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Dedicated to practitioners who embark on the long journey of discovery for the betterment of mankind, knowing that the road ahead is often paved with quandary and enigma, rather than triumph. Nevertheless, what defines such a voyage is that first step, taken in the hope that each subsequent one would bring humanity a little closer to the desirable future imagined today.

This book attempts to narrate one such journey, and its many successes and failures.

Hassan Farhangi, PhD, SMIEEE, PEng, is the director of smart grid research at British Columbia Institute of Technology (BCIT) in Burnaby, British Columbia, Canada, and adjunct professor at Simon Fraser University in Vancouver, Canada. Dr. Farhangi has held adjunct professor appointments at the National University of Singapore, Royal Road University, in Victoria, Canada, and at the University of British Colombia, in Vancouver, Canada. Dr. Farhangi is currently the chief system architect and the principal investigator of BCIT's smart Microgrid initiative at its Burnaby campus in Vancouver, British Columbia, and the scientific director and principal investigator of Natural Sciences and Engineering Research Council's (NSERC) Pan‐Canadian smart Microgrid network (NSERC Smart Microgrid Network or NSMG‐Net). He has published widely, with numerous contributions in scientific journals and conferences on smart grids and has served on various international standardization committees, such as International Electrotechnical Commission (IEC) Canadian Subcommittee (CSC) Technical Committee 57 (TC 57) Working Group 17 (WG 57) (IEC 61850), Conseil International des Grands Réseaux Électriques (CIGRÉ) WG C6.21 (Smart Metering), CIGRÉ WG C6.22 (Microgrids Evolution), and CIGRÉ WG C6.28 (Hybrid Systems for Off‐Grid Power Supply). Dr. Farhangi obtained his PhD degree from the University of Manchester Institute of Science and Technology, in the United Kingdom, in 1982; his MSc degree from the University of Bradford, in the United Kingdom, in 1978; and his BSc degree from the University of Tabriz, in Iran, in 1976, all in electrical and electronic engineering. Dr. Farhangi is a founding member of SmartGrid Canada, an academic member of CIGRÉ, a member of the Association of Professional Engineers and Geoscientists of British Columbia, and a senior member of the Institute of Electrical and Electronic Engineers.

Geza Joos, PhD, FIEEE is a Professor in the Department of Electrical and Computer Engineering, McGill University, and holds the NSERC/Hydro‐Quebec Industrial Research Chair on the Integration of Renewable Energies and Distributed Generation into the Electric Distribution Grid and the Canada Research Chair in Powering Information Technologies (Tier 1) at McGill University. He has also been involved in industrial consulting and in industry R&D management as technology coordinator for the Power System Planning and Operation Interest Group at CEATI International. His expertise is in power electronics, with applications to power systems and energy conversion. Recent topics have dealt with integration of renewable energy, mainly wind, and distributed generation. He has published numerous journal and conference papers and presented tutorials at international conferences on these subjects. He is active in several Institute of Electrical and Electronic Engineers (IEEE) Power Engineering Society and CIGRE working groups dealing with these issues. He is a Fellow of the IEEE and an active researcher and collaborator with other team members of the NSMG‐Net Strategic Research Network led by Dr. Farhangi and hosted at BCIT. Dr. Joos has supervised many Masters and PhD students at McGill.

This book was prepared as the result of research conducted by the NSERC Strategic Research Network in Smart Microgrids (NSMG‐Net), comprised of researchers from various universities and academic institutions from across Canada. Nevertheless, this book does not necessarily represent the views of these individuals, their universities, their partners, or the funding agencies that have funded their work. As such, the authors make no warrant, express or implied, and assume no legal liability for the information in this book; nor does any party represent that the uses of this information will not infringe upon privately owned rights. This book has not been approved or disapproved by the authors, nor have they certified the accuracy or adequacy of the information in this book. Moreover, the information contained in this book is subject to future revisions. Important notes of limitations include the following: this book is not a replacement for electrical codes or other applicable standards; this book is not intended or provided by the authors as a design specification or as design guidelines for electrical installations; and the book shall not be used for any purpose other than education and training. Persons using this information do so at no risk to the authors, and they rely solely upon themselves to ensure that their use of all or part of this book is appropriate in the particular circumstance.

