A Renewable Microgrid with Hydrogen for Residential Use: Fuzzy Logic for Multi-Objectives

ilhan GARIP, Zainab Failh Allami, Hassan Mohammed Abid, Bahira Abdulrazzaq Mohammed, Ahmed A. Ali, Zamen Latef Naser, Maki Mahdi Abdulhasan

Abstract


Microgrids that utilize renewable energy sources (RES) need storage systems so that excess renewable electric power can be stored and used at other times when production is short. Renewable energy sources do not have a constant and continuous supply. The multi-component nature of hydrogen hybrid renewable microgrids (production and storage elements with varying characteristics and dynamics) necessitates the implementation of energy management systems (EMS). This is a control system that aims to optimize each element in order to achieve proper microgrid operation by working in synergy. The article proposes the use of a renewable microgrid with hydrogen for the following applications. Fuzzy logic controllers (FLCs) are used to implement a residential SGE. Microgrid performance is to be improved in terms of efficiency, operating costs, and lifetime of its elements by addressing a multi-objective problem. A power balance will be considered, as well as the performance and degradation of its components as well as the cost/benefits of transferring energy with the main grid. Based on heuristic models or techniques, traditional SGE provides better performance and lower economic benefits.


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References


F.K. Abo-Elyousr, J.M. Guerrero, and H. S. Ramadan, “Prospective hydrogen-based microgrid systems for optimal leverage via metaheuristic approaches,” Appl. Energy, vol.300, 117384, 2021.

S.Al-Sakkaf, M.Kassas, M.Khalid, and M.A.Abido, “An Energy Management System for Residential Autonomous DC Microgrid Using Optimized Fuzzy Logic Controller Considering Economic Dispatch,” Energies, vol.12, 1457, 2019.

V.A.Freire, L.V.R. de Arruda, C.Bordons, and J. J. Marquez, Optimal Demand Response Management of a Residential Microgrid using Model Predictive Control. IEEE Access, 2020.

H. Merabet, T.Bahi, A.Boukadoum, and D. Drici, “Study and analysis of the operation of a Cuk converter for precise voltage regulation,” ijSmartGrid, vol 7, pp. 148-153, 2023.

L.Amira, B.Tahar, and I.Yousra, “Performance of Meta-heuristic Algorithm for a Photovoltaic System under Partial Shade,” ijSmartGrid, vol. 7, pp. 160-167, 2023.

F. J Vivas, A. De las Heras, F. Segura, and J. M. Andújar, “H2RES2 simulator A new solution for hydrogen hybridization with renewable energy sources-based systems,” Int. J. Hydrog. Energy, vol.42, pp.13510–13531, 2017.

P.K.Polamarasetty, S.S.N.Ramakrishna, V.Muddala, and M. Vinay Kumar, “A Review on The Estimate Solar PV Cell Variables For Efficient Photovoltaic Systems,” ijSmartGrid, vol 7, pp. 154-159,2023.

K. Ullah, G. Hafeez, I. Khan, S. Jan, and N. Javaid, “A multi-objective energy optimization in smart grid with high penetration of renewable energy sources,” Appl. Energy, vol.299, 117104, 2021.

M. Kamruzzaman, Md. Anwarul, and Md. Anwarul Abedin, “Optimization of Solar Cells with Various Shaped Surficial Nanostructures,” ijSmartGrid, vol 7, pp.113-118, 2023.

F.García-Torres, and C.Bordons, “Optimal Economical Schedule of Hydrogen-Based Microgrids With Hybrid Storage Using Model Predictive Control,” IEEE Trans. Ind. Electron., vol.62, pp.5195–5207, 2015.

J.M.Andújar, J.M.Bravo, and A.Peregrín, “Stability analysis and synthesis of multivariable fuzzy systems using interval arithmetic,” Fuzzy Sets Syst. 148, 337–353, 2004.

E.H.Mamdani, and S.Assilian, “An experiment in linguistic synthesis with a fuzzy logic controller,” Int. J. Man. Mach. Stud, vol.7, pp.01–13, 1975.

A. Balodeau, and K. Agbossou, “Control analysis of renewable energy system with hydrogen storage for residential applications,” J. Power Sources, vol.162, pp.757–764, 2006.

A.Harrag, and S.Messalti, “How fuzzy logic can improve PEM fuel cell MPPT performances? Int. J. Hydrog. Energy vol.43, pp.537–550, 2018.

J.L.Casteleiro-Roca, A.J.Barragán, F.S.Manzano, J.L.Calvo-Rolle, and J.M.Andújar, “Fuel Cell Hybrid Model for Predicting Hydrogen Inflow through Energy Demand,” Electronics, vol. 8, pp.1325-34, 2019.

I.Ngamroo, “Application of electrolyzer to alleviate power fluctuation in a stand-alone microgrid based on an optimal fuzzy PID control,” Int. J. Electr. Power Energy Syst. vol.43, pp.969–976, 2012.

A.T. Sofyan, D.Nael, and A.M. Anas, “Detection of xylene as a detrimental chemical compound by employing a photonic crystal based on porous silicon,” ijSmartGrid, vol.7, pp.38-45, 2023.

A. J. Calderón, F. J Vivas, F. Segura, and J. M, Andújar, “Integration of a Multi-Stack Fuel Cell System in Microgrids: A Solution Based on Model Predictive Control,” Energies, vol. 13, pp. 4924-4934, 2020.

A. J. Barragan, J.M. Enrique, F. Segura, and J. M. Andujar, “Iterative fuzzy modeling of hydrogen Fuel Cells by the extended kalman filter,” IEEE Access, vol.8, pp.180280–180294, 2020.

N.Nabipour, S.N. Qasem, and K.Jermsittiparsert, “Type-3 fuzzy voltage management in PV/Hydrogen fuel cell/battery hybrid systems,” Int. J. Hydrog. Energy, 45(56), 32478–32492, 2020.

J.Hu, Y.Shan, J.M.Guerrero, A.Ioinovici, K.W.Chan, and J.Rodriguez, “Model predictive control of microgrids – An overview,” Renew. Sust. Energ. Rev., vol.136, 110422, 2021.

J.V.Francisco, S.Francisca, M.A.José, P.Adriana, L.S.Jaime, I.Fernando, and L.Eduardo, “Multi-objective fuzzy logic-based energy management system for microgrids with battery and hydrogen energy storage system,” Electronics, vol.9, pp.01-23, 2020.




DOI (PDF): https://doi.org/10.20508/ijrer.v14i1.14828.g8877

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