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Cyber-Physical Power and Energy Systems with Wireless Sensor Networks: A Systematic Review

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Abstract

Power grids are among the primary targets for exploitation by cyber-attacks. Modern power and energy systems are controlled and monitored by a network of electrical and communication devices for reliability improvement and resilience enhancement. To increase the capability of remote control and monitoring, Wireless Sensor Networks (WSNs) are widely employed in modern power and energy systems. WSNs, as the foundation of Internet-of-Things (IoT), act as the essential enabling technologies for Cyber-Physical Power and Energy Systems (CPPES). Despite the benefits of WSNs in power and energy systems, such as high efficiency and low deployment costs, their security is a major challenge. In this paper, a systematic review of applications, challenges, and standards of WSNs in CPPES is presented, and various theoretical solutions are discussed. Finally, recommendations for future research are provided.

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  • 15 April 2023

    The abstract section has been updated.

References

  1. Farooq H et al (2014) Choices available for implementing smart grid communication network. In: 2014 international conference on computer and information science

  2. Feng Z et al (2011) Study on smart grid communications system based on new generation wireless technology. In: 2011 international conference on electronics, communications and control

  3. Fang X et al (2012) Smart grid-the new and improved power grid: a survey. IEEE Comms Surv Tutor 14(4):944–980

    Google Scholar 

  4. Fan Z et al (2013) Smart grid communications: overview of research challenges, solutions, and standardization activities. IEEE Comms Surv Tutor 15(1):21–38

    Google Scholar 

  5. Mohammadi F (2021) Emerging challenges in smart grid cybersecurity enhancement: a review. Energies 14:1380

    Google Scholar 

  6. Mohammadi F, Saif M et al (2022) A review of cyber–resilient smart grid. In: 2022 World Automation Congress (WAC)

  7. Jian PC (2015) Trends in smart power grid communication and networking. In: 2015 international conference on signal processing and communication

  8. Mohammadi F et al (2019) A fast fault detection and identification approach in power distribution systems. In: 2019 International conference on power generation systems and renewable energy technologies

  9. Giustina DD et al (2015) Hybrid communication network for the smart grid: validation of a field test experience. IEEE Trans Power Deliv 30(6):2492–2500

    Google Scholar 

  10. Goel N et al (2015) Smart grid networks: a state of the art review. In: 2015 international conference on signal processing and communication

  11. Mulla A et al (2015) The wireless technologies for smart grid communication: a review. In: 2015 5th international conference on communication systems and network technologies

  12. Kuzlu M et al (2015) Review of communication technologies for smart homes/building applications. In: 2015 IEEE innovative smart grid technologies-Asia

  13. Musleh AS et al (2019) A prediction algorithm to enhance grid resilience toward cyber attacks in WAMCS applications. IEEE Syst J 13(1):710–719

    Google Scholar 

  14. Parvez I et al (2014) Frequency band for HAN and NAN communication in smart grid. In: 2014 IEEE symposium on computational intelligence applications in smart grid

  15. Hiew Y-K et al (2014) Performance of cognitive smart grid communication in home area network. In: 2014 IEEE 2nd international symposium on telecommunications technologies

  16. Aalamifar F et al (2012) Viability of powerline communication for the smart grid. In: 2012 26th Biennial Symp Comms

  17. Hartmann T et al (2014) Generating realistic smart grid communication topologies based on real-data. In: 2014 IEEE Int Conf Smart Grid Comms

  18. Parikh PP et al (2010) Opportunities and challenges of wireless communication technologies for smart grid applications. In: IEEE PES general meeting

  19. Yan Y et al (2013) A survey on smart grid communication infrastructures: motivations, requirements and challenges. IEEE Comms Surv Tutor 15(1):5–20

    Google Scholar 

  20. Saputro N et al (2012) A survey of routing protocols for smart grid communications. Comput Netw 56(11):2742–2771

    Google Scholar 

  21. Gungor VC et al (2013) A survey on smart grid potential applications and communication requirements. IEEE Trans Ind Inform 9(1):28–42

    Google Scholar 

  22. Erol-Kantarci M et al (2011) Wireless multimedia sensor and actor networks for the next generation power grid. Ad Hoc Netw 9(4):542–551

    Google Scholar 

  23. Isa NBM et al (2015) Smart grid technology: communications, power electronics and control system. In: 2015 international conference on sustainable energy engineering and application

  24. Gungor VC et al (2011) Smart grid technologies: communication technologies and standards. IEEE Trans Ind Inform 7(4):529–539

    Google Scholar 

  25. Amin R et al (2012) Smart grid communication using next generation heterogeneous wireless networks. In: 2012 IEEE 3rd international conference on smart grid communications

  26. Bera S et al (2014) Energy-efficient smart metering for green smart grid communication. In: 2014 IEEE global communications conference

  27. Batista NC et al (2014) Layered smart grid architecture approach and field tests by ZigBee technology. Energy Convers Manag 88:49–59

    Google Scholar 

  28. Käbisch S et al (2010) Interconnections and communications of electric vehicles and smart grids. In: 2010 1st IEEE international conference on smart grid communications

