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Alizadeh Golmahalleh, Mohammad, Jafari-Nokandi, Meysam. (1404). IGDT-Based Epsilon-Constraint Multi-Objective Optimal Planning of Hybrid Ship Power System with Renewable Energy Resources and Energy Storage System. سامانه مدیریت نشریات علمی, (), -. doi: 10.22098/joape.2025.16711.2290
Mohammad Alizadeh Golmahalleh; Meysam Jafari-Nokandi. "IGDT-Based Epsilon-Constraint Multi-Objective Optimal Planning of Hybrid Ship Power System with Renewable Energy Resources and Energy Storage System". سامانه مدیریت نشریات علمی, , , 1404, -. doi: 10.22098/joape.2025.16711.2290
Alizadeh Golmahalleh, Mohammad, Jafari-Nokandi, Meysam. (1404). 'IGDT-Based Epsilon-Constraint Multi-Objective Optimal Planning of Hybrid Ship Power System with Renewable Energy Resources and Energy Storage System', سامانه مدیریت نشریات علمی, (), pp. -. doi: 10.22098/joape.2025.16711.2290
Alizadeh Golmahalleh, Mohammad, Jafari-Nokandi, Meysam. IGDT-Based Epsilon-Constraint Multi-Objective Optimal Planning of Hybrid Ship Power System with Renewable Energy Resources and Energy Storage System. سامانه مدیریت نشریات علمی, 1404; (): -. doi: 10.22098/joape.2025.16711.2290

IGDT-Based Epsilon-Constraint Multi-Objective Optimal Planning of Hybrid Ship Power System with Renewable Energy Resources and Energy Storage System

Journal of Operation and Automation in Power Engineering
مقالات آماده انتشار، اصلاح شده برای چاپ، انتشار آنلاین از تاریخ 02 آبان 1404    اصل مقاله (3.04 M)
نوع مقاله: Special issue: Advanced Technologies for Resilient and Efficient Microgrid Management: Innovations in Energy Optimization, Security, and Integration
شناسه دیجیتال (DOI): 10.22098/joape.2025.16711.2290
نویسندگان
Mohammad Alizadeh Golmahalleh* 1؛ Meysam Jafari-Nokandi2
1Faculty of Electrical and Computer Engineering, Imam Khomeini Naval University, Nowshahr, Iran.
2Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran.
چکیده
The integration of solar generation and Energy Storage Systems (ESSs) into ship power systems has gained increasing attention. This trend is primarily driven by stringent Marine Pollution Protocol regulations and the increasing integration of Renewable Energy Sources (RESs). Integrating RESs and BESSs into ship power systems helps reduce pollutant emissions from fossil fuel generators. However, inadequate sizing of hybrid ship power systems may result in high investment costs and elevated greenhouse gas emissions. This article introduces a Mixed-Integer Linear Programming model for identifying the optimal configuration of RESs and BESSs. The model incorporates two objective functions, aiming to minimize both costs and pollutant emissions. In the proposed model, the possibility of using four different technologies -lead-acid, nickel-cadmium, lithium-ion, and sodium-sulfur- has been considered for BESSs. For optimal energy management of a hybrid ship power system under photovoltaic radiation uncertainty along the route, Information Gap Decision Theory has been utilized. Considering the two contradictory objective functions in the proposed model, the ε-constraint method has been used to determine Pareto optimal responses, and the fuzzy inference method has been used to determine the final optimal response. The proposed model has been evaluated through four distinct case studies. The analysis of the results shows that using the optimal sizing of RESs and BESSs can lead to a simultaneous reduction in costs and emissions.
کلیدواژه‌ها
Hybrid ship power system planning؛ information gap decision theory؛ epsilon constraint
مراجع
  1. S. Alessandro, P. Mario, and D. Alfonso, “A novel highly integrated hybrid energy storage system for electric propulsion and smart grid applications,” in Adv. Energy Storage Technol. (C. Xiangping and C. Wenping, eds.), p. Ch. 4, Rijeka: IntechOpen, 2018.
