Main Article Content
This work presents the optimization of a wind-solar-diesel system with battery storage for a continuous and reliable production of electrical energy. In this context, detailed mathematical modeling of the present system and its operation algorithm has been presented. The objective function of the system is to minimize its cost of energy (CoE) which estimates the average lifetime cost of power production per kWh. The cost elements comprising the CoE include investment costs, fuel costs, and operation and maintenance costs. The optimization is performed in the HOMER software in addition to three metaheuristic optimization techniques namely the Cuckoo Search algorithm (CS), the BAT algorithm (BA) and the Firefly algorithm (FA). The simulations conducted in this paper are based on meteorological data collected from an installation in Bouzareah. Simulation results show the excellent properties and superiority of the CS optimization method compared to HOMER, BA and FA algorithms and demonstrate the feasibility of the proposed hybrid PV-wind-diesel-battery system in Bouzareah.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Ounis, H. and N. Aries, On the wind resource in Algeria: Probability distributions evaluation. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 2020: p. 0957650920975883.
Yao, Shujie, Shuai Zhang, and Xingmin Zhang. "Renewable energy, carbon emission and economic growth: A revised environmental Kuznets Curve perspective." Journal of Cleaner Production 235 (2019): 1338-1352.
Lowitzsch, Jens, Christina E. Hoicka, and Felicia J. van Tulder. "Renewable energy communities under the 2019 European Clean Energy Package–Governance model for the energy clusters of the future?." Renewable and Sustainable Energy Reviews 122 (2020): 109489.
Radchenko, Oleksandr, et al. "Prospective directions of state regulation of “green” energy development in the context of Ukraine’s energy safety." (2021).
Basma, Aoukach, and Oukarfi Benyounes. "A simulation energy management system of a multi-source renewable energy based on multi agent system." IAES International Journal of Artificial Intelligence 10.1 (2021): 191.
Alvarez-Carulla, Albert, Jordi Colomer-Farrarons, and Pere Ll Miribel. "Low-Power Energy Harvesting Solutions for Smart Self-Powered Sensors." Sensors for Diagnostics and Monitoring (2018): 217-250.
Bordons, C., Garcia-Torres, F., & Ridao, M. A. (2020). Model predictive control of microgrids (Vol. 358). Cham: Springer.
Bordons, Carlos, Félix Garcia-Torres, and Miguel A. Ridao. Model predictive control of microgrids. Vol. 358. Cham: Springer, 2020.
Fodhil, F., A. Hamidat, and O. Nadjemi, Potential, optimization and sensitivity analysis of photovoltaic-diesel-battery hybrid energy system for rural electrification in Algeria. Energy, 2019. 169: p. 613-624.
Kaabeche, A., M. Belhamel, and R. Ibtiouen, Sizing optimization of grid-independent hybrid photovoltaic/wind power generation system. Energy, 2011. 36(2): p. 1214-1222.
Luna-Rubio, R., et al., Optimal sizing of renewable hybrids energy systems: A review of methodologies. Solar Energy, 2012. 86(4): p. 1077-1088.
Emad, D., et al., Computational methods for optimal planning of hybrid renewable microgrids: a comprehensive review and challenges. Archives of Computational Methods in Engineering, 2019: p. 1-23.
Nadjemi, O., et al., Optimal hybrid PV/wind energy system sizing: Application of cuckoo search algorithm for Algerian dairy farms. Renewable and Sustainable Energy Reviews, 2017. 70: p. 1352-1365.
Marsa, N., et al., Optimal sizing of stand-alone hybrid photovoltaic/wind system using BAT algorithm. International Journal of Ambient Energy, 2019: p. 1-9.
Huaxu, Liang, et al. "Experimental investigation of cost-effective ZnO nanofluid based pectral splitting CPV/T system." Energy 194 (2020): 116913.
Bousdira, K., et al., Combustion Study of Phoenicicole Biomass in Algerian Oasis Using Thermogravimetric Analysis: Deglet Nour Cultivar Case. Arabian Journal for Science and Engineering, 2018. 43(5): p. 2299-2308.
Sawle, Y., S. Gupta, and A.K. Bohre, Optimal sizing of standalone PV/Wind/Biomass hybrid energy system using GA and PSO optimization technique. Energy Procedia, 2017. 117: p. 690-698.
Acevedo-Arenas, C.Y., et al., MPC for optimal dispatch of an AC-linked hybrid PV/wind/biomass/H2 system incorporating demand response. Energy Conversion and Management, 2019. 186: p. 241-257.
Aykut, E. and U.K. Terzi, Techno-economic and environmental analysis of grid connected hybrid wind/photovoltaic/biomass system for Marmara University Goztepe campus. International journal of green energy, 2020. 17(15): p. 1036-1043.
Eberhart, R. and J. Kennedy. Particle swarm optimization. in Proceedings of the IEEE international conference on neural networks. 1995. Citeseer.
