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An innovative hybrid controller-based combined grid-connected hybrid renewable energy system

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Abstract

In the upcoming decades, renewable energy is poised to fulfill 50% of the world's energy requirements. Wind and solar hybrid generation systems, complemented by battery energy storage systems (BESS), are expected to play a pivotal role in meeting future energy demands. However, the variability in inputs from photovoltaic and wind systems, contingent on environmental conditions, introduces fluctuations in their power outputs. Effectively managing constant power at the DC-link and enhancing power quality (PQ) at the AC-bus present formidable challenges. In this article, the hybrid power generation (HPG) system has been analyzed in different stages of the proposed controller. The initial stage focuses on mitigating power fluctuations at the DC-link by employing a hybrid phase-locked loop (PLL)-based voltage source converter (VSC) controller. Subsequently, the second stage delves into the analysis of power quality aspects, addressing issues such as sag, swell, harmonics, and voltage interruptions. To tackle these challenges, a distribution static compensator (D-STATCOM) is introduced, leveraging a hybrid technique that integrates the cuckoo search (CS) algorithm and recurrent neural network (RNN). This innovative approach, a unique contribution of this research, was implemented and simulated using MATLAB/Simulink. The obtained results demonstrate comparability with existing applications of the controller, thereby validating the efficacy of the proposed model.

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References

  1. Alizadeh Bidgoli M, Payravi AR, Ahmadian A et al (2021) Optimal day-ahead scheduling of autonomous operation for the hybrid micro-grid including PV WT diesel generator and pump as turbine system. J Ambient Intell Human Comput 12:961–977. https://doi.org/10.1007/s12652-020-02114-8

    Article  Google Scholar 

  2. Bihari SP, Sadhu PK (2023) SLDB controller based 31 level MLI for grid-connected hybrid renewable energy sources. J Ambient Intell Human Comput 14:1047–1059. https://doi.org/10.1007/s12652-021-03357-9

    Article  Google Scholar 

  3. De Paola A, Ferraro P, Lo Re G et al (2020) A fog-based hybrid intelligent system for energy saving in smart buildings. J Ambient Intell Human Comput 11:2793–2807. https://doi.org/10.1007/s12652-019-01375-2

    Article  Google Scholar 

  4. Diwania S, Kumar M, Kumar R, Kumar A, Gupta V, Khetrapal P (2022) Machine learning-based thermo-electrical performance improvement of nanofluid-cooled photovoltaic–thermal system. Energy Environ. https://doi.org/10.1177/0958305X221146947

    Article  Google Scholar 

  5. Diwania S, Kumar R, Kumar M, Gupta V, Alsenani TR (2022) Performance enrichment of hybrid photovoltaic thermal collector with different nano-fluids. Energy Environ. https://doi.org/10.1177/0958305X221093459

    Article  Google Scholar 

  6. Ballal MS, Ballal DM, Suryawanshi HM et al (2014) Corrective measures for the effective load management and control under disturbance at bhusawal thermal power station: case study. J Inst Eng India Ser B 95:163–173. https://doi.org/10.1007/s40031-014-0082-3

    Article  Google Scholar 

  7. Chittora P, Singh A, Singh M et al (2023) Experimental investigation of modern control algorithms for power quality improvement for single-phase grid-connected photo-voltaic system. J Inst Eng India Ser B 104:715–729. https://doi.org/10.1007/s40031-023-00887-y

    Article  Google Scholar 

  8. Deshmukh AN, Chandrakar VK (2022) Design and performance analysis of grid-connected solar photovoltaic system with performance forecasting approach (PFA). J Inst Eng India Ser B 103:1521–1532. https://doi.org/10.1007/s40031-022-00779-7

    Article  Google Scholar 

  9. Pandey SK, Singh B (2021) PV–BES microgrid system with LQR-tuned CC–CVF-based control algorithm. J Inst Eng India Ser B 102:585–593. https://doi.org/10.1007/s40031-020-00534-w

