Skip to main content
SpringerLink
Log in

Egret Swarm Optimized Distributed Power Flow Controller for Power Quality Enhancement in Grid Connected Hybrid System

  • Original Article
  • Published:
Journal of Electrical Engineering & Technology Aims and scope Submit manuscript

Abstract

Renewable energy sources (RES) are crucial to the generation of electrical power, especially for grid-connected systems. When RES is integrated with a grid, power quality issues such as voltage sag, swell, and harmonics, affect the consumers. To overcome these issues, this paper presents the intelligent control algorithm-based Finite Control Set Model Predictive Control (FCS-MPC) strategy for an electrical grid-connected photovoltaic-wind hybrid energy system with DPFC (Distributed Power Flow Controller). For controlling FCS-MPC, Egret Swarm Optimization Algorithm (ESOA) algorithm is utilized to select the values required for the control operation. This work aims at mitigating PQ issues and compensating for power demand in HRES. This research proposes an ESOA-based FCS-MPC technique (ESOA FCS-MPC) with DPFC with real and reactive power to address PQ concerns in HRES systems. The proposed work is tested with the MATLAB/Simulink tool, and compared with the existing conventional PID controller, FOPID controller, and BWO-Based FOPID Controller based DPFC system. Based on simulation results, DPFC can improve the quality of the power and reduces the THD current and voltage value by 0.86 and 0.49%, respectively.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

References

  1. Abas N, Dilshad S, Khalid A, Saleem MS, Khan N (2020) Power quality improvement using dynamic voltage restorer. IEEE Access. 8:164325–164339

    Google Scholar 

  2. Afzal MM, Muhammad AK, Muhammad ASH, Abdul W, Waqar U, Hussain S, Sang BR (2020) A comparative study of supercapacitor-based STATCOM in a grid-connected photovoltaic system for regulating power quality issues. Sustainability 12(17):6781

    Google Scholar 

  3. Alam, Md Shafiul, Fahad Saleh Al-Ismail, Mohammad Ali Abido, and Aboubakr Salem. "High-Level Penetration of Renewable Energy with Grid: Challenges and Opportunities." arXiv preprint arXiv:2006.04638 (2020).

  4. Alkahtani AA, Alfalahi STY, Athamneh AA, Al-Shetwi AQ, Mansor MB, Hannan MA, Agelidis VG (2020) Power quality in microgrids including supraharmonics: issues, standards, and mitigations. IEEE Access 8:127104–127122

    Google Scholar 

  5. Almohaimeed SA, Abdel-Akher M (2020) Power quality issues and mitigation for electric grids with wind power penetration. Appl Sci 10(24):8852

    Google Scholar 

  6. Al-Shetwi Ali Hannan, Jern Ker Pin, Alkahtani Ammar (2020) Power quality assessment of grid-connected PV system in compliance with the recent integration requirements. Electronics 9(2):366

    Google Scholar 

  7. Andang A, Rukmi SH, Manuaba K. "The Investigation of a Single-phase Shunt Hybrid Active Power Filter with FCS MPC and Hysteresis Control." In 2019 International Conference on Sustainable Engineering and Creative Computing (ICSECC), pp. 416–421. IEEE. (2019)

  8. Bajaj M, Singh AK (2020) Grid integrated renewable DG systems: a review of power quality challenges and state-of-the-art mitigation techniques. Int J Energy Res 44(1):26–69

    Google Scholar 

  9. Brinkel G, AlSkaif IL, van Voorden F (2020) Impact of rapid PV fluctuations on power quality in the low-voltage grid and mitigation strategies using electric vehicles. Int J Electric Power Energy Syst 118:105741

    Google Scholar 

  10. Tareen WU, Mekhilef S, Seyedmahmoudian M, Horan B (2017) Active power filter (APF) for mitigation of power quality issues in grid integration of wind and photovoltaic energy conversion system. Renew Sustain Energy Rev 70:635–655

    Google Scholar 

  11. Tareen WUK, Saad M (2017) Three-phase transformerless shunt active power filter with reduced switch count for harmonic compensation in grid-connected applications. IEEE Trans Power Electron 33(6):4868–4881

    Google Scholar 

  12. Hu R, Wei W, Zhe C, Xuezhi W, Long J, Wei M, Guohong Z (2020) Coordinated voltage regulation methods in active distribution networks with soft open points. Sustainability 12(22):9453

