Final Report Summary - SA-WSN (Spectrum-Aware and Reliable Wireless Sensor Networks for Europe’s Future Electricity Networks and Power Systems)
Spectrum-Aware and Reliable Wireless Sensor Networks for Europe’s Future Electricity Networks and Power Systems
EU FP7 Marie Curie IRG Project (Project No: 249206, Project Acronym: SA-WSN)
Researcher: Assoc. Prof. Vehbi Cagri Gungor
Project Web Site: http://akademik.bahcesehir.edu.tr/~cgungor/sawsn.html
PUBLISHABLE SUMMARY
Project Description:
The collaborative and low-cost nature of distributed sensor networks brings significant advantages over traditional communication technologies used in today’s electric power systems. Recently, these networks have been widely recognized as a promising technology that could enhance various aspects of today’s electric power systems, including generation, transmission, and distribution, making them a vital component of the next generation Europe's electric power system, i.e. smart grid. However, harsh and complex electric power system environments pose great challenges in the reliability of wireless communications because of obstructions, node contentions, RF interference and noise. Hence, the realization of wireless sensor network-based smart grid applications requires reliable and efficient communication capabilities of the deployed sensor network.
To address this need, in this project, a Spectrum-Aware and Cross-Layer Communication framework is proposed to realize efficient sensor networking for currently designed and envisioned smart grid applications. The proposed framework uses cross-layer and cognitive spectrum-aware spectrum access techniques to achieve more efficient spectrum utilization by adapting to the availability of communication resources in electric power system environments, which varies greatly with location, time and frequency in these environments because of obstructions, node contentions, RF interference and noise. Overall, the proposed framework will enable intelligent and low-cost wireless electric power system monitoring and control systems to maintain safety, reliability, efficiency, and uptime of the next generation electric power grid in Europe.
General Project Objectives:
The main objective of this project is to lay down fundamental basis for the development of a cognitive communication protocol suite for wireless sensor networks (WSN) to realize real-world smart grid applications. With this objective in mind, the specific goals of this project are:
1. Investigation and evaluation of the current state-of-the-art WSN technologies and smart grid applications to provide a better understanding of potential advantages and research challenges, and motivate research institutions and industry to further explore this promising research and application field;
2. Development of accurate analytical models that capture the inherent uncertainties of wireless channel in different power system environments, including outdoor substations, underground transformer vaults, and indoor main power control rooms;
3. Verification of developed analytical models / protocols with an extensive set of experiments;
4. Design of spectrum-aware and cognitive WSN solutions and innovative approaches that will enable more efficient utilization of the wireless channel, thus providing researchers and end-users with building blocks to provide application-specific QoS for mission-critical smart grid applications;
5. To bridge the performance gap between sensor networking theory and smart grid applications by using an interdisciplinary research approach and collaboration with world-leading sensor networking and electric power system experts.
Description of the Main Results: The summary of our main results through our analytical work and comparative performance evaluations can be made as follows:
• The relationship between dynamics of link quality and radio hardware measurements has been identified based on extensive sets of link quality measurements on IEEE 802.15.4-compliant sensor nodes in smart grid envirionments, such as 500kV outdoor substation, main power control room and underground network transformer vaults. Our in-depth analysis on wireless link reliability shows that wireless links in smart grid are exposed to spatio-temporally varying spectrum characteristics due to electromagnetic interference, equipment noise, dynamic topology changes, and fading.
• The empirical measurements in the field have demonstrated that average link quality indicator (LQI) values provided by sensor network radio components is closely correlated with packet reception rate and can be used as a reliable metric for wireless link quality assessment during the operation of the network. Importantly, the wireless channel in different electric power system environments has been modelled using log-normal shadowing path loss model through a combination of analytical and empirical methods. We believe that this model will help the research community to develop realistic link quality models of WSNs in smart grid envirionments and further investigate and develop solutions for this promising research field.
• Our extensive comparative performance evaluations on different link quality estimators show that the link-quality estimators considering the link asymmetry, such as ETX and four-bit, show the best performance in harsh smart grid environments. This is because the ETX and four-bit consider the link asymmetry by evaluating uplink and downlink qualities in their estimation methods. Therefore, they quickly react to the changes in link qualities in the network.
• In our performance evaluations and analyses, we have observed that the signal strength of the received power decays exponentially with respect to distance in smart grid environments. In addition, for a given distance, it can show a random behavior depending on the environmental characteristics. In other words, it can greatly vary at the same distance for the same environment. Since the smart grid environment is very unstable, it is challenging to estimate link quality dynamically. It is also observed that if the log-normal shadowing standard deviation increases, the transitional region increases. It is also shown that the received signal quality decreases with increasing distance and high path loss. In addition, we have oberved that the packet reception rate (PRR) values in smart grid environments are volatile and fluctuate between 0% and 100%. The high variation in PRR values at the same distance is of course due to the unstable characteristics of the transitional region. Our analysis also reveals that the size of the transitional region in descending order is underground transformer vault (LOS), main power room (LOS), 500 kV substation (LOS), main power room (NLOS), underground transformer vault (NLOS), 500 kV substation (NLOS). Furthermore, the rate of the decrease in packet reception rates for these environments is in the reverse order of the transitional region sizes. Our analysis shows that the frame size must be kept small to mitigate the effects of the packet losses especially in harsh smart grid environments.