    Article  Google Scholar 

  10. Kulkarni NG, Virulkar VB (2023) Enhancing the power quality of grid connected photovoltaic system during fault ride through: a comprehensive overview. J Inst Eng India Ser B 104:821–836. https://doi.org/10.1007/s40031-023-00870-7

    Article  Google Scholar 

  11. Saroha J, Pandove G, Singh M (2018) Modelling and simulation of grid connected SPV system with active power filtering features. J Inst Eng India Ser B 99:25–35. https://doi.org/10.1007/s40031-017-0293-5

    Article  Google Scholar 

  12. Marrekchi A, Keskes S, Sallem S, Kammoun MBA (2022) Comparative analysis of three non-linear control strategies for grid-connected PV system. IETE J Res 68(5):3739–3749. https://doi.org/10.1080/03772063.2020.1779617

    Article  Google Scholar 

  13. Rajendran N, Sundharajan V (2022) Sun flower optimization with self-tuned fuzzy logic MPPT controller and reactive power compensation for grid-connected PV system. IETE J Res. https://doi.org/10.1080/03772063.2022.2096704

    Article  Google Scholar 

  14. Byunggyu Yu (2018) Anti-islanding performance analysis of multiple PV micro-inverter operations. IETE J Res 64(6):785–795. https://doi.org/10.1080/03772063.2017.1373608

    Article  Google Scholar 

  15. Saxena NK, Kumar A, Gupta V (2021) Enhancement of system performance using STATCOM as dynamic compensator with squirrel cage induction generator (SCIG) based microgrid. Int J Emerg Electr Power Syst 22(2):177–189. https://doi.org/10.1515/ijeeps-2020-0228

    Article  Google Scholar 

  16. Saxena NK, Gao WD, Kumar A, Mekhilef S, Gupta V (2022) Frequency regulation for microgrid using genetic algorithm and particle swarm optimization tuned STATCOM. Int J Circuit Theory Appl 50(9):3231–3250

    Article  Google Scholar 

  17. Garcia P, Garcia CA, Fernandez LM, Llorens F, Jurado F (2014) ANFIS-based control of a grid-connected hybrid system integrating renewable energies, hydrogen and batteries. IEEE Trans Ind Inform 10(2):1107–1117

    Article  Google Scholar 

  18. Bhattacharjee C, Roy BK (2016) Advanced fuzzy power extraction control of wind energy conversion system for power quality improvement in a grid tied hybrid generation system. IET Trans Gener Trans Distrib 10:1179–1189

    Article  Google Scholar 

  19. Bahmani-Firouzi B, Azizipanah-Abarghooee R (2014) Optimal sizing of battery energy storage for micro-grid operation management using a new improved bat algorithm. Int J Elect Power Energy Syst 1(56):42–54

    Article  Google Scholar 

  20. Sarker K, Chatterjee D, Goswami SK (2017) Grid integration of photovoltaic and wind based hybrid distributed generation system with low harmonic injection and power quality improvement using biogeography-based optimization. Int J Renewable Energy Focus 22–23:38–56

    Article  Google Scholar 

  21. Shaik AG, Mahela OP (2018) Power quality assessment and event detection in hybrid power system. Int J Elect Power Syst Res 161:26–44

    Article  Google Scholar 

  22. Mishra S, Ray PK (2016) Power quality improvement using photovoltaic fed DSTATCOM based on JAYA optimization. IEEE Trans Sustain Energy 7(4):1672–1680

    Article  Google Scholar 

  23. Pandey PK, Sandhu KS Multi diode modelling of PV Cell. Power electronics (IICPE). 2014 IEEE 6th India international conference. 2014, p 1–4

  24. Saxena NK, Gupta V, Rajput RS, Kumar A, Gupta AR (2022) Reactive power requirement for operating wind-driven micro grid in the presence of several proportions and classes of static load. In: Kumar, A., Srivastava, S.C., Singh, S.N. (eds) Renewable energy towards smart grid. Lecture notes in electrical engineering, vol 823. Springer, Singapore. https://doi.org/10.1007/978-981-16-7472-3_3