Bing, L. and J. Weisun, Chaos optimization method and its application [J]. Control Theory & Applications, 1997. 4.
Dorigo, M. and L.M. Gambardella, Ant colonies for the travelling salesman problem. biosystems, 1997. 43(2): p. 73-81.
Gambardella, L.M. and M. Dorigo, Ant-Q: A reinforcement learning approach to the traveling salesman problem, in Machine learning proceedings 19951995, Elsevier. p. 252-260.
Yang, X., Nature-inspired metaheuristic algorithms. 2010. Firefly algorithm, 2011: p. 79-90.
Yang, X.-S. and S. Deb. Cuckoo search via Lévy flights. in 2009 World congress on nature & biologically inspired computing (NaBIC). 2009. Ieee.
Yang, X., A new metaheuristic bat-inspired algorithm (2010). Nature inspired cooperative strategies for optimization (NICSO 2010): p. 65-74.
Yang, X.-S. Firefly algorithms for multimodal optimization. in International symposium on stochastic algorithms. 2009. Springer.
Kaabeche, A., S. Diaf, and R. Ibtiouen, Firefly-inspired algorithm for optimal sizing of renewable hybrid system considering reliability criteria. Solar Energy, 2017. 155: p. 727-738.
Ribo-Pérez, David, et al. "Modelling biomass gasifiers in hybrid renewable energy microgrids; a complete procedure for enabling gasifiers simulation in HOMER." Renewable Energy 174 (2021): 501-512.
Saheb-Koussa, D., et al., Economic and environmental analysis for grid-connected hybrid photovoltaic-wind power system in the arid region. Energy Procedia, 2011. 6: p. 361-370.
Bahramara, S., M.P. Moghaddam, and M. Haghifam, Optimal planning of hybrid renewable energy systems using HOMER: A review. Renewable and Sustainable Energy Reviews, 2016. 62: p. 609-620.
Mills, A. and S. Al-Hallaj, Simulation of hydrogen-based hybrid systems using Hybrid2. International Journal of Hydrogen Energy, 2004. 29(10): p. 991-999.
Sinha, S. and S. Chandel, Review of software tools for hybrid renewable energy systems. Renewable and Sustainable Energy Reviews, 2014. 32: p. 192-205.
Zhou, W., et al., Current status of research on optimum sizing of stand-alone hybrid solar–wind power generation systems. Applied energy, 2010. 87(2): p. 380-389.
Khenfous, S., et al. Optimal size of renewable hybrid system applying nature-inspired algorithms. in 2018 International Conference on Wind Energy and Applications in Algeria (ICWEAA). 2018. IEEE.
Sba, K.M., et al. Sizing Of A Hybrid (Photovoltaic/Wind) Pumping Systembased On Metaheuristic Optimization Methods. in 2018 International Conference on Wind Energy and Applications in Algeria (ICWEAA). 2018. IEEE.
Overland, I., Future petroleum geopolitics: consequences of climate policy and unconventional oil and gas. Handbook of Clean Energy Systems, 2015: p. 1-29.
Bouznit, M., M.d.P. Pablo-Romero, and A. Sanchez-Braza, Measures to promote renewable energy for electricity generation in Algeria. Sustainability, 2020. 12(4): p. 1468.
Ghezloun, A., S. Chergui, and N. Oucher, Algerian energy strategy in the context of sustainable development (Legal framework). Energy Procedia, 2011. 6: p. 319-324.
Yassa, N. https://www.cnese.dz/static/Cnes/data/Rapport_CEREFE_2020_ Transition%20Energ%C3%A9tique%20en%20Alg%C3%A9rie.pdf. 2020.
Saheb, D. and M. Koussa, An experimental intelligent simulator of a single household: Wind energy application. Journal of Renewable Energies, 2017. 20(4): p. 615-625.
Ross Jr, R. Flat-plate photovoltaic array design optimization. in 14th Photovoltaic Specialists Conference. 1980.
Manwell, J.F., J.G. McGowan, and A.L. Rogers, Wind energy explained: theory, design and application2010: John Wiley & Sons.
Belboid, Y., A. El moumen Zerifi, and C.N. Fiala. Behavior analysis and optimal management of hybrid Wind/Diesel/Storage power system. in 2018 International Conference on Wind Energy and Applications in Algeria (ICWEAA). 2018. IEEE.
Abbes, Dhaker. "Contribution au dimensionnement et à l’optimisation des systèmes hybrides éoliens-photovoltaïques avec batteries pour l’habitat résidentiel autonome." Ecole Nationale Supérieure d'Ingénieurs-Poitiers (2012).
Mohamed, M.A., et al., A novel framework-based cuckoo search algorithm for sizing and optimization of grid-independent hybrid renewable energy systems. International journal of green energy, 2019. 16(1): p. 86-100.