Expected Final Results and their Potential Impact and Use:
The potential applications of the proposed cognitive sensor network platform for smart grid span a very wide range, including automatic metering, remote power system monitoring and control, electricity fraud detection, equipment fault diagnostics, demand response, load control, and distribution automation, etc. Importantly, all these applications would lead to new products, processes and services, improving industrial efficiency and use of sustainable energy resources while providing a competitive edge for Europe in the global market place. At the same time, it would ensure the reliability of the electric power infrastructure, helping to improve the daily lives of ordinary citizens.
Overall, our research activities have resulted in 14 journal papers, 4 conference papers, 1 book chapter, 2 tutorials. Our journal papers have been published in prestigious journals, such as IEEE Transactions on Industrial Electronics (SCI, impact factor= 3.439) Industrial Electronics Magazine (SCI, impact factor= 3.758) IEEE Communications Magazine (SCI, impact factor= 3.661) Elsevier Ad Hoc Networks (SCIE, impact factor=1.592) Elsevier Computer Networks (SCIE, impact factor=1.231) IEEE Vehicular Technology Magazine (SCI, impact factor= 1.105) and as well as top notch conferences, such as IEEE ICC, IEEE CRWC and IEEE IB2COM, etc.
In summary, in this project, Dr. Gungor has executed the following activities to further strengthen the dissemination activities as well as ensure transfer of knowledge:
i) Collaborated with researchers across several academic departments in Europe through joint publications and EU projects on wireless sensor networks for smart grid applications,
ii) Gave tutorials, short, interactive seminars in international conferences and workshops,
iii) Employed graduate and undergraduate students to educate young, promising researchers in this field
iv) Taught undergraduate and graduate courses, supervised graduate students’ M.S. theses, and undergraduate senior design projects,
v) Served as a technical member in EUROGIA commission (European Union EUREKA cluster) and in organization and technical program committee member of leading workshops and serve as a reviewer for leading journals in the area, such as IEEE/ACM Transactions on Networking, IEEE Transactions on Smart Grid, IEEE Transactions on Mobile Computing, IEEE Wireless Communications, IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics, IEEE Sensors Journal, IEEE Journal on Selected Areas in Communications, IEEE Communications Magazine, EURASIP Journal on Wireless Communications and Networking, Computer Networks Journal (Elsevier), Ad Hoc Networks Journal (Elsevier).
EU FP7 Marie Curie IRG Project (Project No: 249206, Project Acronym: SA-WSN)
Researcher: Assoc. Prof. Vehbi Cagri Gungor
Project Web Site: http://akademik.bahcesehir.edu.tr/~cgungor/sawsn.html
PUBLISHABLE SUMMARY
Project Description:
The collaborative and low-cost nature of distributed sensor networks brings significant advantages over traditional communication technologies used in today’s electric power systems. Recently, these networks have been widely recognized as a promising technology that could enhance various aspects of today’s electric power systems, including generation, transmission, and distribution, making them a vital component of the next generation Europe's electric power system, i.e. smart grid. However, harsh and complex electric power system environments pose great challenges in the reliability of wireless communications because of obstructions, node contentions, RF interference and noise. Hence, the realization of wireless sensor network-based smart grid applications requires reliable and efficient communication capabilities of the deployed sensor network.
To address this need, in this project, a Spectrum-Aware and Cross-Layer Communication framework is proposed to realize efficient sensor networking for currently designed and envisioned smart grid applications. The proposed framework uses cross-layer and cognitive spectrum-aware spectrum access techniques to achieve more efficient spectrum utilization by adapting to the availability of communication resources in electric power system environments, which varies greatly with location, time and frequency in these environments because of obstructions, node contentions, RF interference and noise. Overall, the proposed framework will enable intelligent and low-cost wireless electric power system monitoring and control systems to maintain safety, reliability, efficiency, and uptime of the next generation electric power grid in Europe.
General Project Objectives:
The main objective of this project is to lay down fundamental basis for the development of a cognitive communication protocol suite for wireless sensor networks (WSN) to realize real-world smart grid applications. With this objective in mind, the specific goals of this project are:
1. Investigation and evaluation of the current state-of-the-art WSN technologies and smart grid applications to provide a better understanding of potential advantages and research challenges, and motivate research institutions and industry to further explore this promising research and application field;
2. Development of accurate analytical models that capture the inherent uncertainties of wireless channel in different power system environments, including outdoor substations, underground transformer vaults, and indoor main power control rooms;
3. Verification of developed analytical models / protocols with an extensive set of experiments;
4. Design of spectrum-aware and cognitive WSN solutions and innovative approaches that will enable more efficient utilization of the wireless channel, thus providing researchers and end-users with building blocks to provide application-specific QoS for mission-critical smart grid applications;
5. To bridge the performance gap between sensor networking theory and smart grid applications by using an interdisciplinary research approach and collaboration with world-leading sensor networking and electric power system experts.