Figure 1.1 Topology of a smart microgrid  3

Figure 1.2 The evolution of smart grid. Source Farhangi 2010 [1]  4

Figure 1.3 Thematic structure of NSMG‐Net research  10

Figure 1.4 The microgrid design process  22

Figure 2.1 The campus smart microgrid. Source: BCIT Burnaby Campus, NSERC Smart Microgrid Research Network, www.smart‐microgrid.ca/  26

Figure 2.2 The campus microgrid OASIS subsystem. Source: Project 2.5 Report – Microgrid design guidelines and use cases – Presented at AGM NSMG‐Net Sep. 2015  28

Figure 2.3 Campus microgrid STG subsystem. Source: Project 2.5 Report – Microgrid design guidelines and use cases – Presented at AGM NSMG‐Net Sep. 2015  29

Figure 2.4 The campus microgrid smart home subsystem smart microgrid. Source: http://www.smart‐microgrid.ca/wp‐content/uploads/2011/08/Overview‐of‐the‐BCIT‐microgrid.pdf  29

Figure 2.5 Aerial photograph of the 25 kV Distribution Test Line, showing the physical layout. Source: Ross et al. 2014 [5]. Reproduced with permission of CIGRÉ/Hydro.Quebec  30

Figure 2.6 The utility microgrid system. Source: Project 2.5 Report – Microgrid design guidelines and use cases – Presented at AGM NSMG‐Net Sep. 2015. Reproduced with permission of Hydro.Qebec   31

Figure 2.7 Topology of three‐phase sections of North American MV distribution network CIGRE benchmark. Source: CIGRE TF C6.04.02 [7], version 21, August 2010 Reproduced with permission of CIGRÉ  33

Figure 2.8 Modified North American MV distribution network CIGRE benchmark. Source: CIGRE TF C6.04.02 [7], version 21, August 2010 Reproduced with permission of CIGRÉ  34

Figure 3.1 Block diagram of the load model. Source: Haddadi et al. 2013 [8]  38

Figure 3.2 Grid‐tie inverter configuration used for controllable loads  39

Figure 3.3 Grid‐tie inverter control loop used for controllable loads  39

Figure 3.4 Two level half‐bridge topology. Source: Yazdani and Iravani 2010 [9] Reproduced with permission of IEEE/Wiley  40

Figure 3.5 Detailed switch model. Source: Yazdani and Iravani 2010 [9] Reproduced with permission of IEEE/Wiley  40

Figure 3.6 Switching function model. Source: Yazdani and Iravani 2010 [9] Reproduced with permission of IEEE/Wiley  41

Figure 3.7 Average switch model. Source: Yazdani and Iravani 2010 [9] Reproduced with permission of IEEE/Wiley  41

Figure 3.8 Recommended wind turbine model to be used for microgrids. Source: Hansen 2012 [11]  43

Figure 3.9 Schematic diagram of the multi‐DER microgrid system. Source: Etemadi et al. 2012 [12]  44

Figure 3.10 Single‐line diagram of the microgrid used to derive state space equations. Source: Etemadi et al. 2012 [12] Reproduced with permission of IEEE  45

Figure 3.11 Grid‐tie inverter configuration used for the energy storage system  48

Figure 3.12 Grid‐tie inverter control loops used for the energy storage system operating as a current  48

Figure 3.13 Grid‐tie inverter control loops used for the energy storage system operating as a voltage source  48

Figure 3.14 Grid‐tie inverter configuration used for inverter‐interfaced renewable DGs. Source: Kamh et al. 2012 [15]  49

