10.1007/s40095-022-00547-9

Influence of solar and solid oxide fuel cell in AGC learning by utilizing spotted hyena optimized cascade controller

  • Arindita Saha*1,
  • Puja Dash2,
  • Naladi Ram Babu3,
  1. Department of Electrical Engineering, Regent Education & Research Foundation Group of Institutions, Kolkata, West Bengal, IN
  2. Department of Electrical and Electronics Engineering, Gayatri Vidya Parishad College of Engineering (Autonomous), Visakhapatnam, Andhra Pradesh, IN
  3. Department of Electrical and Electronics Engineering, Aditya Engineering College, East-Godavari, Andhra Pradesh, IN

Published in Issue 2022-11-03

How to Cite

Saha, A., Dash, P., & Babu, N. R. (2022). Influence of solar and solid oxide fuel cell in AGC learning by utilizing spotted hyena optimized cascade controller. International Journal of Energy and Environmental Engineering, 14(4 (December 2023). https://doi.org/10.1007/s40095-022-00547-9
Crossref
Scopus
Google Scholar
Europe PMC

Abstract

Abstract The present work explores automatic generation control learning for manifold area and sources under traditional situations. Sources in area-1 are thermal, biodiesel; thermal and gas plant in area-2; and thermal, split-shaft gas turbine (Ss(GT)) in area-3. An original strive has been set out to execute cascade controller with the amalgamation of proportional with tilt–integral–derivative with filter (TIDN) and fractional-order integral–derivative (FOID). TIDN and FOID are in series connection, hence named TIDN-FOID. Various scrutiny expresses excellency of TIDN-FOID controller over proportional–integral–derivative filter (PIDN) and TIDN from outlook regarding the lessened level of peak overshoot, extent of oscillations, peak undershoot as well as settling time. In an endeavour to procure the controller’s gains and parameters, bioinspired meta-heuristic spotted hyena optimizer (SHO) is applied. It is also observed that the presence of a renewable solar source makes the system significantly better compared to the base thermal–biodiesel–gas–Ss(GT) system. TIDN-FOID performance is also observed to be excellent in the presence of solar for both 1% step load disturbance and random load pattern individually. Fixed as well as variable insolation for solar is analysed separately. The performance of solid oxide fuel cell (SoFC) is also examined using the TIDN-FOID controller, which provides with noteworthy outcome in dynamic performance for both types of disturbances. Also, sensitivity analysis is performed, and it is observed that the values of the TIDN-FOID parameters at nominal conditions are appropriate for a higher value of disturbance.

Keywords

  • Automatic generation control,
  • Biodiesel plant,
  • Solar thermal power plant,
  • Solid oxide fuel cell,
  • Spotted hyena optimizer,
  • TIDN-FOID controller

