Optimal Wireless Technology Selection Approach for Sustainable Indian Smart Grid
Keywords:Automation, communication, data acquisition and analysis, data-driven decision-making, evaluation, instrumentation and control, instru- mentation telemetry system, optimal selection, optimization, smart grid, sustainable energy.
The smart grid is playing a game-changing role in achieving clean and green energy, infrastructure, and cities, which are all part of the sustainable development goals. The significance of communication infrastructure in the reliable design and operation of the smart grid is well recognized, notably for renewable integration, facilitating distributed energy resources and storage, demand response, and energy efficiency. Since choosing the optimal communication technology is a strategic decision, the problem needs careful investigation, taking into account realistic data traffic estimates to fulfill the communication needs of the applications envisaged. Even though a vast array of technologies with diverse capabilities is available to meet such communication needs, choosing the optimal wireless technology for a smart grid project remains a difficult challenge. In this context, to achieve and maximize the benefits of the smart grid and its applications, a systematic and efficient approach is necessary. This study proposes a data-driven decision-making approach for evaluating the capabilities of viable wireless technology options and selecting the most suitable option for the smart grid project at the design phase. The suggested approach and the decision-support tool were developed using a cost-function-based optimization technique. A case study of Siliguri city Indian smart grid pilot is discussed to validate the potential and aptness of the presented approach and suggest better technology alternatives as replacements. Being field data-driven, the presented optimization approach is simple, customizable, strategic, and re-usable with practical efficacy to assist decision-making.
M. P. Bhandari and K. Bhattrai, “Institutional Architecture For Sustain-
able Development (SD): A Case Study from Bangladesh, India, Nepal,
and Pakistan,” Socioecon. Challenges, vol. 1, no. 3, pp. 6–21, 2017.
R. T. Devereaux, “Unplugging the Grid: Energy Surety via Wireless
Power,” Strateg. Plan. Energy Environ., vol. 38, no. 2, pp. 7–16, 2018.
S. H. Kulkarni and T. R. Anil, “Renewable Energy in India—Barriers to
Wind Energy,” Strateg. Plan. Energy Environ., vol. 38, no. 2, pp. 40–69,
A. Misra, G. Venkataramani, S. Gowrishankar, E. Ayyasam, and V.
Ramalingam, “Renewable Energy Based Smart Microgrids—A Pathway
To Green Port Development,” Strateg. Plan. Energy Environ., vol. 37,
no. 2, pp. 17–32, 2017.
N. Vukovic, U. Koriugina, D. Illarionova, D. Pankratova, P. Kiseleva,
and A. Gontareva, “Towards Smart Green Cities-Analysis of Integrated
Renewable Energy Use in Smart Cities,” Strateg. Plan. Energy Environ.,
vol. 40, no. 1, pp. 75–94, 2021.
J. Bhatt and O. Jani, “Smart Grid: Energy Backbone of Smart City and
e-Democracy,” in E-Democracy for Smart Cities, Springer Singapore,
, pp. 319–366.
National Smart Grid Mission (NSGM), “SG Projects |National Smart
Grid Mission, Ministry of Power, Government of India, Siliguri, West
Bengal,” 2021. [Online]. Available: https://www.nsgm.gov.in/sg-proje
cts/WBSEDCL, West Bengal. [Accessed: 16-Jul-2021].
J. Bhatt, V. Shah, and O. Jani, “An Instrumentation Engineer’s Review
on Smart Grid: Critical Applications and Parameters,” Renew. Sustain.
Energy Rev., vol. 40, pp. 1217–1239, 2014.
Optimal Wireless Technology Selection Approach 275
P. Matouˇsek, O. Ryˇsav ́y, M. Gr ́egr, and V. Havlena, “Flow based mon-
itoring of ICS communication in the smart grid,” J. Inf. Secur. Appl.,
vol. 54, 2020.
A. E. Labrador Rivas and T. Abr ̃ao, “Faults in smart grid systems: Mon-
itoring, detection and classification,” Electr. Power Syst. Res., vol. 189,
no. May, p. 106602, 2020.