  25. Pan L, Wang X (2020) Variable pitch control on direct-driven PMSG for offshore wind turbine using Repetitive-TS fuzzy PID control. Renewable Energy 159:221–237

    Article  Google Scholar 

  26. Yehia DM, Mansour DA, Yuan W (2018) Fault ride-through enhancement of PMSG wind turbines with DC microgrids using resistive-type SFCL. IEEE Trans Appl Supercond 28(4):1–5

    Google Scholar 

  27. Hua J, Shana Y, Xub Y, Guerreroc JM (2019) A coordinated control of hybrid ac/dc microgrids with PV-wind-battery under variable generation and load conditions. Electr Power Energy Syst 104:583–592

    Article  Google Scholar 

  28. Ma T, Cintuglu MH, Mohammed OA (2017) Control of hybrid ac/dc microgrid involving energy storage and pulsed loads. IEEE Trans Ind Appl 53:567–575

    Article  Google Scholar 

  29. Jian S (2011) Impedance-based stability criterion for grid-connected inverters. IEEE Trans Power Electron 26(11):3075–3078

    Article  Google Scholar 

  30. Jia Q, Yan G, Cai Y, Li Y, Zhang J (2019) Small-signal stability analysis of photovoltaic generation connected to weak AC grid. J Modern Power Syst Clean Energy 7(2):254–267

    Article  Google Scholar 

  31. Chatterjee AS (2023) A bus clamping PWM-based improved control of grid tied PV inverter with LCL filter under varying grid frequency condition. IETE J Res 69(2):862–878

    Article  Google Scholar 

  32. Singh B, Maulik K, Hussain I (2018) Control of grid tied smart PV-DSTATCOM system using an adaptive technique. IEEE Trans Smart Grid 9(5):3986–3993

    Article  Google Scholar 

  33. Pandey P, Sandhu K (2021) Integrated grid-connected hybrid power generating system with optimized PLL-based power control. Walailak J Sci Technol WJST 18(16):22784

    Google Scholar 

  34. Kumar R, Kumar S, Sengupta A (2022) Optimization of bio-impedance techniques-based monitoring system for medical & industrial applications. IETE J Res 68(5):3843–3854

    Article  Google Scholar 

  35. Shi Z, Liang H, Dinavahi V (2018) Direct interval forecast of uncertain wind power based on recurrent neural networks. IEEE Trans Sustain Energy 9(3):1177–1187

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Electrical Engineering, Gyan Ganga Institute of Technology and Science, Jabalpur, MP, 482003, India

    Pawan Kumar Pandey

  2. Chitkara University Institute of Engineering and Technology, Chitkara University, Chandigarh, Punjab, 140401, India

    Ramesh Kumar

  3. Department of Electrical and Electronics Engineering, KIET Group of Institutions, Delhi-NCR, Ghaziabad, UP, 201206, India

    Varun Gupta & Sourav Diwania

  4. Department of Electronics and Communication Engineering, KIET Group of Institutions, Delhi-NCR, Ghaziabad, UP, 201206, India

    Abhas Kanungo

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  1. Pawan Kumar Pandey
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  4. Abhas Kanungo
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  5. Sourav Diwania
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Contributions

Declarations Funding Not applicable. Conflict of interest No conflict of interest among present authors. Availability of data and materials It is arranged and developed by present authors. Code Availability -It is accomplished by corresponding and main author combined. Authors Contributions -Varun Gupta is corresponding whereas Pawan Pandey performed all simulations and literature survey work in this manuscript. -Rest of the work is done by remaining authors. Ethical Approval All authors are aware about the ethical approval. Consent to Participate- All present authors are agree to participate. Consent to Publish- All present authors are giving their consent for publishing the paper.

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Correspondence to Varun Gupta.

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Pandey, P.K., Kumar, R., Gupta, V. et al. An innovative hybrid controller-based combined grid-connected hybrid renewable energy system. Electr Eng (2024). https://doi.org/10.1007/s00202-024-02363-2

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