Figure 3.15 Look up tables used to emulate the WTG or PV DG  49

Figure 3.16 Grid‐tie inverter control loop used for renewable DGs  50

Figure 3.17 A typical diesel engine synchronous generator system model  50

Figure 5.1 Microgrid control function timescales. Source: Joos et al. 2017 [30]  66

Figure 5.2 The microgrid control system functional framework core functions. Source: Joos et al. 2017 [30]  66

Figure 5.3 Schematic diagram of the three‐phase EC‐DER and its control architecture. Source: Zamani et al. 2012 [32]  67

Figure 5.4 Enhanced voltage magnitude regulation scheme for the three‐phase EC‐DER. Source: Zamani et al. 2012 [32]  69

Figure 5.5 Frequency regulation loop, augmented with the phase angle restoration loop. Source: Zamani et al. 2012 [32]  69

Figure 5.6 Enhanced voltage magnitude regulation scheme. Source: Zamani et al. 2012 [32]  69

Figure 5.7 The decoupled control strategy with the host DER unit. Source: Haddadi et al. [33]  70

Figure 5.8 Block diagram of the dependencies decoupling control strategy. Source: Haddadi et al. [33]  71

Figure 5.9 Reactive power control loop used for renewable DGs. Source: Ellis et al. 2012 [34]  73

Figure 5.10 Active power control loop used for renewable DGs. Source: Ellis et al. 2012 [34]  73

Figure 5.11 Reactive power control loop used for the ESS (current controlled VSI)  75

Figure 5.12 Active power control loop used for the ESS (current controlled VSI)  76

Figure 5.13 Reactive power control loop used for the synchronous generator [35]  78

Figure 5.14 Active power control loop used for the synchronous generator with diesel engine as shown in Figure 3.17  78

Figure 5.15 Per‐phase block diagram of the DVR control system in FCI mode. Source: Ajaei et al. 2013 [37]. Reproduced with permission of IEEE  80

Figure 5.16 Primary and secondary controllers and SPAACE. Source: Mehrizi‐Sani et al. 2012 [39] Reproduced with permission of IEEE  81

Figure 5.17 Finite state machine representation of SPAACE algorithm Δt is the time passed since violation and T is the maximum permissible time for the violation. Source: Mehrizi‐Sani et al. 2012 [39] Reproduced with permission of IEEE  82

Figure 5.18 Flowchart of the strategy. Source: Mehrizi‐Sani et al. 2012 [40]. Reproduced with permission of IEEE   83

Figure 5.19 The recloser‐fuse coordination algorithm. Source: Zamani et al. 2012 [44] Reproduced with permission of IEEE  86

Figure 5.20 Flowchart of the communications‐assisted protection scheme. Source: Etemadi et al. 2013 [45] Reproduced with permission of IEEE.  87

Figure 5.21 Flowchart of the voltage control scheme including overcurrent protection. Source: Etemadi et al. 2013 [45]. Reproduced with permission of IEEE  88

Figure 5.22 Modification in REF logic. Source: Davarpanah et al. 2013 [47] Reproduced with permission of IEEE  89

Figure 6.1 Typical communication layers representation  92

Figure 6.2 Communication networks overlay between HANs, LANs, and WANs with interfaces applications (inspired from Wu et al. 2012 [48]). Reproduced with permission of CRC  93

Figure 6.3 The campus smart microgrid topology and communication network. (Farhangi 2016 [49])  94

Figure 6.4 Typical physical media for communication links  95

Figure 7.1 A combined power and communication model  102

Figure 7.2 The microgrid modeling approach. Source: Project 2.5 Report – Microgrid design guidelines & use cases – Presented at AGM NSMG‐Net Sep. 2015  103

Figure 7.3 Real time simulation system configuration  104

Figure 8.1 Recommended data and specification requirements for coordinated planning and design  106

