Abstract
In this paper, an energy management system EMS hourly energy management system for a renewable energy system (HRES) is presented. The proposed HRES is composed of hybrid wind turbine (WT), solar photovoltaic (PV) panels, a diesel generator (DG) and a Distributed Collector System (DCS), as primary energy sources. In turn, an energy storage system (ESS), which is a battery sub-system. The wind turbine, PV panels and DCS system are made to work at peak power, while the battery acts as storage. The EMS uses intelligent rule-based controllers and optimizers to meet the energy demanded by the load and maintain the state of charge (SOC) of the battery between certain target margins, while trying to optimize the utilization cost and lifetime of the BESS. Simulation results show that optimization-based control meets the objectives set for the HRES EMS and achieves a total cost savings of 23.5% over other simpler control state-based EMSs.
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Kroposki, B., Lasseter, R., Ise, T., Morozumi, S., Papatlianassiou, S., Hatziargyriou, N.: Making microgrids work. IEEE Power Energy Mag. 6(3), 40e53 (2008)
Nelson, D.B., Nehrir, M.H., Wang, C.: Unit sizing and cost analysis of stand-alone hybrid wind/PV/fuel cell power generation systems. Renew. Energy 31(10), 1641e56 (2006)
Thameem Ansari, M.Md., Velusami, S.: Dual mode linguistic hedge fuzzy logic controller for an isolated windediesel hybrid power system with superconducting magnetic energy storage unit. Energy Convers. Manag. 51(1), 169e81 (2010)
González, I., Ramiro, A., Calderón, M., Calderón, A.J., González, J.F.: Estimation of the state-of-charge of gel lead-acid batteries and application to the control of a stand-alone wind-solar test-bed with hydrogen support. Int. J. Hydrogen Energy 37(15), 11090e103 (2012)
Etxeberria, A., Vechiu, I., Camblong, H., Vinassa, J.M.: Comparison of three topologies and controls of a hybrid energy storage system for microgrids. Energy Convers. Manag. 54(1), 113e21 (2012)
Thounthong, P., Chunkag, V., Sethakul, P., Sikkabut, S., Pierfederici, S., Davat, B.: Energy management of fuel cell/solar cell/supercapacitor hybrid power source. J. Power Sources 196(1), 313e24 (2011)
Bockris, J.: The origin of ideas on a hydrogen economy and its solution to the decay of the environment. Int. J. Hydrogen Energy 27(7e8), 731e40 (2002)
Erdinc, O., Uzunoglu, M.: Recent trends in PEM fuel cellpowered hybrid systems: investigation of application areas, design architectures and energy management approaches. Renew. Sust. Energy Rev. 14(9), 2874e84 (2010)
Ipsakisa, D., Voutetakisa, S., Seferlisa, P., Stergiopoulosa, F., Elmasides, C.: Power management strategies for a stand-alone power system using renewable energy sources and hydrogen storage. Int. J. Hydrogen Energy 34(16), 7081e95 (2009)
Zhou, K., Ferreira, J.A., de Haan, S.W.H.: Optimal energy management strategy and system sizing method for standalone photovoltaic-hydrogen systems. Int. J. Hydrogen Energy 33(2), 477e89 (2008)
Dursun, E., Kilic, O.: Comparative evaluation of different power management strategies of a stand-alone PV/wind/PEMFC hybrid power system. Int. J. Electr. Power 34(1), 81e9 (2012)
Carapellucci, R., Giordano, L.: Modeling and optimization of an energy generation island based on renewable technologies and hydrogen storage systems. Int. J. Hydrogen Energy 37(3), 2081e93 (2012)
Bernal-Agustın, J.L., Dufo-Lopez, R.: Hourly energy management for grid-connected windehydrogen systems. Int. J. Hydrogen Energy 33(22), 6401e13 (2008)
Dufo-López, R., Bernal-Agustín, J.L., Contreras, J.: Optimization of control strategies for stand-alone renewable energy systems with hydrogen storage. Renew. Energy 32(7), 1102e26 (2007)
Derrouazin, M., Aillerie, N., Mekkakia-Maaza, Charles, J.P.: Fuzzy logic controller versus classical logic controller for residential hybrid solar-wind-storage energy system. AIP Conf. Proc. 1758 (2016). https://doi.org/10.1063/1.4959451
Yuan, Y., Zhang, T., Shen, B., Yan, X., Long, T.: A fuzzy logic energy management strategy for a photovoltaic/diesel/battery hybrid ship based on experimental database. Energies 11(9) (2018). https://doi.org/10.3390/en11092211
Derrouazin, M., Aillerie, N., Mekkakia-Maaza, Charles, J.P.: Multi input-output fuzzy logic smart controller for a residential hybrid solar-wind-storage energy system. Energy Convers. Manag. 148, 238–250 (2017). https://doi.org/10.1016/j.enconman.2017.05.046
Messalti, A., Harrag, A., Loukriz, A.: A new variable step size neural networks MPPT controller: review, simulation and hardware implementation. Renew. Sustain. Energy Rev. 68, 221–233 (2017). https://doi.org/10.1016/j.rser.2016.09.131
Henriques, J., Cardoso, A., Dourado, A., De Coimbra, U.: PID Controllers by Means of a Neural Network, pp. 311–316
Zadeh, L.A.: Information and control. Fuzzy sets 8(3), 338–353 (1965). https://doi.org/10.1016/S0019-9958(65)90241-X (Original Research Article)
Saravanan, S., Thangave, S.: Fuzzy logic controller based power management for a standalone solar/wind/fuel cell fed hybrid system. J. Renew. Sustain. Energy 5, 053147 (2013). https://doi.org/10.1063/1.4827315
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Ampuño-Avilés, G., López-Marcillo, R., Andrade-Núñez, D. (2023). Development of an Energy Management System for a Microgrid Using Neural Networks. Case Study: San Cristobal Island, Galapagos Archipelago. In: López-López, P.C., Barredo, D., Torres-Toukoumidis, Á., De-Santis, A., Avilés, Ó. (eds) Communication and Applied Technologies. Smart Innovation, Systems and Technologies, vol 318. Springer, Singapore. https://doi.org/10.1007/978-981-19-6347-6_5
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