Description of the Main Results: The summary of our main results through our analytical work and comparative performance evaluations can be made as follows:
• The relationship between dynamics of link quality and radio hardware measurements has been identified based on extensive sets of link quality measurements on IEEE 802.15.4-compliant sensor nodes in smart grid envirionments, such as 500kV outdoor substation, main power control room and underground network transformer vaults. Our in-depth analysis on wireless link reliability shows that wireless links in smart grid are exposed to spatio-temporally varying spectrum characteristics due to electromagnetic interference, equipment noise, dynamic topology changes, and fading.
• The empirical measurements in the field have demonstrated that average link quality indicator (LQI) values provided by sensor network radio components is closely correlated with packet reception rate and can be used as a reliable metric for wireless link quality assessment during the operation of the network. Importantly, the wireless channel in different electric power system environments has been modelled using log-normal shadowing path loss model through a combination of analytical and empirical methods. We believe that this model will help the research community to develop realistic link quality models of WSNs in smart grid envirionments and further investigate and develop solutions for this promising research field.
• Our extensive comparative performance evaluations on different link quality estimators show that the link-quality estimators considering the link asymmetry, such as ETX and four-bit, show the best performance in harsh smart grid environments. This is because the ETX and four-bit consider the link asymmetry by evaluating uplink and downlink qualities in their estimation methods. Therefore, they quickly react to the changes in link qualities in the network.
• In our performance evaluations and analyses, we have observed that the signal strength of the received power decays exponentially with respect to distance in smart grid environments. In addition, for a given distance, it can show a random behavior depending on the environmental characteristics. In other words, it can greatly vary at the same distance for the same environment. Since the smart grid environment is very unstable, it is challenging to estimate link quality dynamically. It is also observed that if the log-normal shadowing standard deviation increases, the transitional region increases. It is also shown that the received signal quality decreases with increasing distance and high path loss. In addition, we have oberved that the packet reception rate (PRR) values in smart grid environments are volatile and fluctuate between 0% and 100%. The high variation in PRR values at the same distance is of course due to the unstable characteristics of the transitional region. Our analysis also reveals that the size of the transitional region in descending order is underground transformer vault (LOS), main power room (LOS), 500 kV substation (LOS), main power room (NLOS), underground transformer vault (NLOS), 500 kV substation (NLOS). Furthermore, the rate of the decrease in packet reception rates for these environments is in the reverse order of the transitional region sizes. Our analysis shows that the frame size must be kept small to mitigate the effects of the packet losses especially in harsh smart grid environments.
Expected Final Results and their Potential Impact and Use:
The potential applications of the proposed cognitive sensor network platform for smart grid span a very wide range, including automatic metering, remote power system monitoring and control, electricity fraud detection, equipment fault diagnostics, demand response, load control, and distribution automation, etc. Importantly, all these applications would lead to new products, processes and services, improving industrial efficiency and use of sustainable energy resources while providing a competitive edge for Europe in the global market place. At the same time, it would ensure the reliability of the electric power infrastructure, helping to improve the daily lives of ordinary citizens.
Overall, our research activities have resulted in 14 journal papers, 4 conference papers, 1 book chapter, 2 tutorials. Our journal papers have been published in prestigious journals, such as IEEE Transactions on Industrial Electronics (SCI, impact factor= 3.439) Industrial Electronics Magazine (SCI, impact factor= 3.758) IEEE Communications Magazine (SCI, impact factor= 3.661) Elsevier Ad Hoc Networks (SCIE, impact factor=1.592) Elsevier Computer Networks (SCIE, impact factor=1.231) IEEE Vehicular Technology Magazine (SCI, impact factor= 1.105) and as well as top notch conferences, such as IEEE ICC, IEEE CRWC and IEEE IB2COM, etc.
In summary, in this project, Dr. Gungor has executed the following activities to further strengthen the dissemination activities as well as ensure transfer of knowledge:
i) Collaborated with researchers across several academic departments in Europe through joint publications and EU projects on wireless sensor networks for smart grid applications,
ii) Gave tutorials, short, interactive seminars in international conferences and workshops,
iii) Employed graduate and undergraduate students to educate young, promising researchers in this field
iv) Taught undergraduate and graduate courses, supervised graduate students’ M.S. theses, and undergraduate senior design projects,
v) Served as a technical member in EUROGIA commission (European Union EUREKA cluster) and in organization and technical program committee member of leading workshops and serve as a reviewer for leading journals in the area, such as IEEE/ACM Transactions on Networking, IEEE Transactions on Smart Grid, IEEE Transactions on Mobile Computing, IEEE Wireless Communications, IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics, IEEE Sensors Journal, IEEE Journal on Selected Areas in Communications, IEEE Communications Magazine, EURASIP Journal on Wireless Communications and Networking, Computer Networks Journal (Elsevier), Ad Hoc Networks Journal (Elsevier).