References

  1. Elgerd (2007) Tata McGraw-Hill
  2. Kundur (1993) Mc Graw Hill
  3. Ibraheem Kumar and Kothari (2005) Recent philosophies of automatic generation control strategies in power systems 20(1) (pp. 346-357) https://doi.org/10.1109/TPWRS.2004.840438
  4. Elgerd and Fosha (1970) Optimum megawatt-frequency control of multiarea electric energy systems 89(4) (pp. 556-563) https://doi.org/10.1109/TPAS.1970.292602
  5. Das et al. (1999) Dynamics of diesel and wind turbine generators on an isolated power system (pp. 183-189) https://doi.org/10.1016/S0142-0615(98)00033-7
  6. Ch et al. (2012) GA based frequency controller for solar thermal–diesel–wind hybrid energy generation/energy storage system 43(1) (pp. 262-279) https://doi.org/10.1016/j.ijepes.2012.05.025
  7. Ismayil, C., Sreerama, K.R., Sindhu, T.K.: Automatic generation control of single area thermal power system with fractional order PID (PI
  8. λ
  9. D
  10. μ
  11. ) controllers. In Third Int. Conf. on Advances in Control and Optimization of Dynamical Systems, March 13–15, (2014). Kanpur, India: pp.552–557.
  12. Babu and Saikia (2020) AGC of a multiarea system incorporating accurate HVDC and precise wind turbine systems 30(4)
  13. Ramoji and Saikia (2021) Optimal coordinated frequency and voltage control of CCGT-thermal plants with TIDF CONTROLLER https://doi.org/10.1080/03772063.2021.1959420
  14. Sharma et al. (2020) Frequency excursion mitigation strategy using a novel COA optimised fuzzy controller in wind integrated power systems (pp. 4071-4085) https://doi.org/10.1049/iet-rpg.2020.0882
  15. Kumar et al. (2021) Real time simulation for load frequency control of multisource microgrid system using grey wolf optimization based modified bias coefficient diagram method (GWOMBCDM) controller 16(1) (pp. 205-221) https://doi.org/10.1007/s42835-020-00596-2
  16. Mandeep et al. (2021) Algorithm based LFC design of a six-area hybrid diverse power system integrating IPFC and RFB 67(3) (pp. 394-407) https://doi.org/10.1080/03772063.2018.1548908
  17. Nanda et al. (2006) Some new findings on automatic generation control of an interconnected hydrothermal system with conventional controllers 21(1) (pp. 187-194) https://doi.org/10.1109/TEC.2005.853757
  18. Saikia, L.C., Chowdhury, A., Shakya, N., et al.: AGC of a multi area thermal system using firefly optimized IDF controller. India Conf. (INDICON), IEEE, Mumbai, India (2013)
  19. Pradhan et al. (2016) Firefly algorithm optimized fuzzy PID controller for AGC of multi-area multi-source power systems with UPFC and SMES 19(1) (pp. 338-354)
  20. Saha and Saikia (2019) Renewable energy source-based multiarea AGC system with integration of EV utilizing cascade controller considering time delay 29(1) https://doi.org/10.1002/etep.2646
  21. Sharma and Saikia (2015) Automatic generation control of a multi-area ST—thermal power system using grey wolf optimizer algorithm based classical controllers (pp. 853-862) https://doi.org/10.1016/j.ijepes.2015.06.005
  22. Saha and Saikia (2017) Utilisation of ultra-capacitor in load frequency control under restructured STPP-thermal power systems using WOA optimised PIDN-FOPD controller 11(13) (pp. 3318-3331) https://doi.org/10.1049/iet-gtd.2017.0083
  23. Dutta and Prakash (2020) Load frequency control of multi-area hybrid power system integrated with renewable energy sources utilizing FACTS & energy storage system https://doi.org/10.1002/ep.13329
  24. Barik and Das (2018) Expeditious frequency control of solar photobiotic/biogas/biodiesel generator based isolated renewable microgrid using grasshopper optimisation algorithm 12(14) (pp. 1659-1667) https://doi.org/10.1049/iet-rpg.2018.5196
  25. Gupta and Kumar (2018) Particle swarm optimization based automatic generation control of interconnected power system incorporating battery energy (pp. 1562-1569) https://doi.org/10.1016/j.procs.2018.05.120
  26. Arya (2019) Effect of energy storage systems on automatic generation control of interconnected traditional and restructured energy systems (pp. 6475-6493) https://doi.org/10.1002/er.4493
  27. Tasnin and Saikia (2018) Performance comparison of several energy storage devices in deregulated AGC of a multi-area system incorporating geothermal power plant 12(7) (pp. 761-772) https://doi.org/10.1049/iet-rpg.2017.0582
  28. Deng et al. (2010) Generalized predictive control for fractional order dynamic model of solid oxide fuel cell output power (pp. 8097-8103) https://doi.org/10.1016/j.jpowsour.2010.07.053
  29. Pathak et al. (2019) Modeling of HVDC tie-links and their utilization in AGC/LFC operations of multi-area power systems https://doi.org/10.1109/TIE.2018.2835387
  30. Kumari et al. (2016) Design of PI controller for automatic generation control of multi area interconnected power system using bacterial foraging optimization 8(6) (pp. 2779-2786) https://doi.org/10.21817/ijet/2016/v8i6/160806236