  2. Z. Jin et al., “Hierarchical control design for a shipboard power system with DC distribution and energy storage aboard future more-electric ships,” IEEE Trans. Ind. Inf., vol. 14, no. 2, pp. 703–714, 2018.
  3. H. Jabari et al., “A review on propulsion drive trains of electric ships: Structures, challenges and opportunities,” J. Energy Manage. Technol., vol. 9, no. 1, pp. 1–13, 2025.
  4. I. Atawi et al., “Recent advances in hybrid energy storage system integrated renewable power generation: Configuration, control, applications, and future directions,” Batteries, vol. 9, no. 1, p. 29, 2023.
  5. R. Iqbal et al., “Comparative study based on technoeconomics analysis of different shipboard microgrid systems comprising PV/wind/fuel cell/battery/diesel generator with two battery technologies: A step toward green maritime transportation,” Renew. Energy, vol. 221, p. 119670, 2024.
  6. A. Dolatabadi, R. Ebadi, and B. Mohammadi-Ivatloo, “A two-stage stochastic programming model for the optimal sizing of hybrid PV/diesel/battery in hybrid electric ship system,” J. Oper. Autom. Power Eng., vol. 7, no. 1, pp. 16–26, 2019.
  7. C. Leone et al., “Multi-objective optimization of PV and energy storage systems for ultra-fast charging stations,” IEEE Access, vol. 10, pp. 14208–14224, 2022.
  8. A. El Shamy, P. Aduama, and A. Al-Sumaiti, “Chance constrained optimal sizing of a hybrid PV/battery/hydrogen isolated microgrid: A life-cycle analysis,” Energy Convers. Manage., vol. 332, p. 119707, 2025.
  9. X. Bao et al., “Optimal sizing of battery energy storage system in a shipboard power system with considering energy management optimization,” Discrete Dyn. Nat. Soc., vol. 2021, p. 9032206, 2021.
  10. C. Chen et al., “Optimal allocation and economic analysis of energy storage system in microgrids,” IEEE Trans. Power Electron., vol. 26, no. 10, pp. 2762–2773, 2011.
  11. N. Bigdeli, “Optimal management of hybrid PV/fuel cell/battery power system: A comparison of optimal hybrid approaches,” Renew. Sustain. Energy Rev., vol. 42, pp. 377– 393, 2015.
  12. P. Zhao, J. Wang, and Y. Dai, “Capacity allocation of a hybrid energy storage system for power system peak shaving at high wind power penetration level,” Renew. Energy, vol. 75, pp. 541–549, 2015.
  13. M. Arifujjaman, “A comprehensive power loss, efficiency, reliability and cost calculation of a 1 MW/500 kWh battery based energy storage system for frequency regulation application,” Renew. Energy, vol. 74, pp. 158–169, 2015.
  14. H. Zhao et al., “Review of energy storage system for wind power integration support,” Appl. Energy, vol. 137, pp. 545–553, 2015.
  15. A. Boveri et al., “Optimal sizing of energy storage systems for shipboard applications,” IEEE Trans. Energy Convers., vol. 34, no. 2, pp. 801–811, 2018.
  16. A. Bukar et al., “Optimal planning of hybrid photovoltaic/battery/diesel generator in ship power system,” Int. J. Power Electron. Drive Syst., vol. 11, p. 1527, 2020.
  17. A. Diab et al., “Application of different optimization algorithms for optimal sizing of pv/wind/diesel/battery storage stand-alone hybrid microgrid,” IEEE Access, vol. 7, pp. 119223–119245, 2019.
  18. A. Mohammed et al., “Review of optimal sizing and power management strategies for fuel cell/battery/super capacitor hybrid electric vehicles,” Energy Rep., vol. 9, pp. 2213–2228, 2023.
  19. H. Akter et al., “A short assessment of renewable energy for optimal sizing of 100% renewable energy based microgrids in remote islands of developing countries: A case study in bangladesh,” Energies, vol. 15, no. 3, p. 1084, 2022.
