Enhancing Engineering Education through Laboratory Test Benches: A Pedagogical Framework for Global Knowledge Exchange

Authors

Sondes Skander-Mustapha

Universite de Tunis El Manar, Ecole Nationale d’Ingenieurs de Tunis, LR11ES15 Laboratoire de Systemes Electriques, 1002 Tunis; & Universite de Carthage, Ecole Nationale d’Architecture et d’Urbanisme, 2026 Sidi Bou Saïd (Tunisia)

Marwa Ben Said-Romdhane

Universite de Tunis El Manar, Ecole Nationale d’Ingenieurs de Tunis, LR11ES15 Laboratoire de Systemes Electriques, 1002 Tunis; & Universite de Gabès, Institut Superieur des Sciences Appliquées et de Technologie de Gabes, 6029 Gabes (Tunisia)

Article Information

DOI: 10.47772/IJRISS.2025.903SEDU0707

Subject Category: Education

Volume/Issue: 9/26 | Page No: 9325-9334

Publication Timeline

Submitted: 2025-09-18

Accepted: 2025-09-24

Published: 2025-12-02

Abstract

Advances in renewable energy integration, smart grids, and power electronics have led to the development of sophisticated laboratory platforms, including grid emulators, microgrid test benches and digital twin models. Originally conceived for research purposes, these platforms also offer powerful tools for engineering education. This paper explores how research-grade test benches developed in our laboratory can be systematically integrated into engineering curricula to bridge the gap between theory, simulation, and experimental practice. By mapping each platform to specific curricular modules, such as power systems, renewable energy integration, control engineering, and optimization, we demonstrate their capacity to foster experiential learning and strengthen competencies in modeling, system analysis, and real-time implementation. Case examples illustrate how students can engage in project-based learning by designing controllers, analyzing grid fault responses, or optimizing microgrid performance using digital twin frameworks. Beyond enhancing local curricula, these platforms enable global knowledge exchange through open-source models, remote laboratory access, and international collaborative initiatives. This work contributes to educational research by showing how cutting-edge laboratory infrastructures can enrich pedagogy, cultivate practical engineering skills, and promote collaborative learning across borders.

Keywords

Smart Grid Education, Laboratory-Based Learning

Downloads

References

1. Larrondo-Petrie, M. M., Zapata-Rivera, L. F., Aranzazu-Suescun, C., Sanchez-Viloria, J. A., Molina-Peña, A. E., & Santana-Santana, K. S. (2021, November). Addressing the need for online engineering labs for developing countries. In 2021 World Engineering Education Forum/Global Engineering Deans Council (WEEF/GEDC) (pp. 387-396). IEEE. [Google Scholar] [Crossref]

2. May, D., Alves, G. R., Kist, A. A., & Zvacek, S. M. (2023). Online laboratories in engineering education research and practice. In International handbook of engineering education research (pp. 525-552). Routledge. [Google Scholar] [Crossref]

3. Li, Y., Wang, K., Xiao, Y., & Froyd, J. E. (2020). Research and trends in STEM education: A systematic review of journal publications. International journal of STEM education, 7(1), 11. [Google Scholar] [Crossref]

4. Terzieva, V., Paunova-Hubenova, E., & Slavcheva, S. (2024). Trends, challenges, opportunities, and innovations in STEM education. IFAC-PapersOnLine, 58(3), 106-111. [Google Scholar] [Crossref]

5. Anitha, D., Jeyamala, C., & Thiruvengadam, S. J. (2025). Impact Analysis of Conceive-Design-Implement-Operate (CDIO) Educational Framework–a Longitudinal Study. Journal of Engineering Education Transformations, 540-547. [Google Scholar] [Crossref]

6. Frady, K. (2023). Use of virtual labs to support demand-oriented engineering pedagogy in engineering technology and vocational education training programmes: A systematic review of the literature. European Journal of Engineering Education, 48(5), 822-841. [Google Scholar] [Crossref]

7. Van den Beemt, A., Groothuijsen, S., Ozkan, L., & Hendrix, W. (2023). Remote labs in higher engineering education: engaging students with active learning pedagogy. Journal of Computing in Higher Education, 35(2), 320-340. [Google Scholar] [Crossref]

8. Kamp, A. (2023). Engineering Education in the Rapidly Changing World: Rethinking the Vision for Higher Engineering Education|. TU Delft OPEN Publishing. [Google Scholar] [Crossref]

9. Van den Beemt, A., Groothuijsen, S., Ozkan, L., & Hendrix, W. (2023). Remote labs in higher engineering education: engaging students with active learning pedagogy. Journal of Computing in Higher Education, 35(2), 320-340. [Google Scholar] [Crossref]

10. Skander-Mustapha, S., Ghorbal, M. J. B., Said-Romdhane, M. B., Miladi, M., & Slama-Belkhodja, I. (2018). Grid emulator for small scale distributed energy generation laboratory. Sustainable cities and society, 43, 325-338. [Google Scholar] [Crossref]

