Future Wireless Communication Technologies for Smart Grids: A LPWAN Prospective

By G. Pradeep Reddy, Y. V. Pavan Kumar

The modern smart grid initiatives support interoperability of local/onsite micro-power grids which are normally located in vicinity of each other as opposed to the macro-power grids. Hence, effective communication technologies play a very crucial role in collecting data and transferring control centre decisions for desired operation from the grid management view. Figure 1 shows several wireless technologies used in smart grid development [1]. Among these, LPWAN (Low-Power Wide-Area Network) are suitable for interoperability of local micro-power grids since the information exchange is typically in the order of few bytes. The LPWAN is a wide-area wireless communication network typically meant for long range communications with low data rate and low power consumption. This article describes a few key technologies used for LPWAN such as Sigfox, Narrowband-Internet of Things (NB-IoT) and LoRa (Long Range). These new technologies can be used to establish an effective communication between micro or macro power grids which operate on different bandwidths and at different distances.

Various wireless communication technologies

Fig. 1. Various wireless communication technologies

Description of Sigfox Technology

Sigfox is a network provider currently providing services to more than 70 countries. Within the Sigfox network, each device can send and receive messages daily. The typical connectivity of Sigfox network is illustrated in Fig. 2. Sigfox uses Ultra Narrow Band technology [3] and lightweight protocols for maximum battery life. The payload for uplink is 0 to 12 bytes. The number of bytes used depends on type of information being transferred. Downlink payload is 0 to 8 bytes. The data generated from energy meters is sent to the Sigfox cloud via Sigfox base stations. Sigfox cloud is the interface between the network and the user. Its functionalities include serving messages and providing services such as data storage, analytics, predictions, alerts, etc., based on user requirements.

Sigfox network scenarioFig. 2. Sigfox network scenario

Description of NB-IoT Technology

NB-IoT shown in Fig. 3 is a mobile network designed for the Internet of Things developed by the 3rd Generation Partnership Project (3GPP) standard. It can be built on top of any existing cellular network. With the present cellular network, it is possible to send a high volume of data with high speed, but it consumes high power. Whereas, with NB-IoT, it is only possible to send less volume of data with lower speed, but at lower cost, and longer battery life. Further, it works in a licenced spectrum, thereby, the interference is low when compared with technologies operating in an unlicensed band. The frame format of NB-IoT is same as that of LTE. There are three modes of operation: Standalone operation, In-band operation, and Guard band operation [4]. Each energy meter which is enabled with NB-IoT services will send data to the Cloud via pre-installed core network. The data is made available on the application server, where user can access it easily for performing specific analysis.

NB-IoT network scenario

Fig. 3. NB-IoT network scenario

Description of LoRa Technology

LoRa technology is developed by Semtech for long-range communications. It works in ISM (Industrial, Scientific and Medical) band specific to different countries. The LoRa is available at two layers PHY (LoRa Radio) and MAC (LoRaWAN). LoRa end nodes (radios) are connected to the gateway in a star-of-stars topology manner as shown in Fig. 4. There are three types of LoRaWAN specifications available, namely Class A, Class B, and Class C [5]. LoRa offers a spreading factor of 7-12 and bandwidth of 125 kHz, 250 kHz or 500 kHz that can be chosen as per the user requirement. Each energy meter connected with a LoRa radio sends data to the gateway. This gateway sends the data to the cloud where it is made available to the user and for further processing.

LoRaWAN network scenario

Fig. 4. LoRaWAN network scenario


The cumulative summary with critical factors [2] is given in Table. I. NB-IoT and Sigfox need service from network provider whereas LoRa network can be established by an individual. Based on the application (micro or macro power grid), one among these technologies can be chosen.

Table I: Comparison of Typical Parameters of Sigfox, NB-IoT, and LoRa Technologies

Performance Factor

Sigfox Technology

NB-IoT Technology

LoRa Technology





Frequency Band

ISM band

Licensed Band

ISM band

Max. Data Rate

100 bps/ 600 bps




By operator

By operator

Individual can install






Sigfox in collaboration with ETSI (European Telecommunications Standards Institute)






  1. Y. Li, X. Cheng, Y. Cao, D. Wang, L. Yang, “Smart choice for the smart grid: narrowband internet of things (NB-IoT),” IEEE Internet of Things Journal, Vol. 5, No. 3, pp. 1505-1515, 2018.
  2. M. Kais, B. Eddy, C. Frederic, M. Fernand, “A comparative study of LPWAN technologies for large-scale IoT deployment,” ICT Express, Vol. 5, No. 1, pp. 1-7, 2019.
  3. Sigfox, https://www.sigfox.com/en/what-sigfox/technology, last accessed on 06 July 2020.
  4. C.B. Mwakwata, H. Malik, M.M. Alam, L.Y. Moullec, S. Parand, S. Mumtaz, “Narrowband internet of things (NB-IoT): From physical (PHY) and media access control (MAC) layers perspectives,” Sensors, Vol. 19, No. 11, 2019.
  5. Thethingsnetwork, https://www.thethingsnetwork.org/docs/lorawan/classes.html, last accessed on 06 July 2020.


This article edited by Jose Medina

For a downloadable copy of August 2020 eNewsletter which includes this article, please visit the IEEE Smart Grid Resource Center.

G. Pradeep Reddy
G. Pradeep Reddy received the M.Tech. degree with specialization in Communication Engineering in the year 2010 from Vellore Institute of Technology (VIT), Vellore, India, and the B.Tech. degree in Electronics and Communication Engineering in the year 2007 from JNTU Hyderabad University, India. He is currently pursuing PhD degree at VIT-AP University. He has an overall experience of 10 years of teaching. His research areas include Smart Grids, Machine Learning, IoT and Ultra-Wideband (UWB) Communications. He has published several research papers in international journals and conferences.
Y.V. Pavan Kumar
Y.V. Pavan Kumar received the Ph.D. degree in Electrical Engineering in the year 2018 from Indian Institute of Technology Hyderabad (IITH), India; the M.Tech. degree in Instrumentation and Control Systems in the year 2011 from JNTU Kakinada University, India; and the B.Tech. degree in Electrical and Electronics Engineering in the year 2007 from JNTU Hyderabad University, India. He has an overall experience of 7.5 years in both industry and academia. Currently, he is working as an Associate Professor in the School of Electronics Engineering at VIT-AP University, Amaravati, India. His research areas include advanced control systems and artificial intelligence applications to microgrids and smart grids, self-healing grids, power quality, and power converters. He has authored 85 research papers for various reputed Journal/Conferences, 3 books, 3 innovation disclosures. He is an Invited Member of IEEE Smart Grid R & D Committee and Reviewer for many IEEE, Elsevier, Springer, etc., Journals/Conferences.

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