    Google Scholar 

  13. Li C, Vahid RD, Hamed VH, Jan K (2020) Coordination of OLTC and smart inverters for optimal voltage regulation of unbalanced distribution networks. Electric Power Syst Res 187:106498

    Google Scholar 

  14. Liang X, Andalib-Bin-Karim C (2018) Harmonics and mitigation techniques through advanced control in grid-connected renewable energy sources: A review. IEEE Trans Ind Appl 54(4):3100–3111

    Google Scholar 

  15. Nagaraju G, Shankar S (2020) Power quality improvement of wind energy conversion system with unified power quality controller: a hybrid control model. Trans Inst Meas Control 42(11):1997–2010

    Google Scholar 

  16. Rahman S, Haneen A, Masood M , Arif IS (2018) "Reverse power flow protection in grid connected PV systems." In SoutheastCon 2018, IEEE, pp. 1–5

  17. Rohouma W, Robert SB, Aaqib AP, Miroslav MB (2020) D-STATCOM for harmonic mitigation in low voltage distribution network with high penetration of nonlinear loads. Renewable Energy 145:1449–1464

    Google Scholar 

  18. Chauhan RK, Mashhood H, Jai PP (2018) Intelligent control model to enhance the performance of unified power quality conditioner. J Intell Fuzzy Syst 35(5):5007–5020

    Google Scholar 

  19. Goud S, Ch R, Mohit B, Ehab E, Salah K (2021) Power quality improvement using distributed power flow controller with BWO-based FOPID controller. Sustainability 13(20):11194

    Google Scholar 

  20. Reddy C, Srikanth G, Flah A, Gundala SR, Edson B (2021) Power quality improvement in HRES grid connected system with FOPID based atom search optimization technique. Energies 14(18):5812

    Google Scholar 

  21. Jin JX, Jian W, Ruo HY, Tian LZ, Shuai M, Ying JF, Yun QX (2021) A superconducting magnetic energy storage with dual functions of active filtering and power fluctuation suppression for photovoltaic microgrid. J Energy Storage 38:102508

    Google Scholar 

  22. Jin JX, Ruo HY, Run TZ, Ying JF, Qi X, Xiao YC (2021) Combined low voltage ride through and power smoothing control for DFIG/PMSG hybrid wind energy conversion system employing a SMES-based AC-DC unified power quality conditioner. Int J Electric Power Energy Syst 128:106733

    Google Scholar 

  23. Naidu PK, Meikandasivam S (2020) Power quality enhancement in a grid-connected hybrid system with coordinated PQ theory & fractional order PID controller in DPFC. Sustain Energy Grids Netw 21:100317

    Google Scholar 

  24. Malik M (2020) “A scheme for reduction in harmonics and establish the stability of hybrid system connected in grid.” Ain Shams Eng J 11(4):1123–1130

    Google Scholar 

  25. Tareen WUK, Muhammad A, Saad M, Mutsuo N, Mehdi S, Ben H, Mudasir AM, Nauman AB (2018) Mitigation of power quality issues due to high penetration of renewable energy sources in electric grid systems using three-phase APF/STATCOM technologies: a review. Energies 11(6):1491

    Google Scholar 

  26. de Yuan H, Ferreira JB, Cvoric D (2010) A FACTS device: distributed power-flow controller (DPFC). IEEE Trans Power Electron 25(10):2564–2572

    Google Scholar 

  27. Chen F, Liao X, Ha Li, Cao D (2022) Egret swarm optimization algorithm: an evolutionary computation approach for model free optimization. Biomimetics 7(4):144

    Google Scholar 

  28. Din AF, Ud IM, Gul F, Akhtar S (2023) Development of reinforced learning based non-linear controller for unmanned aerial vehicle. J Ambient Intell Humaniz Comput 14(4):4005–4022

    Google Scholar 

  29. Rostami M, Farajollahi A, Parvin H (2022) Deep learning-based face detection and recognition on drones. J Ambient Intell Hum Comput. https://doi.org/10.1007/s12652-022-03897-8

    Article  Google Scholar 

  30. Zhang K, Ting Qu, Zhou D, Thürer M, Liu Y, Nie D, Li C, Huang GQ (2019) IoT-enabled dynamic lean control mechanism for typical production systems. J Ambient Intell Humaniz Comput 10:1009–1023

    Google Scholar 

  31. Wechsler H (2023) Immunity and security using holism, ambient intelligence, triangulation, and stigmergy: Sensitivity analysis confronts fake news and COVID-19 using open set transduction. J Ambient Intell Humaniz Comput 14(4):3057–3074

