The simulation outcomes and time-domain analysis for various test conditions: without a controller, with PSO-based PV-STATCOM, with BFOA-based PV-STATCOM, and with the Hybrid PSO-BFOA-based PV-STATCOM, reveal that all the system modes are stabilized with PSO application. The stability of modes is progressively improved with BFO control, eventually, the modes are optimally stabilized by deploying the hybrid PSO-BFO algorithm.

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References

  1. Kumar R, Khetrapal P, Badoni M, Diwania S (2021) Evaluating the relative operational performance of wind power plants in Indian electricity generation sector using two-stage model. Energy Environ. https://doi.org/10.1177/0958305X211043531

    Article  Google Scholar 

  2. The World's Largest Solar Plant is Now Online in India (2016). https://www.popularmechanics.com/science/green-tech/a24063/worlds-largest-solar-plant-india/

  3. Zhang Y, Huang SF, Schmall J, Conto J, Billo J, Rehman E (2014) Evaluating system strength for large-scale wind plant integration. In: Proceedings of IEEE PES General Meeting 27–31, July, pp 1–5. https://doi.org/10.1109/PESGM.2014.6939043

  4. Shah R, Mithulananthan N, Bansal R, Ramachandaramurthy V (2015) A review of key power system stability challenges for large-scale PV integration. Renew Sustain Energy Rev 41:1423–1436. https://doi.org/10.1016/j.rser.2014.09.027

    Article  Google Scholar 

  5. Eftekharnejad S, Vittal V, Heydt GT, Keel B, Loehr J (2013) Small signal stability assessment of power systems with increased penetration of photovoltaic generation: a case study. IEEE Trans Sustain Energy 4:960–967. https://doi.org/10.1109/TSTE.2013.2259602

    Article  Google Scholar 

  6. Tamimi B, Cañizares C, Bhattacharya K (2013) System stability impact of large-scale and distributed solar photovoltaic generation: the case of Ontario, Canada. IEEE Trans Sust Energy 4:680–688. https://doi.org/10.1109/TSTE.2012.2235151

    Article  Google Scholar 

  7. Kumar R, Singh R, Ashfaq H (2020) Stability enhancement of multi-machine power systems using Ant colony optimization-based static synchronous compensator. Comput Electr Eng 83:1–17. https://doi.org/10.1016/j.compeleceng.2020.106589

    Article  Google Scholar 

  8. Kundur P, Balu NJ, Lauby MG (1994) Power system stability and control. McGraw-hill, New York

    Google Scholar 

  9. Hingorani NG, Gyugyi L (2000) Understanding FACTS: concepts and technology of flexible AC transmission systems. Wiley, New York

    Google Scholar 

  10. Mathur RM, Varma RK (2002) Thyristor-based FACTS controllers for electrical transmission systems. Wiley, New York

    Book  Google Scholar 

  11. Xiao Y, Song Y, Liu CC, Sun Y (2003) Available transfer capability enhancement using FACTS devices. IEEE Trans Power Syst 18:305–312. https://doi.org/10.1109/TPWRS.2002.807073

    Article  Google Scholar 

  12. Firouzi M, Gharehpetian GB, Salami Y (2017) Active and reactive power control of wind farm for enhancement transient stability of multi-machine power system using UIPC. IET Renew Power Gener 11:1246–1252. https://doi.org/10.1049/iet-rpg.2016.0459

    Article  Google Scholar 

  13. Bian XY, Geng Y, Fu KLLoY, Zhou QB, (2016) Coordination of PSSs and SVC damping controller to improve probabilistic small-signal stability of power system with wind farm integration. IEEE Trans Power Syst 31:2371–2382. https://doi.org/10.1109/TPWRS.2015.2458980

    Article  Google Scholar 

  14. Bakhshi M, Holakooie MH, Rabiee A (2017) Fuzzy based damping controller for TCSC using local measurements to enhance transient stability of power systems. Int J Electr Power Energy Syst 85:12–21. https://doi.org/10.1016/j.ijepes.2016.06.014

    Article  Google Scholar 

  15. Varma RK, Salehi R (2017) SSR mitigation with a new control of PV solar f arm as STATCOM (PV-STATCOM). IEEE Trans Sustain Energy 8:1473–1483. https://doi.org/10.1109/TSTE.2017.2691279

    Article  Google Scholar 

  16. Khayyatzadeh M, Kazemzadeh R (2017) Sub-synchronous resonance damping using high-penetration PV plant. Mech Syst Signal Process 84:431–444. https://doi.org/10.1016/j.ymssp.2016.07.023

