A multipurpose problem-based learning platform for education and research under smart grid umbrella

Abstract

Developing user-friendly learning platform tailored to illustrating the integrative nature of specific subjects can be very effective in enhancing the involvement of students in the classroom. The focus of this paper is twofold; first, highlighting a specific project from a teaching perspective for the design and implementation of a multipurpose experimental test facility for plug-in electric vehicle, renewable energy and energy storage management in the smart grid context. Second, proposing the application of this project as an interactive tool to assist in demonstrating the system behaviour, when teaching the new emerging subjects in power engineering courses particularly, Smart Grid. Indeed, the scope of the test facility with the developed simulation tool is specially structured and oriented to education, training and research studies, where problem-based learning can be easily implemented. The electrical test hardware in this design can be operated independently as a multipurpose experimental setup for plug-in electric vehicle. In addition, it can also be interconnected with a small size wind or photovoltaic system to facilitate a complete hybrid integrated platform for testing and model verification. A variety of illustrative examples are presented to show the features of the test facility with its operation and how the components of this facility were selected. Additionally, several test scenarios are depicted using the developed simulation tool, which cover the assessment of grid integration with its components in the event of unforeseen circumstances. A recommendation that can be drawn from this paper is to motivate academics who are actively involved in conducting research on smart grid, to make use of their hardware or software designs in the process of teaching and learning so that undergraduate students can get the opportunity of observation and experimentation. In this sense, suggestions for future work are proposed.

Keywords

Smart grid education problem-based learning plug-in electric vehicle power conversion energy storage management system

Get full access to this article

View all access options for this article.

References

Haidar

AMA

Muttaqi

Soetanto

Smart grid and its future perspectives in Australia. Renewable Sustainable Energy Rev 2015; 51: 1375–1389.

Ferreira

Fortes

Boucas

MVCM.

Electrical power systems engineering undergraduate courses in Brazil: academic and market perspectives. Int J Elect Eng Educ 2016; 53: 37–53.

Kezunovic M. Teaching the smart grid fundamentals using modeling, simulation, and hands-on laboratory experiments. In: Proceedings of the IEEE power and energy society general meeting, Providence, RI, USA, 25–29 July 2010, pp 1–5. IEEE.

Fernando

M-R

Luis Carlos Herrero-De

Pablo

et al. Using PBL to improve educational outcomes and student satisfaction in the teaching of DC/DC and DC/AC converters. IEEE Trans Educ 2017; 60: 229–237.

Haidar

AMA

Muttaqi

Soetanto

Technical challenges for electric power industries due to grid-integrated electric vehicles in low voltage distributions: a review. Energy Conver Manage 2014; 86: 689–700.

Maher

GMA

Mahammad

Azah

et al. An optimal scheduling controller for virtual power plant and microgrid integration using the binary backtracking search algorithm. IEEE Trans Ind Appl 2018; 54: 2834–2844.

Wilkins

Balakrishnan

MS.

Assessing student satisfaction in transnational higher education. Int J Educ Manage 2013; 27: 143–156.

Sasha

Vial

Montserrat

et al. Improving the laboratory learning experience: a process to train and manage teaching assistants. IEEE Trans Educ 2015; 58: 130–139.

Sasha

Christian

Vial

et al. Decoding student satisfaction: how to manage and improve the laboratory experience. IEEE Trans Educ 2015; 58: 151–158.

10.

Aydın

Kalayci

Implementing consecutive project-based learning in an antenna and propagation course. Int J Elect Eng Educ 2016; 53: 87–96.

11.

Johnson

Hayes

MJ.

A comparison of problem-based and didactic learning pedagogies on an electronics engineering course. Int J Elect Eng Educ 2016; 53: 3–22.

12.

Subhan

Jaffery

Athar

, et al. Teaching tool for a control systems laboratory using a quadrotor as a plant in MATLAB. IEEE Trans Educ 2017; 60: 249–256.

13.

Feisel

Rosa

AJ.

The role of the laboratory in undergraduate engineering education. J Eng Educ 2005; 94: 121–130.

14.

Casas

JDLHI

del Hoyo

ADB.

Learning by doing’ methodology applied to the practical teaching of electrical machines. Int J Elect Eng Educ 2009; 46: 133–149.

15.

Stanisavljevic

Pavlovic

Nikolic

, et al. SDLDS – system for digital logic design and simulation. IEEE Trans Educ 2013; 56: 235–245.

16.

Gallardo

Barrero

Martinez-Torres

, et al. Addressing learner satisfaction outcomes in electronic instrumentation and measurement laboratory course organization. IEEE Trans Educ 2007; 50: 129–136.

17.

Said

FRM

Adikan

Mekhilef

, et al. Implementation of the problem-based learning approach in the Department of Electrical Engineering, University of Malaya. Eur J Eng Educ 2005; 30: 129–136.

18.

Maskell

Grabau

PJ.

A multidisciplinary cooperative problem-based learning approach to embedded systems design. IEEE Trans Educ 1998; 41: 101–103.

19.

Atwa

El-Saadany

Salama

MMA

; et al. Optimal renewable resources mix for distribution system energy loss minimization. IEEE Trans Power Syst 2010; 25: 360–370.

20.

20. Ani

VA.

Design of a reliable hybrid (PV/Diesel) power system with energy storage in batteries for remote residential home. J Energy 2016; 2016: Article ID 6278138.

21.

Ahmed MAH, Al-Khalid bin Hj O and Luiz ACL. Flexibility-based anti-islanding protection of a microgrid integrated with power grid. In: Proceedings of the 5th IEEE international conference on smart energy grid engineering, Canada, 14-17 Aug 2017. pp. 38–45. IEEE.

22.

Ahmed

MAH

Kashem

Behavioral characterization of electric vehicle charging loads in a distribution power grid through modeling of battery chargers. IEEE Trans Ind Appl 2016; 52: 483–492.

23.

HF/PFC 1.5KW Lithium Battery Charger, www.tccharger.com/english/product/t35/47.html (accessed 2 May 2014).

24.

CANdapte Manual Ewert Energy Systems, www.ewertenergy.com (accessed 31 December 2014).

25.

Lithium Iron Phosphate B. Battery Specification type: HP-PW-40AH, Power Type/3.2V 40AH, www.servovision.com/ABF%20Battery%20Cell/HP-PW-40AH.pdf (accessed 15 July 2014).

26.

27.

Orion BMS Wiring & Installation Manual, Ewert Energy Systems.

28.

Operation Manual, JLD404AH Intelligent Ampere Hour Meter, 2012.

29.

High Precision battery monitor, Owner’s Manual, http://tbs-electronics.com (accessed 22 January 2015).

30.

Jiang

Nayanasiri

Maskell

, et al. A hybrid maximum power point tracking for partially shaded photovoltaic systems in the tropics. Renewable Energy 2015; 76: 53–65.

31.

Setting Up Torque | Orion Li-Ion Battery Management System.

32.

Chika IE, Azzi D, Hewitt A, et al. A holistic approach to assessing students’ laboratory performance using Bayesian networks. In: Proceedings of the IEEE Workshop on Computational Intelligence in Virtual Environments, Nashville, TN, USA, 30 March- 2 April 2009, pp. 1–7. IEEE.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

2.45 MB