    Google Scholar 

  32. Liu W (2021) Slam algorithm for multi-robot communication in unknown environment based on particle filter. J Ambient Intell Hum Comput. https://doi.org/10.1007/s12652-021-03020-3

    Article  Google Scholar 

  33. D’Aniello G, Gaeta A, Gaeta M, Tomasiello S (2018) Self-regulated learning with approximate reasoning and situation awareness. J Ambient Intell Humaniz Comput 9:151–164

    Google Scholar 

  34. Taimoor M, Lu X, Maqsood H, Sheng C (2023) A novel fault diagnosis in sensors of quadrotor unmanned aerial vehicle. J Ambient Intell Hum Comput 14(10):14081–14099

    Google Scholar 

  35. Annepu V, Rajesh A (2020) Implementation of an efficient artificial bee colony algorithm for node localization in unmanned aerial vehicle assisted wireless sensor networks. Wireless Person Commun 114:2663–2680

    Google Scholar 

  36. Edla DR, Tripathi D, Kuppili V, Dharavath R (2020) Multilevel automated security system for prevention of accidents at unmanned railway level crossings. Wireless Personal Commun 111:1707–1721

    Google Scholar 

  37. Alimi IA, Teixeira AL, Monteiro PP (2019) Effects of correlated multivariate FSO channel on outage performance of space-air-ground integrated network (SAGIN). Wireless Pers Commun 106(1):7–25

    Google Scholar 

  38. Miura R, Suzuki M (2003) Preliminary flight test program on telecom and broadcasting using high altitude platform stations. Wireless Pers Commun 24:341–361

    Google Scholar 

  39. Alam T (2022) Blockchain-enabled deep reinforcement learning approach for performance optimization on the internet of things. Wireless Pers Commun 126(2):995–1011

    Google Scholar 

  40. Shin M, Mughal DM, Park S, Kim S-H, Chung MY (2021) Cellular Licensed Band Sharing Technology Among Mobile Operators: A Reinforcement Learning Perspective. Wireless Personal Communications 120:27–47

    Google Scholar 

  41. Praise J, Jeya RJ, Raj S, Bibal Benifa JV (2020) Development of reinforcement learning and pattern matching (RLPM) based firewall for secured cloud infrastructure. Wireless Person Commun 115:993–1018

    Google Scholar 

  42. Bhangale KB, Kothandaraman M (2022) Survey of deep learning paradigms for speech processing. Wireless Person Commun 125(2):1913–1949

    Google Scholar 

  43. Yuvaraj N, Karthikeyan T, Praghash K (2021) An improved task allocation scheme in serverless computing using gray wolf Optimization (GWO) based reinforcement learning (RIL) approach. Wireless Pers Commun 117:2403–2421

    Google Scholar 

  44. Swarup A, Gopal M (1989) Control strategies for robot manipulators—a review. IETE J Res 35(4):198–207

    Google Scholar 

  45. Singh S, Khosla A, Kapoor R (2022) Visual-thermal fusion-based object tracking via a granular computing backed particle filtering. IETE J Res. https://doi.org/10.1080/03772063.2022.2030251

    Article  Google Scholar 

  46. Asha CS, Narasimhadhan AV (2020) Visual tracking using kernelized correlation filter with conditional switching to median flow tracker. IETE J Res 66(3):427–438

    Google Scholar 

  47. Kumar A (2021) Real-time performance comparison of vision-based autonomous landing of quadcopter on a ground moving target. IETE J Res. https://doi.org/10.1080/03772063.2021.1963332

    Article  Google Scholar 

  48. Rao DH, Kamat HV (1996) Neuro-fuzzy system for robotics applications. IETE J Res 42(4–5):325–333. https://doi.org/10.1080/03772063.1996.11415938

    Article  Google Scholar 

  49. El Hamidi K, Mjahed M, El Kari A, Ayad H, El Gmili N (2021) Design of hybrid neural controller for nonlinear MIMO system based on NARMA-L2 model. IETE J Res. https://doi.org/10.1080/03772063.2021.1909507

    Article  Google Scholar 

  50. Lu Y-S, Berkelman P (2023) Design and evaluation of state and disturbance observers for a multivariable magnetic levitation system. IETE J Res 69(1):420–437