Figure 8.2 Microgrid design criteria  109

Figure 8.3 Globalized levelized cost per megawatt‐hour comparison of various DER technologies (https://www.worldenergy.org/wp‐content/uploads/2013/09/WEC_J1143_CostofTECHNOLOGIES_021013_WEB_Final.pdf ‐ accessed 27th July 2018)  110

Figure 8.4 Estimated levelized cost per kilowatt‐hour comparison for energy storage (http://www.eosenergystorage.com/documents/EPRI‐Energy‐Storage‐Webcast‐to‐Suppliers.pdf ‐ accessed 15 August 2017)  111

Figure 8.5 Flowchart of a cost‐benefit analysis methodology. Source: Clavier 2013 [61]. Reproduced with permission of McGill University   112

Figure 8.6 Optimal sizing of islanded microgrids (IMG) methodology. Source: Bhuiyan et al. 2015 [63]. Reproduced with permission of IET  113

Figure 8.7 Standards and application guidelines and application notes relevant to the microgrid design process  117

Figure 9.1 Example of frequency control case study. Source: Farrokhabadi et al. 2015 [64]. Reproduced with permission of IEEE  122

Figure 9.2 Valuation functions of the individual DERs in the microgrid. Source: Ross 2015 [65]. Reproduced with permission of McGill University  123

Figure 9.3 Valuation function of the amalgamated virtual resource for the microgrid at a specific operating point. Source: Ross 2015 [65]. Reproduced with permission of McGill University  124

Figure 9.4 Example of frequency‐related utility regulations. Source: http://www.hydroquebec.com/transenergie/fr/commerce/pdf/e1201_fev09.pdf. Reproduced with permission of HydroQuebec  124

Figure 9.5 Harmonic study on common household loads. (a) Supply voltage and input current waveforms of two commercial variants of LED lamp; (b) frequency spectrum of commercially available LED and CFL lamps. Source: Wang et al. 2013 [62]. Reproduced with permission of IEEE  126

Figure 9.6 DER response to the proposed droop control and the conventional droop‐based control with high gains. Source: Haddadi et al. 2014 [33]. Reproduced with permission of IEEE  127

Figure 9.7 Trace of the dominant eigenvalues of a three DER system for a droop gain. 2 < m₁ < 30 rad/s/MW, m₂ = m₃ = 2 m₁, where m₁, m₂, and m₃ are the droop gains of DER₁, DER₂, and DER₃ respectively. Source: Haddadi et al. 2014 [33]. Reproduced with permission of IEEE  127

Figure 9.8 RMS AC component of the output current of the synchronous generator feeding to the fault. Source: Yazdanpanahi et al. 2014 [66]. Reproduced with permission of IEEE  128

Figure 9.9 Frequency response subject to a FDI persistent attack. Source: Chlela et al. 2016 [67]. Reproduced with permission of IEEE  129

Figure 9.10 Transition between (a) islanded and (b) grid connected mode of operation of a microgrid. Source: Ross et al. 2014 [5]. Reproduced with permission of CIGRE/HydroQuebec  130

Figure 10.1 The EMS Functional Requirements use case diagram  136

Figure 10.2 The Protection use case diagram  139

Figure 10.3 The Intentional Islanding use case diagram  141

Figure 11.1 Single line diagram of the campus OASIS microgrid. Source: Ross and Quashie 2016 [69]  144

Figure 11.2 Total valuation functions and quadratic approximation for multi‐objective optimization approach. Source: Ross and Quashie 2016 [69]  146

Figure 11.3 Value (cost) of curtailing electric vehicles when charging within a 15‐minute period. Source: Ross and Quashie 2016 [69]  147

Figure 11.4 Value of power from ESS to maintain constant power output based on the mean power of the past 24‐hours (P_m). Source: Ross and Quashie 2016 [69]  148

Figure 11.5 Value of the ESS' state of charge for reliability. Source: Ross and Quashie 2016 [69]  148

