Techno-Economic Modeling and Optimization of a Hybrid Wind–Solar Off-Grid System for Remote Areas

Authors

  • sheys khosravi * Department of Electrical Engineering, Ayandegan University, Mazandaran, Tonekabon, Iran.

https://doi.org/10.48314/imes.vi.31

Abstract

The primary objective of this study is to examine the optimal integration of wind and solar renewable energy resources within distribution networks. With the increasing penetration of wind farms into modern power systems, it has become evident that, similar to solar power plants, wind power facilities are subject to inherent uncertainties in electricity generation due to the stochastic nature of wind. Consequently, despite the low cost associated with wind-based electricity production, its large-scale deployment remains limited, as network operators continue to depend on thermal power plants to satisfy load demands reliably. A promising strategy to mitigate the uncertainty associated with renewable generation is the combined utilization of wind and solar power, wherein wind generation can supply the load during periods of low solar irradiation, while solar output can offset reduced wind generation during midday hours.

Keywords:

Renewable energy, Wind energy, Solar energy, Optimization

References

  1. [1] Eltamaly, A. M., Alotaibi, M. A., Alolah, A. I., & Ahmed, M. A. (2021). A novel demand response strategy for sizing of hybrid energy system with smart grid concepts. IEEE access, 9, 20277–20294. https://doi.org/10.1109/ACCESS.2021.3052128
  2. [2] Samy, M. M., Mosaad, M. I., El-Naggar, M. F., & Barakat, S. (2021). Reliability support of undependable grid using green energy systems: Economic study. IEEE access, 9, 14528–14539. https://doi.org/10.1109/ACCESS.2020.3048487
  3. [3] Sawle, Y., Jain, S., Babu, S., Nair, A. R., & Khan, B. (2021). Prefeasibility economic and sensitivity assessment of hybrid renewable energy system. IEEE access, 9, 28260–28271. https://doi.org/10.1109/ACCESS.2021.3058517
  4. [4] Shaheen, M. A. M., Hasanien, H. M., & Al-Durra, A. (2021). Solving of Optimal Power Flow Problem Including Renewable Energy Resources Using HEAP Optimization Algorithm. IEEE access, 9, 35846–35863. https://doi.org/10.1109/ACCESS.2021.3059665
  5. [5] Verma, A., & Singh, B. (2019). An implementation of renewable energy based grid interactive charging station. 2019 IEEE transportation electrification conference and expo (ITEC) (pp. 1–6). IEEE. https://doi.org/10.1109/ITEC.2019.8790455
  6. [6] Ravada, B. R., Tummuru, N. R., & Ande, B. N. L. (2021). Photovoltaic-wind and hybrid energy storage integrated multi-source converter configuration for DC microgrid applications. IEEE transactions on sustainable energy, 12(1), 83–91. https://doi.org/10.1109/TSTE.2020.2983985
  7. [7] Narayanan, V., Kewat, S., & Singh, B. (2021). Control and implementation of a multifunctional solar PV-BES-DEGS based microgrid. IEEE transactions on industrial electronics, 68(9), 8241–8252. https://doi.org/10.1109/TIE.2020.3013740
  8. [8] Rao, T. E., Sundaram, E., Chenniappan, S., Almakhles, D., Subramaniam, U., & Bhaskar, M. S. (2022). Performance improvement of grid interfaced hybrid system using distributed power flow controller optimization techniques. IEEE access, 10, 12742–12752. https://doi.org/10.1109/ACCESS.2022.3146412
  9. [9] Krishna, K. H., Prudhviraj, I. V. N. S. M., Prabhavathi, J., Kartheek, M., & Gopi, K. S. (2021). Performance investigation of multifunctional hybrid wind-solar PV-BES-DEGS based microgrid system with EAF and SOGI based control. 2021 Innovations in power and advanced computing technologies (i-PACT) (pp. 1-8). IEEE. https://doi.org/10.1109/i-PACT52855.2021.9696491
  10. [10] Ramkumar, M. S., Swapna, G., Saravanan, A., Hemalatha, N., Dharmaraj, G., Purushotham, S., & Sivaramkrishnan, M. (2021). Super capacitor based solar and wind grid connected storage system. 2021 third international conference on inventive research in computing applications (ICIRCA) (pp. 218–225). IEEE. https://doi.org/10.1109/ICIRCA51532.2021.9544604