    Article  Google Scholar 

  17. Varma RK, Maleki H (2019) PV solar system control as STATCOM (PV-STATCOM) for power oscillation damping. IEEE Trans Sustain Energy 10:1793–1803. https://doi.org/10.1109/TSTE.2018.2871074

    Article  Google Scholar 

  18. Varma RK, Rahman SA, Vanderheide T (2015) New control of PV solar farm as STATCOM (PV-STATCOM) for increasing grid power transmission limits during night and day. IEEE Trans Power Deliv 30:755–763. https://doi.org/10.1109/TPWRD.2014.2375216

    Article  Google Scholar 

  19. Singh A, Sharma V (2019) Salp swarm algorithm-based model predictive controller for frequency regulation of solar integrated power system. Neural Comput Appl 31:8859–8870. https://doi.org/10.1007/s00521-019-04422-3

    Article  Google Scholar 

  20. Varma RK, Siavashi EM (2019) Enhancement of solar farm connectivity with smart PV inverter PV-STATCOM. IEEE Trans Sustain Energy 10:1161–1171. https://doi.org/10.1109/TSTE.2018.2862405

    Article  Google Scholar 

  21. Shah R, Mithulananthan N, Lee KY (2013) Large-scale PV plant with a robust controller considering power oscillation damping. IEEE Trans Energy Convers 28:106–116. https://doi.org/10.1109/TEC.2012.2230328

    Article  Google Scholar 

  22. Wandhare RG, Agarwal V (2014) Novel stability enhancing control strategy for centralized PV-grid systems for smart grid applications. IEEE Trans Smart Grid 5:1389–1396. https://doi.org/10.1109/TSG.2013.2279605

    Article  Google Scholar 

  23. Varma RK, Khadkikar V, Seethapathy R (2009) Nighttime application of PV solar farm as STATCOM to regulate grid voltage. IEEE Trans Energy Convers 24:983–985. https://doi.org/10.1109/TEC.2009.2031814

    Article  Google Scholar 

  24. Varma RK (2014) Multivariable modulator controller for power generation facility. PCT Application (PCT/CA2014/051174) filed on December 6.

  25. Gevorgian V, Booth S (2013) Review of PREPA technical requirements for interconnecting wind and solar generation. National Renewable Energy Lab. (NREL), Golden, CO (United States).

  26. Farsangi MM, Nezamabadi-pour H, Song YH, Lee KY (2007) Placement of SVCs and selection of stabilizing signals in power systems. IEEE Trans Power Syst 22:1061–1071. https://doi.org/10.1109/TPWRS.2007.901285

    Article  Google Scholar 

  27. Kumar R, Singh R, Ashfaq H, Singh S, Badoni M (2020) Power system stability enhancement by damping and control of Sub-synchronous torsional oscillations using Whale optimization algorithm based Type-2 wind turbines. ISA Trans 108:240–256. https://doi.org/10.1016/j.isatra.2020.08.037

    Article  Google Scholar 

  28. Abdulrahman I, Belkacemi R, Radman G (2019) Power oscillations damping using wide-area-based solar plant considering adaptive time-delay compensation. Energy Syst 12:459–489. https://doi.org/10.1007/s12667-019-00350-2

    Article  Google Scholar 

  29. Howlader AM, Sadoyama S, Roose LR, Chen Y (2019) Active power control to mitigate voltage and frequency deviations for the smart grid using smart PV inverters. Appl Energy. https://doi.org/10.1016/j.apenergy.2019.114000

    Article  Google Scholar 

  30. Miao D, Hossain S (2020) Improved gray wolf optimization algorithm for solving placement and sizing of electrical energy storage system in micro-grids. ISA Trans. https://doi.org/10.1016/j.isatra.2020.02.016

    Article  Google Scholar 

  31. Kumar R, Singh R, Ashfaq H (2020) Stability enhancement of induction generator–based series compensated wind power plants by alleviating subsynchronous torsional oscillations using BFOA-optimal controller tuned STATCOM. Wind Energy 23:1846–1867

    Article  Google Scholar 

  32. Li M, Xiong L, Chai H, Xiu L, Hao J (2020) Mechanism of PV generation system damping electromechanical oscillations. IEEE Access 8:135853–135865. https://doi.org/10.1109/ACCESS.2020.3011456

    Article  Google Scholar 

  33. Varma RK, Akbari M (2020) Simultaneous fast frequency control and power oscillation damping by utilizing PV Solar system as PV-STATCOM. IEEE Trans Sustain Energy 11(1):415–425. https://doi.org/10.1109/TSTE.2019.2892943

    Article  Google Scholar 

  34. Silva-Saravia H, Pulgar-Painemal H, Tolbert LM, Schoenwald DA, Ju W (2021) Enabling utility-scale solar PV plants for electromechanical oscillation damping. IEEE Trans Sustain Energy 12(1):138–147. https://doi.org/10.1109/TSTE.2020.2985999