11. Said-Romdhane, M. B., Skander-Mustapha, S., & Slama-Belkhodja, I. (2020). Robust dynamic grid emulator control. Computers & Electrical Engineering, 85, 106663. [Google Scholar] [Crossref]

12. Ngom, I., Mboup, A. B., Thiaw, L., Skander-Mustapha, S., & Belkhodja, I. S. (2018, March). An improved control for DC-link fluctuation during voltage dip based on DFIG. In 2018 9th International Renewable Energy Congress (IREC) (pp. 1-6). IEEE. [Google Scholar] [Crossref]

13. Ghodbane-Cherif, M., Skander-Mustapha, S., & Slama-Belkhodja, I. (2019). An improved predictive control for parallel grid-connected doubly fed induction generator-based wind systems under unbalanced grid conditions. Wind Engineering, 43(4), 377-391. [Google Scholar] [Crossref]

14. Sayah, A., Saïd-Romdhane, M. B., & Skander-Mustapha, S. (2024). Advanced energy management system with road gradient consideration for fuel cell hybrid electric vehicles. Results in Engineering, 23, 102721. [Google Scholar] [Crossref]

15. Said-Romdhane, M. B., Skander-Mustapha, S., & Slama-Belkhodja, I. (2021, December). Analysis study of city obstacles shading impact on solar PV vehicle. In 2021 4th International Symposium on Advanced Electrical and Communication Technologies (ISAECT) (pp. 01-06). IEEE. [Google Scholar] [Crossref]

16. Said-Romdhane, M. B., Skander-Mustapha, S., & Belhassen, R. (2023). Adaptive Deadbeat Predictive Control for PMSM-based solar-powered electric vehicles with enhanced stator resistance compensation. Science and Technology for Energy Transition, 78, 35. [Google Scholar] [Crossref]

17. Said-Romdhane, M. B., & Skander-Mustapha, S. (2024). Optimizing solar vehicle performance in urban shading conditions with enhanced control strategies. Ain Shams Engineering Journal, 15(10), 102985. [Google Scholar] [Crossref]

18. Skander-Mustapha, S., Ghorbal, M. J. B., Miladi, M., & Slama-Belkhodja, I. (2018, March). Load analysis effect on grid fault emulator. In 2018 9th International Renewable Energy Congress (IREC) (pp. 1-6). IEEE. [Google Scholar] [Crossref]

19. Saïd-Romdhane, M. B., Skander-Mustapha, S., & Slama-Belkhodja, I. (2019, March). Enhanced real time impedance emulation for microgrid equipments testing and applications. In 2019 10th International Renewable Energy Congress (IREC) (pp. 1-6). IEEE. [Google Scholar] [Crossref]

20. Saïd-Romdhane, M. B., Skander-Mustapha, S., & Slama-Belkhodja, I. (2020). Line Impedance Emulator: Modeling, Control Design, Simulation and Experimental Validation. In Numerical Modeling and Computer Simulation. IntechOpen. [Google Scholar] [Crossref]

21. Skander-Mustapha, S., & Slama-Belkhodja, I. (2020, March). Energy management of rooftop PV system including battery storage: case study of ENIT building. In 2020 International Conference on Electrical and Information Technologies (ICEIT) (pp. 1-6). IEEE. [Google Scholar] [Crossref]

22. Dellaly, M., Moussa, S., Skander-Mustapha, S., & Slama-Belkhodja, I. (2021, May). Analysis and Assessment of a Commercial Microgrid Laboratory Platform. In International Conference of the IMACS TC1 Committee (pp. 399-409). Cham: Springer International Publishing. [Google Scholar] [Crossref]

23. Mdini, N., Skander-Mustapha, S., & Slama-Belkhodja, I. (2020). Design of passive power filters for battery energy storage system in grid connected and islanded modes. SN Applied Sciences, 2(5), 933. [Google Scholar] [Crossref]

24. Dellaly, M., Skander-Mustapha, S., & Slama-Belkhodja, I. (2024). A digital twin model-based approach to cost optimization of residential community microgrids. Global Energy Interconnection, 7(1), 82-93. [Google Scholar] [Crossref]

25. Dellaly, M., Skander-Mustapha, S., & Slama-Belkhodja, I. (2023). Optimization of a residential communityʼs curtailed PV power to meet distribution grid load profile requirements. Renewable Energy, 218, 119342. [Google Scholar] [Crossref]

26. Said-Romdhane, M. B., Skander-Mustapha, S., & Slama-Belkhodja, I. (2020, October). PV system inverter control design based on H∞ control. In 2020 11th International Renewable Energy Congress (IREC) (pp. 1-6). IEEE. [Google Scholar] [Crossref]

27. Takriti, M., Skander-Mustapha, S., Boussaada, Z., & Mrabet Bellaaj, N. (2025). Data-driven optimization for efficient integration of photovoltaic agents in residential microgrid systems. Euro-Mediterranean Journal for Environmental Integration, 1-13. [Google Scholar] [Crossref]

Metrics

Views & Downloads

Similar Articles