  11. [11] AlKassem, A., Ahmadi, M. Al, & Draou, A. (2021). Modeling and simulation analysis of a hybrid pv-wind renewable energy sources for a micro-grid application. 2021 9th international conference on smart grid (ICSMARTGRID) (pp. 103–106). IEEE. https://doi.org/10.1109/icSmartGrid52357.2021.9551215
  12. [12] Ghosh, S., Barman, J. C., & Batarseh, I. (2021). Model predictive control of multi-input solar-wind hybrid system in dc community with battery back-up. 2021 IEEE 12th international symposium on power electronics for distributed generation systems (PEDG) (pp. 1–8). IEEE. https://doi.org/10.1109/PEDG51384.2021.9494234
  13. [13] Ali, H. H., Kassem, A. M., Al-Dhaifallah, M., & Fathy, A. (2020). Multi-verse optimizer for model predictive load frequency control of hybrid multi-interconnected plants comprising renewable energy. IEEE access, 8, 114623–114642. https://doi.org/10.1109/ACCESS.2020.3004299
  14. [14] Rampradesh, T., & Rajan, C. C. A. (2021). Performance assessment of nmpc based mppt controller and extended kalman filter for a wind/pv hybrid system. 2021 fourth international conference on electrical, computer and communication technologies (ICECCT) (pp. 1–4). IEEE. https://doi.org/10.1109/ICECCT52121.2021.9616873
  15. [15] Alam, M. J. E., Muttaqi, K. M., & Sutanto, D. (2014). A novel approach for ramp-rate control of solar PV using energy storage to mitigate output fluctuations caused by cloud passing. IEEE transactions on energy conversion, 29(2), 507–518. https://doi.org/10.1109/TEC.2014.2304951
  16. [16] Ari, G. K., & Baghzouz, Y. (2011). Impact of high pv penetration on voltage regulation in electrical distribution systems. 2011 international conference on clean electrical power (ICCEP) (pp. 744–748). IEEE. https://doi.org/10.1109/ICCEP.2011.6036386
  17. [17] Bakhiyi, B., Labrèche, F., & Zayed, J. (2014). The photovoltaic industry on the path to a sustainable future-Environmental and occupational health issues. Environment international, 73, 224–234. https://doi.org/10.1016/j.envint.2014.07.023
  18. [18] Das, N., Wongsodihardjo, H., & Islam, S. (2015). Modeling of multi-junction photovoltaic cell using MATLAB/Simulink to improve the conversion efficiency. Renewable energy, 74, 917–924. https://doi.org/10.1016/j.renene.2014.09.017
  19. [19] Aissou, S., Rekioua, D., Mezzai, N., Rekioua, T., & Bacha, S. (2015). Modeling and control of hybrid photovoltaic wind power system with battery storage. Energy conversion and management, 89, 615–625. https://doi.org/10.1016/j.enconman.2014.10.034
  20. [20] Fialho, L., Melício, R., Mendes, V. M. F., Viana, S., Rodrigues, C., & Estanqueiro, A. (2014). A simulation of integrated photovoltaic conversion into electric grid. Solar energy, 110, 578–594. https://doi.org/10.1016/j.solener.2014.09.041
  21. [21] Sun, K., Zhang, L., Xing, Y., & Guerrero, J. M. (2011). A distributed control strategy based on DC bus signaling for modular photovoltaic generation systems with battery energy storage. IEEE transactions on power electronics, 26(10), 3032–3045. https://doi.org/10.1109/TPEL.2011.2127488
  22. [22] Zhang, L., Sun, K., Xing, Y., Feng, L., & Ge, H. (2011). A modular grid-connected photovoltaic generation system based on DC bus. IEEE transactions on power electronics, 26(2), 523–531. https://doi.org/10.1109/TPEL.2010.2064337

Published

2025-02-24

Issue

Vol. 2 No. 1 (2025): Intelligence Modeling in Electromechanical Systems

Section

Articles

Categories

How to Cite

khosravi, sheys. (2025). Techno-Economic Modeling and Optimization of a Hybrid Wind–Solar Off-Grid System for Remote Areas. Intelligence Modeling in Electromechanical Systems, 2(1), 48-64. https://doi.org/10.48314/imes.vi.31

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