L. Das, S. Munikoti, B. Natarajan, and B. Srinivasan, “Measuring smart
grid resilience: Methods, challenges and opportunities,” Renew. Sustain.
Energy Rev., vol. 130, no. May, p. 109918, 2020.
G. Dileep, “A survey on smart grid technologies and applications,”
Renew. Energy, vol. 146, pp. 2589–2625, 2020.
D. K. Panda and S. Das, “Smart Grid Architecture Model for Control,
Optimization and Data Analytics of Future Power Networks with More
Renewable Energy,” J. Clean. Prod., p. 126877, 2021.
S. Niˇzeti ́c, P. ˇSoli ́c, D. L ́opez-de-Ipi ̃na Gonz ́alez-de-Artaza, and L.
Patrono, “Internet of Things (IoT): Opportunities, issues and challenges
towards a smart and sustainable future,” J. Clean. Prod., vol. 274, 2020.
F. E. Abrahamsen, Y. Ai, and M. Cheffena, “Communication Tech-
nologies for Smart Grid: A Comprehensive Survey,” arXiv Prepr.
arXiv2103.11657, no. March, pp. 1–26, 2021.
USA Department of Energy, “Communications Requirements of smart
grid technologies,” 2010.
M. Kuzlu, M. Pipattanasompom, and S. Rahman, “A comprehensive
review of smart grid related standards and protocols,” in ICSG 2017 –
th International Istanbul Smart Grids and Cities Congress and Fair,
, pp. 12–16.
R. H. Khan and J. Y. Khan, “A comprehensive review of the application
characteristics and traffic requirements of a smart grid communications
network,” Comput. Networks, vol. 57, no. 3, pp. 825–845, 2013.
V. C. Gungor et al., “A Survey on Smart Grid Potential Applications and
Communication Requirements,” IEEE Trans. Ind. Informatics, vol. 9,
no. 1, pp. 28–42, 2013.
M. Kuzlu, M. Pipattanasomporn, and S. Rahman, “Communication
network requirements for major smart grid applications in HAN, NAN
and WAN,” Comput. Networks, vol. 67, no. July, pp. 74–88, 2014.
K. Ahuja, B. Singh, and R. Khanna, “Network Selection in Wireless Het-
erogeneous Environment Based on Available Bandwidth Estimation,”
Recent Adv. Comput. Sci. Commun., vol. 14, no. 4, pp. 1030–1039, 2021.
J. Bhatt et al.
S. R. Salkuti, “Challenges, issues and opportunities for the development
of smart grid,” Int. J. Electr. Comput. Eng., vol. 10, no. 2, pp. 1179–1186,
O. Majeed Butt, M. Zulqarnain, and T. Majeed Butt, “Recent advance-
ment in smart grid technology: Future prospects in the electrical power
network,” Ain Shams Eng. J., vol. 12, no. 1, pp. 687–695, 2021.
V. Kouhdaragh, “Optimization of Smart Grid Communication Network
in a Het-Net Environment Using a Cost Function,” J. Telecommun.,
vol. 35, no. 1, pp. 1–8, 2016.
J. Bhatt, O. Jani, and V. S. K. V Harish, “Development of an assess-
ment tool to review Communication Technologies for Smart Grid in
India,” in 1st International Conference on Innovations in Clean Energy
Technologies (ICET-2020), 2020, pp. 1–11.
S. Banerjee, S. Mondal, P. Chatterjee, and A. K. Pramanick, “An
intercriteria correlation model for sustainable automotive body material
selection,” J. Ind. Eng. Decis. Mak., vol. 2, no. 1, pp. 8–14, 2021.
M. Kuzlu and M. Pipattanasomporn, “Assessment of communica-
tion technologies and network requirements for different smart grid
applications,” in 2013 IEEE PES Innovative Smart Grid Technologies
Conference, ISGT 2013, 2013, pp. 1–6.