  20. M. Moradzadeh and M. Abdelaziz, “A new MILP formulation for renewables and energy storage integration in fast charging stations,” IEEE Trans. Transp. Electr., vol. 6, no. 1, pp. 181–198, 2020.
  21. H. Lan et al., “Optimal sizing of hybrid PV/diesel/battery in ship power system,” Appl. Energy, vol. 158, pp. 26–34, 2015.
  22. H. Liu et al., “Estimation of PV output power in moving and rocking hybrid energy marine ships,” Appl. Energy, vol. 204, pp. 362–372, 2017.
  23. A. Sari et al., “New optimized configuration for a hybrid PV/diesel/battery system based on coyote optimization algorithm: A case study for hotan county,” Energy Rep., vol. 8, pp. 15480–15492, 2022.
  24. J. Zhu et al., “Bi-level optimal sizing and energy management of hybrid electric propulsion systems,” Appl. Energy, vol. 260, p. 114134, 2020.
  25. H. Chen et al., “Optimization of sizing and frequency control in battery/supercapacitor hybrid energy storage system for fuel cell ship,” Energy, vol. 197, p. 117285, 2020.
  26. C. Yao, M. Chen, and Y. Hong, “Novel adaptive multiclustering algorithm-based optimal ess sizing in ship power system considering uncertainty,” IEEE Trans. Power Syst., vol. 33, no. 1, pp. 307–316, 2018.
  27. W. Cao, P. Geng, and X. Xu, “Optimization of battery energy storage system size and power allocation strategy for fuel cell ship,” Energy Sci. Eng., vol. 11, no. 6, pp. 2110–2121, 2023.
  28. P. Venkatesh, R. Gnanadass, and N. Padhy, “Comparison and application of evolutionary programming techniques to combined economic emission dispatch with line flow constraints,” IEEE Trans. Power Syst., vol. 18, no. 2, pp. 688–697, 2003.
  29. N. Kumar, S. Dahiya, and K. Parmar, “Sensitivity analysis based multi-objective economic emission dispatch in microgrid,” J. Oper. Autom. Power Eng., vol. 13, no. 2, pp. 127–139, 2025.
  30. N. Kumar, S. Dahiya, and K. Parmar, “Multi-objective economic emission dispatch optimization strategy considering battery energy storage system in islanded microgrid,” J. Oper. Autom. Power Eng., vol. 12, no. 4, pp. 296–311, 2024.
  31. M. Alizadeh, M. Jafari, and G. Karami, “Mixed integer linear programming for thermal units unit commitment considering load uncertainty, renewable resources and electric vehicles,” Nonlinear Syst. Electr. Eng., vol. 7, no. 1, pp. 108–130, 2020.
  32. F. Jabari et al., “Introduction to information gap decision theory method,” in Robust Opt. Plan. Oper. Electr. Energy Syst., pp. 1–10, 2019.
  33. F. Jabari et al., “Robust unit commitment using information gap decision theory,” in Robust Opt. Plan. Oper. Electr. Energy Syst., pp. 79–93, 2019.
  34. A. Rueda-Medina et al., “A mixed-integer linear programming approach for optimal type, size and allocation of distributed generation in radial distribution systems,” Electr. Power Syst. Res., vol. 97, pp. 133–143, 2013.
  35. M. Kiptoo et al., “Optimal capacity and operational planning for renewable energy-based microgrid considering different demand-side management strategies,” Energies, vol. 16, no. 10, p. 4147, 2023.
  36. A. Shahmoradi and M. Kalantar, “Resource scheduling in a smart grid with renewable energy resources and plug-in vehicles by minlp method,” AUT J. Electr. Eng., vol. 47, no. 2, pp. 39–47, 2015.
  37. D. Akinyele, J. Belikov, and Y. Levron, “Battery storage technologies for electrical applications: Impact in stand-alone photovoltaic systems,” Energies, vol. 10, no. 11, p. 1760, 2017.
  38. X. Luo et al., “Overview of current development in electrical energy storage technologies and the application potential in power system operation,” Appl. Energy, vol. 137, pp. 511–536, 2015.
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