Figure 11.6 Value of ESS' power output to reach desired SoC for reliability. Source: Ross and Quashie 2016 [69]  149

Figure 11.7 Comparison of power import from the EPS for both EMSs for the first time period analysis. Source: Ross and Quashie 2016 [69]  150

Figure 11.8 Comparison of power import from the EPS for both EMSs for the second time period analysis. Source: Ross and Quashie 2016 [69]  150

Figure 11.9 State of charge for the ESS for both EMSs for the first time period analysis. Source: Ross and Quashie 2016 [69]  151

Figure 11.10 State of charge for the ESS for both EMSs for the second time period analysis. Source: Ross and Quashie 2016 [69]  151

Figure 11.11 Volt‐VAR optimization Engine (VVOE) platform. Source: Manbachi et al. 2015 [22]. Reproduced with the permission of the IEEE  153

Figure 11.12 IA‐based VVO/CVR primary structure in a distribution network (IA, intelligent agent; OLTC, on‐load tap changer; DS, disconnector; CB, capacitor bank; VR, voltage regulator; SM, smart meter). Source: Manbachi et al. 2014 [18]. Reproduced with the permission of the IEEE  154

Figure 11.13 Communication structure of proposed VVO/CVR system, using PLC, agent language programming, access control list (ACL), and IEC 61850 standard. Source: Manbachi et al. 2014 [18]. Reproduced with the permission of the IEEE  154

Figure 11.14 Initial flowchart of CB controller IA operating tasks. Source: Manbachi et al. 2014 [18]. Reproduced with the permission of the IEEE  156

Figure 11.15 Single‐line diagram of the system topology used in the anti‐islanding tests. Blue circled numbers indicate measurement points. Source: Ross et al. 2012 [70]. Reproduced with the permission of the IEEE  157

Figure 11.16 Per unit currents from the substation (blue) and DER (red) during capacitor bank connection, on a base power of 100 kW. Source: Ross et al. 2012 [70]. Reproduced with the permission of the IEEE  159

Figure 11.17 Voltage and current waveform (blue) and RMS (red) values from the inverter during capacitor bank connection (with a series impedance X_S). Source: Ross et al. 2012 [70]. Reproduced with the permission of the IEEE  160

Figure 11.18 Frequency, voltage and current RMS values during motor start‐up (blue for substation current, red for inverter current). Source: Ross et al. 2012 [70]. Reproduced with the permission of the IEEE  161

Figure 11.19 Frequency and RMS voltage values of the inverter PCC during islanding (test number 2). Source: Ross et al. 2012 [70]. Reproduced with the permission of the IEEE  163

Figure 11.20 Voltage and current waveform (blue) and RMS (red) values at the inverter's PCC during islanding (test number 2). Source: Ross et al. 2012 [70]. Reproduced with the permission of the IEEE  163

Figure 11.21 Three‐phase voltage and current waveform (blue) and RMS (red) values at the DER PCC during islanded condition with induction machine connected. Source: Ross et al. 2012 [70]  165

Figure 11.22 DER PCC frequency and RMS voltage during islanded condition with induction machine connected. Source: Ross et al. 2012 [70]  165

Figure 11.23 Options for laboratory evaluations of microgrid controller compliance with site‐specific requirements: (a) pure simulation, (b) CHIL, (c) CHIL and PHIL, and (d) hardware only. Source: Maitra et al. 2017 [2]. Reproduced with the permission of the IEEE  167

Figure 11.24 Hardware‐in‐the‐loop platform based on real‐time digital simulator and the real time controller. Source: Etemadi et al. 2012 [13]. Reproduced with the permission of the IEEE  168

Figure 11.25 Real‐time simulation test bed schematic diagram. Source: Etemadi and Iravani 2013 [45]. Reproduced with the permission of the IEEE  169

