A Robust Control Strategy for Microgrid Energy Using Fuzzy Logic

• Autorzy: Meliani Meryem , El Barkany Abdellah , El Abbassi Ikram , Absi Rafik , Jeffali Faouaz

Identyfikatory

DOI

10.24425/mper.2023.145371

• Języki publikacji: EN

Abstrakty

EN

This paper highlights the storage charging and discharging issue. The study objective is to manage the energy inputs and outputs of the principal grid at the same time in order to maximize profit while decreasing costs, as well as to ensure the availability of energy according to demand and the decisions to either save or search for energy. A fuzzy logic control model is applied in MATLAB Simulink to deal with the system’s uncertainties in scheduling the storage battery technology and the charging- discharging. The results proved that the fuzzy logic model has the potential to efficiently lower fluctuations and prolong the lifecycle.

Słowa kluczowe

EN

energy control; renewable energy sources; fuzzy logic system; microgrid; storage system; smart grid

• Wydawca: Production Engineering Committee of the Polish Academy of Sciences ; Polish Association for Production Management
• Czasopismo: Management and Production Engineering Review
• Rocznik: 2023
• Tom: Vol. 14, No. 1
• Strony: 127--136
• Opis fizyczny: Bibliogr. 25 poz., rys., tab., wykr.

Twórcy

autor

Meliani Meryem

• Mechanical Engineering Laboratory, Faculty of Science and Technology, Sidi Mohammed Ben Abdellah University, Route d’Imouzzer, 2202, fez, Morocco

• https://orcid.org/0000-0001-8511-3968

autor

El Barkany Abdellah

• Mechanical Engineering Laboratory, Faculty of Science and Technology, Sidi Mohammed Ben Abdellah University, Morocco

autor

El Abbassi Ikram

• CAM, EPMI, France

autor

Absi Rafik

• CAM, EPMI, France

autor

Jeffali Faouaz

• Laboratory of Materials, Waves, Energy and Environment, Mohammed First University, Morocco

Bibliografia

• Aghajani G. and Yousefi N. (2019), Multi-objective optimal operation in a micro-grid considering economic and environmental goals, Evolving Systems, No. 2, Vol. 10, pp. 239–248.
• Arcos-Aviles D., Pascual J., Marroyo L., Sanchis P., and Guinjoan F., (2018), Fuzzy logic-based energy management system design for residential grid-connected microgrids, IEEE Trans. Smart Grid, No. 2, Vol. 9, pp. 530543.
• Burton T., Jenkins N., Sharpe D., and Bossanyi E. (2011), Wind Energy Handbook, Wiley: Hoboken, NJ, USA.
• Chen Y.-K., Wu Y.-C., Song C.-C., and Chen Y.-S., (2013), Design and implementation of energy management system with fuzzy control for DC microgrid systems, IEEE Trans. Power Electron., No. 4, Vol. 28, pp. 15631570.
• Cheng Y., Liu Y., and Hesse H.C. (2018), A PSOoptimized fuzzy logic control-based charging method for individual household battery, Energies, No. 469, p. 469, Vol. 11.
• El Bourakadi D., Yahyaouy A., and Boumhidi J. (2020), Multi-agent system based on the extreme learning machine and fuzzy control for intelligent energy management in microgrid, Journal of Intelligent Systems, No. 1, Vol. 29, pp. 877–893.
• Faisal M., Hannan M.A., Ker P.J., Hussain A., Mansur M., and Blaabjerg F. (2018), Review of energy storage system technologies in microgrid applications: Issues and challenges, IEEE Access Vol. 6, No. 1. DOI: 10.1109/ACCESS.2018.2841407.
• Faisal M., Hannan M.A., Ker P.J., Rahman M.A., Begum R.A., and Mahlia T.M.I. (2020), Particle swarm optimised fuzzy controller for charging-discharging and scheduling of battery energy storage system in MG applications, Energy Reports, Vol. 6, pp. 215– 228.
• Faisal M., Hannan M.A., Ker P.J., and Uddin M.N. (2019), Backtracking search algorithm based fuzzy charging-discharging controller for battery storage system in microgrid applications, IEEE Access, No. 7, 159357–159368.
• Faisal M. and Koivo H. (2011), Modelling and environmental/economic power dispatch of microgrid using multiobjective genetic algorithm optimization, Fundam. Adv. Topics Wind Power, pp. 361–378.
• Graditi G., Ippolito M.G., Telaretti E., and Zizzo G. (2016), Technical and economical assessment of distributed electrochemical storages for load shifting applications: An Italian case study, Renew. Sustain. Energy Rev., Vol. 57, pp. 515–523.
• Garcia-Gutierrez G., Martínez W., Pereira D., Carrera E.V., Guinjoan F., Pacheco D., et al. (2021), A Comparison of Fuzzy-Based Energy Management Systems Adjusted by Nature-Inspired Algorithms, Applied Sciences.
• Leonori S., Paschero M., Massimo F., Mascioli F., and Rizzi A. (2020), Optimization strategies for microgrid energy management systems by genetic algorithms, Appl. Soft Comput. J., Vol. 86, pp. 105903. DOI: 10.1016/j.asoc.2019.105903.
• Li J., Zhang M., Yang Q., Zhang Z., and Yuan W. (2016), SMES/battery hybrid energy storage system for electric buses, IEEE Trans. Appl. Supercond., No. 4, Vol. 26.
• Martínez J.J., Padilla-Medina J.A., Cano-Andrade S., Sancen A., Prado J., and Barranco A.I. (2018), Development and application of a fuzzy control system for a lead-acid battery bank connected to a DC microgrid, Int. J. Photoenergy, No. 2487173, Vol. 2018.
• Meliani M., Barkany A.E., Abbassi I.E., Darcherif A.M., and Mahmoudi M. (2021), Energy management in the smart grid: State-of-the-art and future trends, International Journal of Engineering Business Management, Vol. 13, 18479790211032920.
• Meliani M., El Barkany A., El Abbassi I., Darcherif A.M., and Mahmoudi M. (2021), Smart grid implementation in Morocco: Case study, Materials Today: Proceedings.
• Migan G.-A. (2013), Study of the Operating Temperature of a PV Module, Lund University: Lund, Sweden.
• Moradi M.H., Eskandari M., and Hosseinian S.M., (2015), Operational strategy optimization in an optimal sized smart micro-grid, IEEE Trans. Smart Grid, No. 3, Vol. 6, pp. 1087–1095.
• Natsheh E.M., Natsheh A.R., and Albarbar A. (2013), Intelligent controller for managing power within standalone hybrid power systems, IET Sci., Meas. Technol., No. 4, Vol. 7, pp. 191–200. DOI: 10.1049/ietsmt.2013.0011.
• Reichmuth D., and Goldman J. (2017), Accelerating US leadership in electric vehicles, Union Concerned Sci., Cambridge, MA, USA, Tech. Rep, [Online]. Available: https://www.ucsusa.org/EV-incentives.
• Solar Electric Supply, SOLAREX-PHOTOVOLTAIC SOLAR MODULES n.d., Available online: https://www.solarelectricsupply.com/solar-panels/solarex (accessed on 9 May 2017).
• Vestas. Vestas|Wind It Means the World to Us n.d., Available online: https://www.vestas.com/ (accessed on9 May 2017).
• Viegas M.A.A. and da Costa C.T. (2021), Fuzzy Logic Controllers for Charging/Discharging Management of Battery Electric Vehicles in a Smart Grid, Journal of Control, Automation and Electrical Systems, pp. 1–14.
• Zadeh L.A. (1965), Fuzzy sets, Information and Control, pp. 338–353.