International Transaction Journal of Engineering,
Management, & Applied Sciences & Technologies


:: International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies

ISSN 2228-9860
eISSN 1906-9642


Vol.11(16) (2020)

  • Optimal Sizing of Isolated Hybrid PV/WT/FC System Using Manta Ray Foraging Optimization Algorithm

    Hamdy M. Sultan, Ahmed S. Menesy (Department of Electrical Engineering, Minia University, Minia, EGYPT),
    Salah Kamel (Department of Electrical Engineering, Aswan University, Aswan 81542, EGYPT),
    Ali S. Alghamdi (Department of Electrical Engineering, College of Engineering, Majmaah University, Almajmaah 11952, SAUDI ARABIA),
    Mohamed Zohdy (Electrical and Computer Engineering Department, School of Engineering and Computer Science, Oakland University, Rochester, Rochester, MI 48309, USA).

    Disciplinary: Electrical Engineering (Electric Power Management), Sustainable Energy (Solar Energy, Wind Energy).

    ➤ FullText

    DOI: 10.14456/ITJEMAST.2020.317

    Keywords: Hybrid energy generating system; Photovoltaic; Wind turbine; MRFO; Statistical analysis; Optimal energy system; COE; LPSP.

    This work seeks to optimize the size components of a proposed stand-alone photovoltaic (PV)/ wind turbine (WT)/ fuel cell (FC) hybrid renewable generating system. A new efficient optimization algorithm called Manta-Ray Foraging Optimization (MRFO) is adapted to design the size components of the hybrid system under multi-objective functions, minimizing the cost of energy (COE) and minimizing the loss of power supply probability (LPSP). The real case study is applied in Ataka city, located on the Suez Gulf (latitude 30.0, longitude 32.5) of Egypt. To ensure the high performance and stability of the developed algorithm, this study testes three different system configurations (PV + WT + FC, WT + FC, and PV + FC). Furthermore, statistical measures for the different configurations have been presented to affirm the robustness and reliability of the developed MRFO technique. The simulation results proved the high capability of the MRFO in solving the studied optimization problem with fast convergence and reliable results, to supply loads with the minimum COE.

    Paper ID: 11A16H

    Cite this article:

    Sultan, H. M., Menesy, A. S., Kamel, S., Alghamdi, A. S., Zohdy, M. (2020). Optimal Sizing of Isolated Hybrid PV/WT/FC System Using Manta Ray Foraging Optimization Algorithm. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 11(16), 11A16H, 1-12.


Abedi, S., H. G. Ahangar, M. Nick, and S. H. Hosseinian. (2011). Economic and reliable design of a hybrid PV-wind-fuel cell energy system using a differential evolutionary algorithm. 19th Iranian Conference on Electrical Engineering, IEEE.

Ashari, M., H. Suryoatmojo, I. Robandi, and T. Hiyama. (2010). Optimal Design of Hydrogen Based Stand-Alone Wind/Microhydro System Using Genetic Algorithm. ICSIIT 2010, 71.

Baghaee, H., M. Mirsalim, G. Gharehpetian, and H. Talebi. (2016). Reliability/cost-based multi-objective Pareto optimal design of stand-alone wind/PV/FC generation microgrid system. Energy, 115, 1022-1041.

Baghaee, H. R., M. Mirsalim, and G. B. Gharehpetian. (2016). Power calculation using RBF neural networks to improve the power-sharing of the hierarchical control scheme in multi-DER microgrids. IEEE Journal of Emerging and Selected Topics in Power Electronics, 4(4), 1217-1225.

Bernal-Agust?n, J. L., and R. Dufo-Lopez. (2009). Simulation and optimization of stand-alone hybrid renewable energy systems. Renewable and Sustainable Energy Reviews, 13(8), 2111-2118.

Diab, A. A. Z., H. M. Sultan, I. S. Mohamed, O. N. Kuznetsov, and T. D. Do. (2019). Application of different optimization algorithms for optimal sizing of PV/wind/diesel/battery storage stand-alone hybrid microgrid. IEEE Access, 7, 119223-119245.

Dufo-Lopez, R. and J. L. Bernal-Agust. (2008). Multi-objective design of PV-wind-diesel-hydrogen-battery systems. Renewable energy, 33(12), 2559-2572.

El-Sharkh, M., M. Tanrioven, A. Rahman, and M. Alam. (2006). Cost related sensitivity analysis for optimal operation of a grid-parallel PEM fuel cell power plant. Journal of Power Sources, 161(2), 1198-1207.

Farghally, H. M., F. H. Fahmy, and M. A. El-Sayed. (2014). Control and optimal sizing of PV-Wind powered rural zone in Egypt. Online Journal on Power & Energy Engineering, 2(2), 188-195.

Garcia, R. S., and D. Weisser. (2006). A wind-diesel system with hydrogen storage: Joint optimisation of design and dispatch. Renewable energy, 31(14), 2296-2320.

Kamankesh, H., V. G. Agelidis, and A. Kavousi-Fard. (2016). Optimal scheduling of renewable micro-grids considering plug-in hybrid electric vehicle charging demand. Energy, 100, 285-297.

Kaviani, A. K., G. Riahy, and S. M. Kouhsari. (2009). Optimal design of a reliable hydrogen-based stand-alone wind/PV generating system, considering component outages. Renewable energy, 34(11), 2380-2390.

Khan, M., and M. Iqbal. (2005). Pre-feasibility study of stand-alone hybrid energy systems for applications in Newfoundland. Renewable energy, 30(6), 835-854.

Strunz, K., and E. K. Brock. (2006). Stochastic energy source access management: infrastructure-integrative modular plant for sustainable hydrogen-electric co-generation. International Journal of Hydrogen Energy, 31(9), 1129-1141.

Sultan, H. M., A. A. Z. Diab, N. K. Oleg, and S. Z. Irina. (2018). Design and evaluation of PV-wind hybrid system with hydroelectric pumped storage on the National Power System of Egypt. Global Energy Interconnection, 1(3), 301-311.

Wu, W., V. I. Christiana, S.-A. Chen and J.-J. Hwang. (2015). Design and techno-economic optimization of a stand-alone PV (photovoltaic)/FC (fuel cell)/battery hybrid power system connected to a wastewater-to-hydrogen processor. Energy, 84, 462-472.

Xu, L., X. Ruan, C. Mao, B. Zhang, and Y. Luo. (2013). An improved optimal sizing method for the wind-solar-battery hybrid power system. IEEE transactions on Sustainable Energy, 4(3), 774-785.

Zhao, W., Z. Zhang, L. Wang. (2020). Manta ray foraging optimization: An effective bio-inspired optimizer for engineering applications. Engineering Applications of Artificial Intelligence, 87, 103300. DOI: 10.1016/j.engappai.2019.103300

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