A hybrid renewable energy production system using a smart controller based on fuzzy logic
Keywords:hybrid energy system, renewable energy, battery storage, fuzzy logic, smart management
Introduction. This article proposes an improved energy management and optimization system with an intelligent economic strategy based on fuzzy logic technology with multiple inputs and outputs (I/O). It is used to control hybrid electric energy sources built around photovoltaic solar panels, wind turbine and electric energy storage system assisted by the electric grid. The novelty in this work that solar photovoltaic, wind turbine and storage system energy sources are prioritized over the grid network which is solicited only during adverse weather conditions, in order to supply a typical household using up to 4,000 Wh per day. In addition of that, the surplus of renewable energy produced during favorable climatic condition is used to produce hydrogen suitable for household heating and cooking using eletrolyzer system. Purpose. Development of improved energy management and optimization system with an intelligent economic strategy based on fuzzy logic technology. This system is embedded on Arduino 2560 mega microcontroller, on which the fundamental program of fuzzy logic and the distribution of events with all possible scenarios have been implemented according to a flowchart allowing the management of the hybrid system. Methods as well as a parametric search and a simulation to characterize the system, are carried out in order to put on the proposed techniques to ensure continuous accommodation at home. Results. The proposed system results confirm their effectiveness by visualizing the output control signals from the electronic switches. Practical value of which transmits power through a single-phase DC/AC converter to power the AC load for the accommodation.
Assahout S., Elaissaoui H., El Ougli A., Tidhaf B., Zrouri H. A Neural Network and Fuzzy Logic based MPPT Algorithm for Photovoltaic Pumping System. International Journal of Power Electronics and Drive Systems, 2018, vol. 9, no. 4, pp. 1823-1833. doi: https://doi.org/10.11591/ijpeds.v9.i4.pp1823-1833.
Abdourraziq M.A., Maaroufi M. Experimental Verification of the main MPPT techniques for photovoltaic system. International Journal of Power Electronics and Drive Systems, 2017, vol. 8, no. 1, pp. 384-391. doi: https://doi.org/10.11591/ijpeds.v8.i1.pp384-391.
Chalok K.H., Tajuddin M.F.N., Sudhakar Babu T., Md Ayob S., Sutikno T. Optimal extraction of photovoltaic energy using fuzzy logic control for maximum power point tracking technique. International Journal of Power Electronics and Drive Systems, 2020, vol. 11, no. 3, pp. 1628-1639. doi: https://doi.org/10.11591/ijpeds.v11.i3.pp1628-1639.
Al-Majidi S.D., Abbod M.F., Al-Raweshidy H.S. A novel maximum power point tracking technique based on fuzzy logic for photovoltaic systems. International Journal of Hydrogen Energy, 2018, vol. 43, no. 31, pp. 14158-14171. doi: https://doi.org/10.1016/j.ijhydene.2018.06.002.
Sahraoui H., Chrifi-Alaoui L., Drid S., Bussy P. Second order sliding mode control of DC-DC converter used in the photovoltaic system according an adaptive MPPT. International Journal of Renewable Energy Research, 2016, vol. 6, no. 2, pp. 375-383. doi: https://doi.org/10.20508/ijrer.v6i2.3369.g6797.
Sahraoui H., Mellah H., Drid S., Chrifi-Alaoui L. Adaptive maximum power point tracking using neural networks for a photovoltaic systems according grid. Electrical Engineering & Electromechanics, 2021, no. 5, pp. 57-66. doi: https://doi.org/10.20998/2074-272X.2021.5.08.
Naik K.A., Gupta C.P. Fuzzy logic based pitch angle controller/or SCIG based wind energy system. 2017 Recent Developments in Control, Automation & Power Engineering (RDCAPE), 2017, pp. 60-65. doi: https://doi.org/10.1109/RDCAPE.2017.8358240.
Ngo Q.-V., Yi C., Nguyen T.-T. The fuzzy-PID based-pitch angle controller for small-scale wind turbine. International Journal of Power Electronics and Drive Systems, 2020, vol. 11, no. 1, pp. 135-142. doi: https://doi.org/10.11591/ijpeds.v11.i1.pp135-142.
