The Role of Wireless Sensor Networks for Pervasive Smart Grids Communication

Written by Viktoriya Mostova and Alfredo Vaccaro

The increasing focus on environmental sustainability has given a lot of attention to the way energy is generated, managed, and consumed, which is also of particular importance for power systems operation and planning. In this context, the design of modern electrical grids has to tackle several challenges, which include the growing demand for electricity and the consequent need to expand the transmission network, the increase in distributed generation and the need to be located closest to load centres, the obsolescence of the current electricity networks, the adequate management of grid congestions, and the need to reconcile the availability of resources according to system reliability and cost efficiency [1].

Among the emerging solutions to address these problems, a number of ideas can be distinguished that can be grouped under the term ”smart grid,” which indicates a technical infrastructure that combines pervasive sensor systems [2], high-speed two-way communications [3], adaptive control, monitoring and protective systems [4], with the goal of improving the resiliency and efficiency of power systems, enhancing the grid flexibility, and supporting the large-scale integration of renewable energy generators and electric vehicles.

The key point of the smart grid paradigm, both from a structural and operational point of view, is the presence of a pervasive and reliable communication network through which different devices can interact with each other [5]. To achieve this goal, the use of Wireless Sensor Networks (WSNs) has been recognized as one of the most promising enabling technologies for developing reliable communication services without the need for implementing complex or costly infrastructures. Indeed, the advantages of WSNs include ease of access to remote sites, large area coverage, absence of leasing costs, and adaptability to changing network topology [6], while the potential disadvantages include uncertainties in quality of service and time delays. However, continuous technological improvements have led WSNs performance comparable to other conventional communication systems [7] [8], supporting their deployment in various smart grid applications, ranging from building automation, decentralized control and pervasive monitoring.

The IEC 61850 Standard

In this context of supporting pervasive monitoring, IEC 61850 represents a valuable standard for integrating WSNs with substation automation components, by defining technical specifications, communication requirements, and functional characteristics. In particular, this standard identifies the enabling factors that WSNs-based communication systems should satisfy in order to effectively support Smart Grid functions:

  1. Flexibility, to allow the WSNs to adapt to the future topological developments of the power grid.
  2. Performance, mainly in terms of the quality of service, and ability to meet the protection and control time requirements.
  3. Reliability, since the communication services provided by the WSNs could be used to support critical applications.

Satisfying these requirements allows effectively deploying WSNs-based communication systems in both generation and distribution monitoring and control, getting a set of potential advantages, which include:

  • Low-cost hardware: wireless communication units can be integrated even in the simplest devices.
  • Fault detection and pervasive communication: by installing WSN-based smart sensors on critical devices, it is possible to pervasively monitor the power components operations, thus promptly detecting and reacting to faults and disturbances, which could trigger cascade events.
  • High network scalability: thousands of devices (transformers, tap changers, breakers, power quality sensors, transformer temperature sensors, breaker position indicators, etc.) can be effectively monitored, all communicating with each other.
  • Pervasive data sharing: the acquired data can be shared to all sensor networks, allowing both utilities and consumers to extract valuable information about the demand power profiles, real-time energy prices, and actual/predicted grid operation states.



To maximize the benefits bought to practical smart city operation scenario, several open issues should be addressed, which include:

  • Enhance sensor robustness to harsh environmental conditions: the sensors are subject to RF interference as well as humidity, dust, or vibration levels that can affect their performance.
  • Improve computing resources: sensor computing affects three main resources, namely energy, memory, and data processing.
  • Information security and privacy issues:  the smart grid can be subjected to external cyberattacks, which can result in loss of confidential information, or in generating large-scale blackouts.

All these issues should be properly addressed in designing reliable WSNs for smart grid communication, by considering all the possible impacts on correct grid operation, and analyzing the technological risks, security standards, and cyber-vulnerabilities involved in the use of the WSN technology.




  1. D. G. Vyas, N. Trivedi, V. Pandya, P. Bhatt, and A. Pujara, “Future challenges and issues in evolution of the smart grid and recommended possible solutions,” in 2019 IEEE 16th India Council International Conference (INDICON), 2019, pp. 1–4.
  2. M. EL Brak, S. EL Brak, M. Essaaidi, and D. Benhaddou, “Wireless sensor network applications in smart grid,” in 2014 International Renewable and Sustainable Energy Conference (IRSEC), 2014, pp. 587–592.
  3. V. Madani, A. Vaccaro, D. Villacci, and R. L. King, “Satellite based communication network for large scale power system applications,” in 2007 iREP Symposium-Bulk Power System Dynamics and Control-VII. Revitalizing Operational Reliability. IEEE, 2007, pp. 1–7.
  4. S. Ullo, A. Vaccaro, and G. Velotto, “Performance analysis of ieee 802.15. 4 based sensor networks for smart grids communications,” Journal of Electrical Engineering: Theory and Application, vol. 1, no. 3, pp. 129–134, 2010.
  5. E. Y. Song, G. J. FitzPatrick, K. B. Lee, and E. Griffor, “A methodology for modeling interoperability of smart sensors in smart grids,” IEEE Transactions on Smart Grid, vol. 13, no. 1, pp. 555–563, 2022.
  6. A. Alhariry, S. Brown, D. Eshenbaugh, N. Whitt, and A. F. Browne, “A survey of sensing methodologies in smart grids,” in SoutheastCon 2021, 2021, pp. 1–5.
  7.  M. Alonso, H. Amaris, D. Alcala, and D. M. Florez R., “Smart sensors for smart grid reliability,” Sensors, vol. 20, no. 8, 2020. [Online]. Available:
  8. A. Yarali, Wireless Sensors/IoT and Artificial Intelligence for Smart Grid and Smart Home, 2022, pp. 239–249.




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Mostova 1
Viktoriya Mostova received a Bachelor’s degree in energy engineering from the University of Sannio, Benevento, Italy, where she is currently a M.Sc. student.
Alfredo Vaccaro
Alfredo Vaccaro received a M.Sc. (Hons.) degree in electronic engineering from the University of Salerno, Salerno, Italy, and a Ph.D. degree in electrical and computer engineering from the University of Waterloo, Waterloo, ON, Canada. From 1999 to 2002, he was an Assistant Researcher with the Department of Electrical and Electronic Engineering, University of Salerno. From March 2002 to October 2015, he was an Assistant Professor of electric power systems with the Department of Engineering, University of Sannio, Benevento, Italy. He is currently an Associate Professor of electrical power systems at the same school. His research interests include soft computing and interval-based methods for uncertain power system analysis, and decentralized architectures for smart grids computing.

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