Management of a hybrid renewable energy storage system

Authors

  • Maissa Medkour
  • Laroussi Kouider

DOI:

https://doi.org/10.54021/seesv5n1-155

Keywords:

energy management, fuel cell, storage, li-ion, photovoltaic (PV) system, hybrid system

Abstract

The development of smart grids, made possible by advancements in computer technology, represents a transformative solution for electricity grids. These systems offer significant improvements in terms of security, reliability, and energy efficiency, while also promoting a low-carbon economy. Smart grids enable more efficient management of electricity supply and demand, as well as optimization of energy storage. However, despite these advantages, challenges persist, particularly in the areas of cybersecurity, and the reliability and speed of information processing. To address these challenges, we propose an innovative algorithm designed for energy management within electricity grids. This algorithm, specifically tailored for grids comprising hybrid storage systems, photovoltaic energy sources, and variable loads, aims primarily to balance supply and demand. This comprehensive approach not only ensures a continuous power supply but also reduces vulnerabilities associated with reliance on a single energy source. To evaluate the effectiveness of this algorithm, we conducted a series of rigorous simulation experiments using the MATLAB platform. These simulations meticulously tested the system's performance, providing substantial experimental evidence of its durability and viability in real-world scenarios. In summary, smart grids offer promising opportunities to enhance the security of electricity grids, maintain supply-demand balance, and promote sustainable energy storage practices. Despite persistent challenges in cybersecurity and information processing, our proposed algorithm represents a significant advancement in addressing these issues and strengthening the capabilities of smart grids.

References

ALHUMADE, H.; REZK, H.; LOUZAZNI, M.; MOUJDIN, I. A.; AL-SHAHRANI, S. Advanced energy management strategy of photovoltaic/PEMFC/lithium-ion batteries/supercapacitors hybrid renewable power system using white shark optimizer. Sensors, v. 23, n. 3, p. 1534, 2023.

ALEXEEVA, O. V.; ROCHE, Y. La Chine en transition énergétique: un virage vers les énergies renouvelables?. Vertigo, v. 14, n. 3, 2014.

AMENEDO, J. L. R.; GÓMEZ, S. A.; ALONSO-MARTINEZ, J.; DE ARMAS, M. G. Grid-forming converters control based on the reactive power synchronization method for renewable power plants. IEEE Access, v. 9, 67989-68007, 2021.

BENCHOUIA, N.; HADJADJ, A. E.; DERGHAL, A.; KHOCHEMANE, L.; MAHMAH, B. Modeling and validation of fuel cell PEMFC. Journal of Renewable Energies, v. 16, n. 2, p. 365-377, 2013.

DJALAB, A. A.; REZAOUI, M. M.; MAZOUZ, L. et al. A robust method for diagnosis and detection of faults in photovoltaic systems using artificial neural networks. Periodica Polytechnica Electrical Engineering and Computer Science, v. 64, n. 3, p. 291-302, 2020.

DJALAB, A. et al. Study of the effects of partial shading on PV array. In: 2018 International Conference on Communications and Electrical Engineering (ICCEE). IEEE, 2018.

FAYYAZI, M.; SARDAR, P.; THOMAS, S. I.; DAGHIGH, R.; JAMALI, A.; ESCH, T. et al. Artificial intelligence/machine learning in energy management systems, control, and optimization of hydrogen fuel cell vehicles. Sustainability, v. 15, n. 6, p. 5249, 2023.

FODHIL, F.; HAMIDAT, A.; NADJEMI, O. Potential, optimization and sensitivity analysis of photovoltaic-diesel-battery hybrid energy system for rural electrification in Algeria. Energy, v. 169, p. 613-624, 2019.

GRANGER, J. H2O – The Mystery, Art, and Science of Water: The Chemistry of Water: Electrolysis. 2020. Available at: http://witcombe.sbc.edu/water/chemistry

electrolysis.html.

GULZAR, M. M.; IQBAL, A.; SIBTAIN, D.; KHALID, M. An innovative converterless solar PV control strategy for a grid connected hybrid PV/wind/fuel-cell system coupled with battery energy storage. IEEE Access, v. 11, p. 23245-23259, 2023.

HAFSI, O.; ABDELKHALEK, O.; MEKHILEF, S.; SOUMEUR, M. A.; HARTANI, M. A.; CHAKAR, A. Integration of hydrogen technology and energy management comparison for DC-Microgrid including renewable energies and energy storage system. Sustainable Energy Technologies and Assessments, v. 52, p. 102121, 2022.

HOSSEINALIZADEH, R.; SHAKOURI, H.; AMALNICK, M. S.; TAGHIPOUR, P. Economic sizing of a hybrid (PV–WT–FC) renewable energy system (HRES) for stand-alone usages by an optimization-simulation model: Case study of Iran. Renewable and Sustainable Energy Reviews, v. 54, p. 139-150, 2016.

JARRY, T.; LACRESSONNIÈRE, F.; JAAFAR, A. et al. Modeling and Sizing of a Fuel Cell—Lithium-Ion Battery Direct Hybridization System for Aeronautical Application. Energies, v. 14, n. 22, p. 7655, 2021.

KOULALI, M.; NEGADI, K.; MANKOUR, M. et al. Adaptive fuzzy control of hybrid PV/fuel cell and battery system using a three-level t type inverter. Przegląd Elektrotechniczny, v. 95, n. 12, p. 25-3, 2019.

LORENTE, D. B.; MOHAMMED, K. S.; CIFUENTES-FAURA, J.; SHAHZAD, U. Dynamic connectedness among climate change index, green financial assets and renewable energy markets: Novel evidence from sustainable development perspective. Renewable Energy, v. 204, p. 94-105, 2023.

MEDGHALCHI, Z.; TAYLAN, O. A novel hybrid optimization framework for sizing renewable energy systems integrated with energy storage systems with solar photovoltaics, wind, battery and electrolyzer-fuel cell. Energy Conversion and Management, v. 294, p. 117594, 2023.

MOHAMED, E.; BELKACEM, K.; DERRADJI, B. et al. Particle swarm optimization-based MPPT technique under partial shading for photovoltaic systems. Journal of Data Acquisition and Processing, v. 38, n. 2, p. 878, 2023.

REBOREDO, J. C.; UGOLINI, A. The impact of energy prices on clean energy stock prices. A multivariate quantile dependence approach. Energy Economics, v. 76, p. 136-152, 2018.

SHARMA, A. K.; PACHAURI, R. K.; CHOUDHURY, S. et al. Role of metaheuristic approaches for implementation of integrated MPPT-PV systems: a comprehensive study. Mathematics, v. 11, n. 2, p. 269, 2023.

SNOUSSI, J.; ELGHALI, S. B.; OUTBIB, R.; MIMOUNI, M. F. Sliding mode control for frequency-based energy management strategy of hybrid storage system in vehicular application. In: 2016 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM) (pp. 1109-1114). IEEE, Jun 2016.

WU, J.; WEI, Z.; LIU, K.; QUAN, Z.; LI, Y. Battery-involved energy management for hybrid electric bus based on expert-assistance deep deterministic policy gradient algorithm. IEEE Transactions on Vehicular Technology, v. 69, n. 11, p. 12786-12796, 2020.

Downloads

Published

2024-06-18

How to Cite

Medkour, M., & Kouider, L. (2024). Management of a hybrid renewable energy storage system. STUDIES IN ENGINEERING AND EXACT SCIENCES, 5(1), 3118–3136. https://doi.org/10.54021/seesv5n1-155