Figure 11.26 The real‐time platform with IEC 61850 and HIL capability  170

Figure 11.27 Real time simulation configuration  170

Table 1.1 Smart grid vis‐à‐vis the existing grid  3

Table 2.1 Coincidental peak loading on the nodes of the CIGRE MV distribution network benchmark  35

Table 3.1 System parameters for the multi‐DER microgrid system  45

Table 4.1 Models required for various studies  58

Table 4.2 Types of simulation tools required to perform studies  63

Table 5.1 Voltage regulation control loops descriptions for electronically coupled DGs as shown in Figures 5.9 and 5.10  72

Table 5.2 Frequency regulation control loops descriptions for electronically coupled DGs as shown in Figure 5.10  72

Table 5.3 Input and output labels description for the electronically coupled DG control loops as shown in Figures 5.9 and 5.10  74

Table 5.4 Voltage regulation control loops descriptions for ESS as shown in Figure 5.11  74

Table 5.5 Frequency regulation control loops descriptions for ESS as shown in Figure 5.12  75

Table 5.6 Input and output labels description for the ESS control loops as shown in Figures 5.11 and 5.12  76

Table 5.7 Voltage regulation control loops descriptions for the SG as shown in Figure 5.13  77

Table 5.8 Frequency regulation control loops descriptions for the SG as shown in Figure 5.14  77

Table 5.9 Input and output labels description for the SG control loops as shown in Figures 5.13 and 5.14  79

Table 10.1 Attributes of the EMS use case  134

Table 10.2 Information exchange and associations between objects of the EMS use case  135

Table 10.3 Regulations of the EMS use case  135

Table 10.4 Attributes of the Protection use case  137

Table 10.5 Information exchange and associations between objects of the Protection use case  138

Table 10.6 Regulations of the Protection use case  138

Table 10.7 Attributes of the Intentional Islanding use case  140

Table 10.8 Information exchange and associations between objects of the Intentional Islanding use case  140

Table 10.9 Regulations of the Intentional Islanding use case  141

Table 11.1 Example of quadratic valuation functions of each DER for the MOO EMS framework  149

Table 11.2 Peak power import/export at the microgrid's PCC for both EMSs  151

Table 11.3 Comparison of business cases for the two EMSs  152

Table 11.4 Relay U/O voltage and U/O frequency threshold settings  158

Table 11.5 Power settings for test condition  162

Table 11.6 Islanding time and reason for island  162

The NSERC Smart Microgrid Network (NSMG‐Net) was launched in late 2010 to address a critical and growing need in the electricity industry to transform its existing, outdated power grid into a next generation intelligent (a.k.a. smart) grid. The primary building blocks of a smart grid are smart microgrids, which are geographically compact units with a flexible distribution system integrated with the main power grid, which can be connected and disconnected to run autonomously for self‐sufficiency of energy production and consumption. By definition, each smart microgrid is capable of engaging in energy transactions with other microgrids as well as with a central utility command and control infrastructure, and has geographical attributes and functions that apply to the local area in which it operates.

At the time NSMG‐Net was initiated, the technologies required to develop smart microgrids were in the research phase. Full development of smart microgrids in the utility context required research with respect to each jurisdiction's specific climate, terrain, and available energy sources, as well as testing, verification, and qualification in near‐real environments. The overarching goal of NSMG‐Net was thus to develop the building blocks of a new smart electrical microgrid that could ultimately provide reliable, low cost, and clean power to communities across the globe.

NSMG‐Net started its research in 2010, comprising researchers from universities of New Brunswick, McGill, Toronto, Ryerson, Waterloo, Manitoba, Alberta, Simon Fraser, British Colombia (UBC) and hosted and led by British Columbia Institute of Technology (BCIT). Adopting an interdisciplinary research strategy, and capitalizing on BCIT's Smart Microgrid testbed, NSMG‐Net researchers achieved significant progress in the development of technologies, know‐how and models for smart microgrid system deployment over the six years of their focused research. Considered as one of the most successful Strategic Research networks, funded by NSERC to date, NSMG‐Net published more than 80 papers in peer‐reviewed journals, and made numerous conference presentations in major academic and scientific gatherings across the world. The Network also trained over 130 engineering students, including 37 undergraduates, 50 masters, 48 doctorate, 5 post‐doctoral fellows and 3 research associates. Four patent applications were filed, together with eight IP disclosures. More importantly, there was significant engagement with several industry partners and other stakeholders both nationally and internationally.