    Article  Google Scholar 

  35. Abou El-Ela AA, El-Sehiemy RA, Shaheen AM et al (2021) Enhanced coyote optimizer-based cascaded load frequency controllers in multi-area power systems with renewable. Neural Comput Appl 33:8459–8477. https://doi.org/10.1007/s00521-020-05599-8

    Article  Google Scholar 

  36. Tolba MA, Rezk H, Al-Dhaifallah M et al (2020) Heuristic optimization techniques for connecting renewable distributed generators on distribution grids. Neural Comput Appl 32:14195–14225. https://doi.org/10.1007/s00521-020-04812-y

    Article  Google Scholar 

  37. Othman AM, El-Fergany AA (2021) Adaptive virtual-inertia control and chicken swarm optimizer for frequency stability in power-grids penetrated by renewable energy sources. Neural Comput Appl 33:2905–2918. https://doi.org/10.1007/s00521-020-05054-8

    Article  Google Scholar 

  38. Kumar R, Diwania S, Singh R, Ashfaq H, Khetrapal P, Singh S (2021) An intelligent Hybrid Wind–PV farm as a static compensator for overall stability and control of multimachine power system. ISA Trans. https://doi.org/10.1016/j.isatra.2021.05.014

    Article  Google Scholar 

  39. Badoni M, Singh A, Singh AK, Saxena H, Kumar R (2021) Grid-tied solar PV system with power quality enhancement using adaptive generalized maximum Versoria criterion. CSEE J Power Energy Syst. https://doi.org/10.17775/CSEEJPES.2020.04820

    Article  Google Scholar 

  40. Singh SK, Singh R, Ashfaq H, Kumar R (2021) Virtual inertia emulation of inverter interfaced distributed generation (IIDG) for dynamic frequency stability & Damping enhancement through BFOA tuned optimal controller. Arab J Sci Eng. https://doi.org/10.1007/s13369-021-06121-5

    Article  Google Scholar 

  41. IEEE Committee Report (1977) First benchmark model for computer simulation of subsynchronous resonance. IEEE Trans Power Apparatus Syst. PAS-96:1565–1572. https://doi.org/10.1109/T-PAS.1977.32485

  42. Dib F, Akchioui NE, Boumhidi I (2019) Design of sliding mode control with optimized fuzzy pss by differential evolution algorithm for power system smib. In: 5th International conference on optimization and applications (ICOA). 1–6. https://doi.org/10.1109/ICOA.2019.8727664

  43. Rahman SA, Varma RK, Vanderheide T (2014) Generalised model of a photovoltaic panel. IET Renew Power Gener 8:217–229. https://doi.org/10.1049/iet-rpg.2013.0094

    Article  Google Scholar 

  44. Reznik A, Simoes MG, Al-Durra A, Muyeen S (2014) LCL filter design and performance analysis for grid-interconnected systems. IEEE Trans Ind Appl 50:1225–1232. https://doi.org/10.1109/TIA.2013.2274612

    Article  Google Scholar 

  45. Shah R, Mithulananthan N, Bansal RC (2012) Damping performance analysis of battery energy storage, ultracapacitor, and shunt capacitor with large-scale PV plants. Appl Energy Spec Issue Smart Grid 96:235–244. https://doi.org/10.1016/j.apenergy.2011.09.035

    Article  Google Scholar 

  46. Abdelkarim N, Mohamed AmrE, Ahmed M. El-G, Hassen TD (2016) A new hybrid BFOA-PSO optimization technique for decoupling and robust control of two-coupled distillation column process. Comput Intell Neurosci, vol. 2016, Article ID 8985425, 17 pages. https://doi.org/10.1155/2016/8985425

  47. Das S, Biswas A, Dasgupta S, Abraham A (2009) Bacterial foraging optimization algorithm: theoretical foundations, analysis, and applications. In: Abraham A, Hassanien AE, Siarry P, Engelbrecht A (eds) Foundations of computational intelligence. Studies in computational intelligence, vol. 203 Springer, Berlin. https://doi.org/10.1007/978-3-642-01085-9_2

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Correspondence to Rajeev Kumar.

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Appendix

Appendix

See Tables 6, 7.

Table 6 System nomenclature
Table 7 The Hybrid PSO-BFOA parameters

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Kumar, R., Diwania, S., Khetrapal, P. et al. Performance assessment of the two metaheuristic techniques and their Hybrid for power system stability enhancement with PV-STATCOM. Neural Comput & Applic 34, 3723–3744 (2022). https://doi.org/10.1007/s00521-021-06637-9

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