Abstract
Among the renewable sources of energy, wind and photovoltaic based energy conversion processes are capturing recent interests. As the input to these two kinds of energy conversion processes is highly unpredictable, the incorporation of an energy storage device becomes imperative for an uninterruptible power supply. However, considering hybrid renewable power generation for fulfilling load demand, arbitrary mixing among participating generating units could result in non-profitable outcomes for power supplying entities. Hence, in this work, optimal sizing of a Wind-Photovoltaic-Battery system has been suggested using a hybrid optimization method integrating Ant Colony Optimization extended to continuous domains (ACO\(_{\text {R}}\)) and Genetic Algorithm (GA) forming ACO\(_{\text {R}}\)-GA. The ACO\(_{\text {R}}\)-GA is compared against other algorithms like Ant Colony Optimization (ACO), GA, Particle Swarm Optimization (PSO), and Grasshopper Optimization Algorithm (GOA) for 10 independent runs. The analysis shows that the proposed hybrid algorithm shows better performance in terms of convergence speed, obtaining global minima, and rendering a more reliable solution.
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References
Bajpai, P., Dash, V.: Hybrid renewable energy systems for power generation in stand-alone applications: a review. Renew. Sustain. Energy Rev. 16(5), 2926–2939 (2012)
Amer, M., Namaane, A., M’sirdi, N.: Optimization of hybrid renewable energy systems (HRES) using PSO for cost reduction. Energy Procedia 42, 318–327 (2013)
Kamjoo, A., Maheri, A., Dizqah, A.M., Putrus, G.A.: Multi-objective design under uncertainties of hybrid renewable energy system using NSGA-ii and chance constrained programming. Int. J. Electr. Power Energ. Syst. 74, 187–194 (2016)
Anand, P., Rizwan, M., Bath, S.K.: Sizing of renewable energy based hybrid system for rural electrification using grey wolf optimisation approach. IET Energ. Syst. Integr. 1(3), 158–172 (2019)
Yang, H., Zhou, W., Lu, L., Fang, Z.: Optimal sizing method for stand-alone hybrid solar-wind system with LPSP technology by using genetic algorithm. Sol. Energy 82(4), 354–367 (2008)
Suhane, P., Rangnekar, S., Mittal, A., Khare, A.: Sizing and performance analysis of standalone wind-photovoltaic based hybrid energy system using ant colony optimisation. IET Renew. Power Gener. 10(7), 964–972 (2016)
Fathy, A., El-baksawi, O.: Grasshopper optimization algorithm for extracting maximum power from wind turbine installed in al-jouf region. J. Renew. Sustain. Energy 11(3), 033303 (2019)
Vasant, P., Zelinka, I., Weber, G.W.: Intelligent Computing & Optimization, vol. 866. Springer, Cham (2018)
Mitiku, T., Manshahia, M.S.: Fuzzy logic controller for modeling of wind energy harvesting system for remote areas. In: Vasant, P., Zelinka, I., Weber, G.W. (eds.) International Conference on Intelligent Computing & Optimization, pp. 31–44. Springer, Cham (2019)
Tito, M.R., Lie, T.T., Anderson, T.: Sizing optimization of wind-photovoltaic hybrid energy systems under transient load. Int. J. Power Energy Syst. 33(4), 168–174 (2013)
Authority, T.E.: (2014). Available at: https://www.ea.govt.nz/dmsdocument/4755
Tito, S., Lie, T., Anderson, T.: Optimal sizing of a wind-photovoltaic-battery hybrid renewable energy system considering socio-demographic factors. Sol. Energy 136, 525–532 (2016)
Auckland, T.K.: (2014). Available at: https://bit.ly/2Bu4Y4H
Borowy, B.S., Salameh, Z.M.: Methodology for optimally sizing the combination of a battery bank and PV array in a wind/PV hybrid system. IEEE Trans. Energy Convers. 11(2), 367–375 (1996)
Yang, H., Lu, L.: Study of typical meteorological years and their effect on building energy and renewable energy simulations. ASHRAE Trans. 110, 424 (2004)
Socha, K., Dorigo, M.: Ant colony optimization for continuous domains. Eur. J. Oper. Res. 185(3), 1155–1173 (2008)
Grefenstette, J.J.: Optimization of control parameters for genetic algorithms. IEEE Trans. Syst. Man Cybern. 16(1), 122–128 (1986)
Nguyen, T.K., Lee, I.G., Kwon, O., Kim, Y.J., Hong, I.P.: Metaheuristic optimization techniques for an electromagnetic multilayer radome design. J. Electromagn. Eng. Sci. 19(1), 31–36 (2019)
Yoon, Y., Kim, Y.H.: The Roles of Crossover and Mutation in Real-Coded Genetic Algorithms. Citeseer, London (2012)
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Hossain, M.A., Abdullah, S.M., Ahmed, A., Islam, Q.N.U., Tito, S.R. (2021). Optimal Generation Mix of Hybrid Renewable Energy System Employing Hybrid Optimization Algorithm. In: Vasant, P., Zelinka, I., Weber, GW. (eds) Intelligent Computing and Optimization. ICO 2020. Advances in Intelligent Systems and Computing, vol 1324. Springer, Cham. https://doi.org/10.1007/978-3-030-68154-8_59
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