This book provides a microgrid design guidelines framework, consisting of specification requirements, design criteria, recommendations, and sample applications for the stakeholder/client in order to comprehend the technologies, limits, tradeoffs, and potential costs and benefits of implementing a smart microgrid. The guidelines take into account such diverse applications of microgrids as required by urban, mining, campus, and remote communities. The development of these guidelines was carried out using a systematic design methodology that comprises design criteria, modeling, simulations, economic and technical feasibility studies, and business case analysis. In addition, the guidelines address the real‐time operation of the microgrid (voltage and frequency control, islanding, and reconnection) as well as the energy management system in islanded and grid‐connected modes. It also summarizes available microgrid benchmarks for the electric power system, control systems, implementation approaches, and the information and communication systems implementable in microgrids. It covers a modeling approach that combines the power and communication systems, allowing a complete system study to be conducted. The book includes the development of use cases and the validation of the models with field results from the BCIT Microgrid and the IREQ test line.

This book is essentially a compilation of research work performed by NSMG‐Net researchers, and published in the public domain, between 2010 and 2016.

This book would not have been possible without the efforts and contributions of the NSERC Smart Microgrid Network (NSMG‐Net) researchers, students, associates, partners, and funders. In particular, the efforts by the NSMG‐Net theme leaders, topic leaders, network researchers, students, and supporting staff during the six years of the network's research are acknowledged. This book capitalizes on numerous papers, reports, and documentations issued by network researchers, including interim reports, annual reports, publications, theses and dissertations, workshops and training materials. The design guidelines, discussed in the body of this book, were extracted, assembled, and inferred out of numerous works published by NSMG‐net researchers. Furthermore, the assistance provided by researchers at the British Columbia Institute of Technology (BCIT), Burnaby, BC and the Institut de recherche d'Hydro‐Québec (IREQ), Varennes, QC is also acknowledged. A special gratitude to our industry and utility partners whose contribution in stimulating suggestions and encouragement, helped in writing these important design guidelines. Finally, the authors would like to acknowledge the information and publications provided by the following researchers, and their students who participated in the NSMG network, including, but not limited to, and in no particular order: Dr. Reza Iravani, University of Toronto, Ontario, Canada; Dr. Geza Joos, McGill University, Quebec, Canada; Dr. Fabrice Labeau, McGill University, Quebec, Canada; Dr. Tho Le‐Ngoc, McGill University, Quebec, Canada; Dr. Dave Michelson, University of British Columbia, BC, Canada, Dr. Ani Gole University of Manitoba, Manitoba, Canada; Dr. Wilsun Xu, University of Alberta, Alberta, Canada; Dr. Julian Meng, University of New Brunswick, NB, Canada, Dr. Eduardo Castillo Guerra, University of New Brunswick, NB, Canada; Dr. Kankar Bhattacharya, University of Waterloo, Ontario, Canada; Dr. Amirnaser Yazdani, Ryerson University, Ontario, Canada; Dr. Hassan Farhangi, BC Institute of Technology, Vancouver, BC, Canada; Dr. Ali Palizban, BC Institute of Technology, Vancouver, BC, Canada; Dr. Siamak Arazanpour, Simon Fraser University, Vancouver, BC, Canada; Dr. Mehrdad Moallem, Simon Fraser University, Vancouver, BC, Canada; Dr. Gary Wang, Simon Fraser University, Vancouver, BC, Canada; Dr. Daniel Lee, Simon Fraser University, Vancouver, BC, Canada.