Yasmine A., Rafik B., Rachid B., Adel M. Grid connected photovoltaic system efficiency and quality improvement using fuzzy-incond MPPT. International Journal of Power Electronics and Drive Systems, 2020, vol. 11, no. 3, pp. 1536-1546. doi: https://doi.org/10.11591/ijpeds.v11.i3.pp1536-1546.
Baniyounes A.M., Ghadi Y.Y., Zahia M.M.A., Adwan E., Oliemat K. Energy, economic and environmental analysis of fuzzy logic controllers used in smart buildings. International Journal of Power Electronics and Drive Systems, 2021, vol. 12, no. 2, pp. 1283-1292. doi: https://doi.org/10.11591/ijpeds.v12.i2.pp1283-1292.
Derrouazin A., Aillerie M., Mekkakia-Maaza N., Charles J.-P. Multi input-output fuzzy logic smart controller for a residential hybrid solar-wind-storage energy system. Energy Conversion and Management, 2017, vol. 148, pp. 238-250. doi: https://doi.org/10.1016/j.enconman.2017.05.046.
Farah L., Haddouche A., Haddouche A. Comparison between proposed fuzzy logic and ANFIS for MPPT control for photovoltaic system. International Journal of Power Electronics and Drive Systems, 2020, vol. 11, no. 2, pp. 1065-1073. doi: https://doi.org/10.11591/ijpeds.v11.i2.pp1065-1073.
Birane M., Larbes C., Cheknane A. Comparative study and performance evaluation of central and distributed topologies of photovoltaic system. International Journal of Hydrogen Energy, 2017, vol. 42, no. 13, pp. 8703-8711. doi: https://doi.org/10.1016/j.ijhydene.2016.09.192.
Derrouazin A., Mekkakia-Maaza N., Taleb R., Nacef M., Aillerie M. Low Cost Hybrid Energiess Smart Management System Applied for Micro-grids. Energy Procedia, 2014, vol. 50, pp. 729-737. doi: https://doi.org/10.1016/j.egypro.2014.06.090.
Tahri G., Foitih Z.A., Tahri A. Fuzzy logic control of active and reactive power for a grid-connected photovoltaic system using a three-level neutral-point-clamped inverter. International Journal of Power Electronics and Drive Systems, 2021, vol. 12, no. 1, pp. 453-462. doi: https://doi.org/10.11591/ijpeds.v12.i1.pp453-462.
Solaris-store. Available at: https://www.solaris-store.com/1307-panneau-solaire-ibc-polysol-260w.html (Accessed 22 May 2019).
Derrouazin A. Contribution à l’optimisation d’un système intelligent de routage des sources d’énergie hybrides pour application à l’habitat. PhD Thesis, University of Science and Technology of Oran, Algeria, 2017. (Fra).
Ravi Sankar R.S., Kumar S.V.J., Rao G.M. Adaptive Fuzzy PI Current Control of Grid Interact PV Inverter. International Journal of Electrical and Computer Engineering, 2018, vol. 8, no. 1, pp. 472-482. doi: https://doi.org/10.11591/ijece.v8i1.pp472-482.
Baruah A., Basu M., Amuley D. Modeling of an autonomous hybrid renewable energy system for electrification of a township: A case study for Sikkim, India. Renewable and Sustainable Energy Reviews, 2021, vol. 135, pp. 110158. doi: https://doi.org/10.1016/j.rser.2020.110158.
Babatunde O., Denwigwe I., Oyebode O., Ighravwe D., Ohiaeri A., Babatunde D. Assessing the use of hybrid renewable energy system with battery storage for power generation in a University in Nigeria. Environmental Science and Pollution Research, 2022, vol. 29, no. 3, pp. 4291-4310. doi: https://doi.org/10.1007/s11356-021-15151-3.
How to Cite
Copyright (c) 2022 M. Ali Moussa, A. Derrouazin, M. Latroch, M. Aillerie
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors who publish with this journal agree to the following terms:
1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.