Optimum design of wind turbine, photovoltaic panel, diesel generator hybrid system and its integration with the distribution network

Zahedi, Rahim; Gitifar, Siavash; Ahmadi, Abolfazl

doi:10.22034/jrenew.2025.196363

Optimum design of wind turbine, photovoltaic panel, diesel generator hybrid system and its integration with the distribution network

Document Type : Original Article

Authors

Rahim Zahedi ¹

siavash gitifar ²

Abolfazl Ahmadi ³

¹ Department of New Energies and Environment, Faculty of New Technologies. University of Tehran, Tehran, Iran

² Faculty of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran

³ Department of Energy Systems Engineering, Faculty of New Technologies. Iran University of Science and Technology, Tehran, Iran

https://doi.org/10.22034/jrenew.2025.196363

Abstract

The inability of conventional energy sources to fully meet the ever-increasing energy demand in today's world points to the ever-increasing importance of hybrid power generation systems. Today, the hybrid systems of electricity production, in which part or all of its sources are renewable energy sources, have attracted the attention of many researchers, scientists, and investors. This research proposes an independent multi-source hybrid generation system with optimal design, including photovoltaic panels, wind turbine generators, batteries, and diesel generators. This research aims to minimize the emission of carbon dioxide and the cost, which is expressed in the form of the net present value of the system. The designed hybrid power generation system is further integrated into the distribution system as a distributed generation. This is to optimally improve the distribution system's performance by minimizing the entire distribution system's total losses and voltage deviation. The combined cost and emissions of energy purchased from the grid and energy produced by distributed generation are also reduced. For this purpose, a multi-objective particle swarm optimization algorithm has been developed. The proposed optimization algorithms are implemented using software for an IEEE standard 33-bus distribution system. The location and size of scattered productions and the type and number of each generating source of the hybrid system are considered decision variables.

Keywords

Multi-Source Hybrid System

Multi-Objective Particle Swarm

Optimization

Distributed generation

MATLAB

HOMER

Subjects

Renewable Energy

8- مراجع

[1] O. D. T. Odou, R. Bhandari, and R. Adamou, Hybrid off-grid renewable power system for sustainable rural electrification in Benin, Renewable energy, Vol. 145, pp. 1266-1279, 2020.

[2] S. Y. Abujarad, M. W. Mustafa, and J. J. Jamian, Recent approaches of unit commitment in the presence of intermittent renewable energy resources: A review, Renewable and Sustainable Energy Reviews, Vol. 70, pp. 215-223, 2017.

[3] E. Saedpanah, R. F. Asrami, A. Sohani, and H. Sayyaadi, Life cycle comparison of potential scenarios to achieve the foremost performance for an off-grid photovoltaic electrification system, Journal of Cleaner Production, Vol. 242, p. 118440, 2020.

[4] A. Louwen, W. G. Van Sark, A. P. Faaij, and R. E. Schropp, Re-assessment of net energy production and greenhouse gas emissions avoidance after 40 years of photovoltaics development, Nature Communications, Vol. 7, No. 1, pp. 1-9, 2016.

[5] A. Kaabeche, M. Belhamel, and R. Ibtiouen, Sizing optimization of grid-independent hybrid photovoltaic/wind power generation system, Energy, Vol. 36, No. 2, pp. 1214-1222, 2011.

[6] C. Ghenai, A. Merabet, T. Salameh, and E. C. Pigem, Grid-tied and stand-alone hybrid solar power system for desalination plant, Desalination, Vol. 435, pp. 172-180, 2018.

[7] A. S. Al-Buraiki and A. Al-Sharafi, Hydrogen production via using excess electric energy of an off-grid hybrid solar/wind system based on a novel performance indicator, Energy Conversion and Management, Vol. 254, p. 115270, 2022.

[8] A. Elouali et al., Physical models for packed bed: Sensible heat storage systems, Journal of Energy Storage, Vol. 23, pp. 69-78, 2019.

[9] H. Mehrjerdi, E. Rakhshani, and A. Iqbal, Substation expansion deferral by multi-objective battery storage scheduling ensuring minimum cost, Journal of energy storage,Vol. 27, p. 101119, 2020.