  31. Jagatheesan et al. (2019) Design of a proportional-integral-derivative controller for an automatic generation control of multi-area power thermal systems using firefly algorithm https://doi.org/10.1109/JAS.2017.7510436
  32. Dash et al. (2015) Comparison of performances of several FACTS devices using Cuckoo search algorithm optimized 2DOF controllers in multi-area AGC (pp. 316-324) https://doi.org/10.1016/j.ijepes.2014.10.015
  33. Rahman et al. (2016) AGC of dish-stirling solar thermal integrated thermal system with biogeography based optimised three degree of freedom PID controller 10(8) (pp. 1161-1170) https://doi.org/10.1049/iet-rpg.2015.0474
  34. Reddy P. J., Kumar T. A.: AGC of three-area hydro-thermal system in deregulated environment using FOPI and IPFC. 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), Chennai; 2017: pp.2815–2821, doi:
  35. https://doi.org/10.1109/ICECDS.2017.8389969
  36. Pan and Das (2016) Fractional order AGC for distributed energy resources using robust optimization 7(5) (pp. 2175-2186) https://doi.org/10.1109/TSG.2015.2459766
  37. Ismayil et al. (2015) Fractional order PID controller for automatic generation control of multiarea power systems (pp. 3329-3348) https://doi.org/10.1002/etep.2038
  38. Rambabu N., Narrisetty V., Saikia L.C.: Maiden Application of Coyote Optimizer Algorithm with TIDN Controller in AGC of a Multi-Area Multi-Source System. 2019 IEEE 16th India Council International Conference (INDICON); pp. 1–4.
  39. Sharma et al. (2020) Optimal fractional-order tilted-integral-derivative controller for frequency stabilization in hybrid power system using Salp swarm algorithm 48(18) (pp. 1912-1931) https://doi.org/10.1080/15325008.2021.1906792
  40. Elsisi (2020) Optimal design of nonlinear model predictive controller based on new modified multitracker optimization algorithm (pp. 1857-1878) https://doi.org/10.1002/int.22275
  41. Dash et al. (2016) Flower pollination algorithm optimized PI-PD cascade controller in automatic generation control of a multi-area power system (pp. 19-28) https://doi.org/10.1016/j.ijepes.2016.02.028
  42. Haroun and Li (2017) A novel optimized hybrid fuzzy logic intelligent PID controller for an interconnected multi-area power system with physical constraints and boiler dynamics 71(2) (pp. 364-379) https://doi.org/10.1016/j.isatra.2017.09.003
  43. Padhan et al. (2014) Application of firefly algorithm for load frequency control of multi-area interconnected power system 42(13) (pp. 1419-1430) https://doi.org/10.1080/15325008.2014.933372
  44. Sahu et al. (2013) DE optimized parallel 2-DOF PID controller for load frequency control of power system with governor dead-band nonlinearity (pp. 19-33) https://doi.org/10.1016/j.ijepes.2012.12.009
  45. Saha and Saikia (2018) Combined application of redox flow battery and DC link in restructured AGC system in the presence of WTS and DSTS in distributed generation unit 12(9) (pp. 2072-2085) https://doi.org/10.1049/iet-gtd.2017.1203
  46. Choudhary et al. (2020) Grasshopper optimisation based robust power/frequency regulator for shipboard micro-grid 14(17) (pp. 3568-3577) https://doi.org/10.1049/iet-rpg.2020.0849
  47. Elsisi and Abdelfattah (2020) New design of variable structure control based on lightning search algorithm for nuclear reactor power system considering load-following operation 52(3) (pp. 544-551) https://doi.org/10.1016/j.net.2019.08.003
  48. Elsisi (2022) Improved grey wolf optimizer based on opposition and quasi learning approaches for optimization: case study autonomous vehicle including vision system https://doi.org/10.1007/s10462-022-10137-0
  49. Bhatt et al. (2010) GA/particle swarm intelligence-based optimization of two specific varieties of controller devices applied to two-area multi-units automatic generation control 32(4) (pp. 299-310) https://doi.org/10.1016/j.ijepes.2009.09.004
  50. Babu and Saikia (2019) Automatic generation control of a solar thermal and dish-stirling solar thermal system integrated multi-area system incorporating accurate HVDC link model using crow search algorithm optimised FOPI Minus FODF controller 13(12) (pp. 2221-2231) https://doi.org/10.1049/iet-rpg.2018.6089
  51. Dhiman and Kumar (2017) Spotted hyena optimizer: a novel bio-inspired based metaheuristic technique for engineering applications (pp. 48-70) https://doi.org/10.1016/j.advengsoft.2017.05.014
  52. Ranganayakulua et al. (2016) A comparative study of fractional order PIλ/PIλDµ tuning rules for stable first order plus time delay processes 12(1) (pp. S136-S152)
  53. Oustaloup et al. (1995) The CRONE control of resonant plants: application to a flexible transmission 1(2) (pp. 113-121) https://doi.org/10.1016/S0947-3580(95)70014-0