    Google Scholar 

  51. Naderolasli A, Tabatabaei M (2017) Stabilization of the two-axis gimbal system based on an adaptive fractional-order sliding-mode controller. IETE J Res 63(1):124–133

    Google Scholar 

  52. Montazeri M, Yousefi MR, Shojaei K, Shahgholian G (2022) Design of fast variable structure adaptive fuzzy control for nonlinear state-delay systems with uncertainty. IETE J Res 68(6):4577–4589

    Google Scholar 

  53. Pathak RR, Mohanty S, Sengupta A (2022) An optimization-based adaptive sliding mode control for an inverted pendulum. IETE J Res. https://doi.org/10.1080/03772063.2022.2127941

    Article  Google Scholar 

  54. Narayan J, Dwivedy SK (2023) Towards neuro-fuzzy compensated PID control of lower extremity exoskeleton system for passive gait rehabilitation. IETE J Res 69(2):778–795

    Google Scholar 

  55. Guendouzi A, Hamerlain M, Saadia N (2022) A robust adaptive nonlinear control design via geometric approach for a quadrotor. IETE J Res 68(6):4544–4554

    Google Scholar 

  56. Safiullah S, Rahman A, Lone SA (2022) A second-order ADRC for synchronized frequency-voltage mitigation of EV integrated power system. IETE J Res. https://doi.org/10.1080/03772063.2022.2120105

    Article  Google Scholar 

  57. Nasseri S, Khalesi MR, Ramezani A, Abdollahi M, Mohseni M (2022) An adaptive decoupling control design for flotation column: a comparative study against model predictive control. IETE J Res 68(6):3994–4007

    Google Scholar 

  58. Tony Thomas A, Parameshwaran R, Sathiyavathi S, Vimala Starbino A (2022) Improved position tracking performance of electro hydraulic actuator using PID and sliding mode controller. IETE J Res 68(3):1683–1695

    Google Scholar 

  59. Bharti OP, Aanchal SS, Vardhan ASS, Vardhan R, Saket K, Kothari DP (2023) Static output feedback-based dfig controller design for the wind-driven scheme. IETE J Res. https://doi.org/10.1080/03772063.2023.2172465

    Article  Google Scholar 

  60. Li T, Song Y, Xia X (2020) Research on remote control algorithm for parallel implicit domain robot patrol inspection on 3D unstructured grid. J Ambient Intell Humaniz Comput 11:6337–6347

    Google Scholar 

  61. Tang S, Liu G, Lin Z, Li X (2022) Multi-station test scheduling optimization method for industrial robot servo system. J Ambient Intell Hum Comput. https://doi.org/10.1007/s12652-020-02577-9

    Article  Google Scholar 

  62. Analysis of Optimization Methods Applied for Renewable Energy Integration. In: 2023 IEEE 3rd International Conference in Power Engineering Applications (ICPEA), 1570861924, 6–7 March 2023.

  63. "New network design for simultaneous use of electric vehicles, photovoltaic generators, wind farms and energy storage," In: 2022 9th Iranian Conference on Renewable Energy & Distributed Generation (ICREDG), 2022, pp. 1–5, doi: https://doi.org/10.1109/ICREDG54199.2022.9804534.

  64. Eidiani M, Ashkhane Y, Khederzadeh M (2009) Reactive power compensation in order to improve static voltage stability in a network with wind generation. In: 2009 Second International Conference on Computer and Electrical Engineering (Vol. 1, pp. 47-50). IEEE.

Download references

Acknowledgements

The author would like to express his heartfelt gratitude to the supervisor for his guidance and unwavering support during this research for his guidance and support.

Funding

No funding was received to assist with the preparation of this manuscript.

Author information

Authors and Affiliations

  1. Depatment of Electrical and Electronics Engineering, Cape Institute of Technology, Levengipuram, Tirunelveli, Tamil Nadu, India

    Ansho P. M.

  2. Department of Electrical and Electronics Engineering, St.Xavier’s Catholic College of Engineering, Nagercoil, Tamil Nadu, India

    Germin Nisha M.

Authors
  1. Ansho P. M.
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Germin Nisha M.
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ansho P. M..

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

P. M., A., M., G.N. Egret Swarm Optimized Distributed Power Flow Controller for Power Quality Enhancement in Grid Connected Hybrid System. J. Electr. Eng. Technol. 19, 2047–2057 (2024). https://doi.org/10.1007/s42835-023-01679-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42835-023-01679-6

Keywords

Search

Navigation