[10] H. Mehrjerdi and R. Hemmati, Electric vehicle charging station with multilevel charging infrastructure and hybrid solar-battery-diesel generation incorporating comfort of drivers, Journal of Energy Storage, Vol. 26, p. 100924, 2019.

[11] Y. Venumadhav, Performance analysis of PI controller based grid connected renewable energy system, Int Res J Eng Technol (IRJET), Vol. 5, No. 09, 2018.

[12] H. Mehrjerdi and R. Hemmati, Modeling and optimal scheduling of battery energy storage systems in electric power distribution networks, Journal of Cleaner Production, Vol. 234, pp. 810-821, 2019.

[13] T. Kousksou, P. Bruel, A. Jamil, T. El Rhafiki, and Y. Zeraouli, Energy storage: Applications and challenges, Solar Energy Materials and Solar Cells, Vol. 120, pp. 59-80, 2014.

[14] H. Mehrjerdi, Modeling and optimization of an island water-energy nexus powered by a hybrid solar-wind renewable system, Energy, Vol. 197, p. 117217, 2020.

[15] K. M. Kotb et al., A fuzzy decision-making model for optimal design of solar, wind, diesel-based RO desalination integrating flow-battery and pumped-hydro storage: Case study in Baltim, Egypt, Energy Conversion and Management, Vol. 235, p. 113962, 2021.

[16] S. A. Memon, D. S. Upadhyay, and R. N. Patel, Optimal configuration of solar and wind-based hybrid renewable energy system with and without energy storage including environmental and social criteria: A case study, Journal of Energy Storage,Vol. 44, p. 103446, 2021.

[17] W. Zhang and A. Maleki, Modeling and optimization of a stand-alone desalination plant powered by solar/wind energies based on back-up systems using a hybrid algorithm, Energy, p. 124341, 2022.

[18] W. Zhang, A. Maleki, and M. A. Nazari, Optimal operation of a hydrogen station using multi-source renewable energy (solar/wind) by a new approach, Journal of Energy Storage, Vol. 53, p. 104983, 2022.

[19] Y. Cao, M. S. Taslimi, S. M. Dastjerdi, P. Ahmadi, and M. Ashjaee, Design, dynamic simulation, and optimal size selection of a hybrid solar/wind and battery-based system for off-grid energy supply, Renewable Energy, Vol. 187, pp. 1082-1099, 2022.

[20] K. Babaremu et al., Overview of Solar–Wind Hybrid Products: Prominent Challenges and Possible Solutions, Energies, Vol. 15, No. 16, p. 6014, 2022.

[21] G. Dalton, D. Lockington, and T. Baldock, Case study feasibility analysis of renewable energy supply options for small to medium-sized tourist accommodations, Renewable Energy, Vol. 34, No. 4, pp. 1134-1144, 2009.

[22] D. Novitasari, S. P. Hadi, and R. Budiarto, Generation Expansion Planning by Considering Climate-Land Use-Energy-Water (CLEW) Nexus, in 2021 International Conference on Technology and Policy in Energy and Electric Power (ICT-PEP), 2021: IEEE, pp. 424-429.

[23] E. Koutroulis, D. Kolokotsa, A. Potirakis, and K. Kalaitzakis, Methodology for optimal sizing of stand-alone photovoltaic/wind-generator systems using genetic algorithms, Solar energy, Vol. 80, No. 9, pp. 1072-1088, 2006.

[24] R. Dufo-López and J. L. Bernal-Agustín, Design and control strategies of PV-Diesel systems using genetic algorithms, Solar energy, vol. 79, no. 1, pp. 33-46, 2005.

[25] A. Singh and S. Parida, Combined optimal placement of solar; wind and fuel cell based DGs using AHP, in World Renewable Energy Congress-Sweden; 8-13 May; 2011; Linköping; Sweden, 2011, no. 057: Linköping University Electronic Press, pp. 3113-3120.

[26] P. Kayal and C. Chanda, Placement of wind and solar based DGs in distribution system for power loss minimization and voltage stability improvement, International Journal of Electrical Power & Energy Systems, Vol. 53, pp. 795-809, 2013.