  29. Wang B et al (2012) Intelligent DC microgrid with smart grid communications: control strategy consideration and design. IEEE Trans Smart Grid 3(4):2148–2156

    Google Scholar 

  30. Elkhorchani H et al (2013) Development of communication architecture for intelligent energy networks. In: 2013 international conference on electrical engineering and software applications

  31. Elkhorchani H et al (2014) Smart micro grid power with wireless communication architecture. In: 2014 international conference on electrical sciences and technologies in Maghreb

  32. Barroso S (2022) Towards a cyber-physical system for sustainable and smart building: a use case for optimising water consumption on a SmartCampus. J Ambient Intell Humaniz Comput

  33. Darwish A et al (2017) Cyber physical systems design, methodology, and integration: the current status and future outlook. J Ambient Intell Humaniz Comput

  34. Elarabi T et al (2015) Design and simulation of state-of-art Zigbee transmitter for IoT wireless devices. In: 2015 IEEE international symposium on signal processing and information technology

  35. Mohammadi F, Nazri G-A et al (2020) An improved droop-based control strategy for MT-HVDC systems. Electronics 9(1):87

    Google Scholar 

  36. Mohammadi F, Mohammadi-Ivatloo B et al (2021) Robust control strategies for microgrids: a review. IEEE Syst J PP(99):1–12

    Google Scholar 

  37. Mohammadi F, Nazri G-A et al (2020) An improved mixed AC/DC power flow algorithm in hybrid AC/DC grids with MT-HVDC systems. Appl Sci 10(1):297

    Google Scholar 

  38. Abdollahi A et al (2020) Optimal power flow incorporating FACTS devices and stochastic wind power generation using Krill Herd algorithm. Electronics 9:1043

    Google Scholar 

  39. Moradzadeh A et al (2020) Short-term load forecasting of microgrid via hybrid support vector regression and long short-term memory algorithms. Sustainability 12(17):7076

    Google Scholar 

  40. Nguyen TT et al (2020) Optimal scheduling of large-scale wind-hydro-thermal systems with fixed-head short-term model. Appl Sci 10(8):2964

    Google Scholar 

  41. Mohammadi F, Nguyen TT (2020) Optimal placement of TCSC for congestion management and power loss reduction using multi-objective genetic algorithm. Sustainability 12(7):2813

    Google Scholar 

  42. Shojaei AH et al (2020) Multi-objective optimal reactive power planning under load demand and wind power generation uncertainties using ε-constraint method. Appl Sci 10(8):2859

    Google Scholar 

  43. Mohammadi F, Rouzbehi K et al (2021) HVDC circuit breakers: a comprehensive review. IEEE Trans Power Electron 36(12):13726–13739

    Google Scholar 

  44. Moradzadeh A et al (2021) Locating inter-turn faults in transformer windings using isometric feature mapping of frequency response traces. IEEE Trans Ind Inform PP(99):1–1

    Google Scholar 

  45. Elahi O et al (2022) Diagnosing disk-space variation in distribution power transformer windings using group method of data handling artificial neural networks. Energies 15(23):8885

    Google Scholar 

  46. Garcia-Hernandez J (2015) Recent progress in the implementation of AMI projects: standards and communications technologies. In: 2015 International conference on mechatronics, electronics and automotive engineering

  47. Kour R et al (2020) Predictive model for multistage cyber-attack simulation. Int J Syst Assur Eng Manag 11:600–613

    Google Scholar 

  48. Li XX et al (2018) A cloud-terminal-based cyber-physical system architecture for energy efficient machining process optimization. J Ambient Intell Humaniz Comput 10:1

    Google Scholar 

  49. Mohammadi F et al (2019) A real-time cloud-based intelligent car parking system for smart cities. In: 2019 2nd IEEE international conference information communication signal processing

  50. Line MB et al (2011) Cyber security challenges in smart grids. In: 2011 2nd IEEE PES international conference and exhibition on innovative smart grid technologies

  51. Yan Y et al (2012) A survey on cyber security for smart grid communications. IEEE Comms Surv Tutor 14(4):5–20

    MathSciNet  Google Scholar 

  52. Jahan S et al (2015) An analysis of smart grid communication infrastructure & cyber security in smart grid. In: 2015 International conference on advances in electrical engineering

  53. Dzung D et al (2005) Security for industrial communication systems. Proc IEEE 93(6):1152–1172

    Google Scholar 

  54. Jameel F (2016) Network security challenges in smart grid. In: 2016 19th international multi-topic conference

  55. Lee E-K et al (2012) Physical layer security in wireless smart grid. IEEE Comms Mag 50(8):90–97

    Google Scholar 

  56. Wang W et al (2013) Cyber security in the smart grid: survey and challenges. Comp Netw 57(5):1344–1371

    Google Scholar 

  57. Shapsough S et al (2015) Smart grid cyber security: challenges and solutions. In: 2015 international conference on smart grid and clean energy technologies

  58. Saponara S et al (2012) Network architecture, security issues, and hardware implementation of a home area network for smart grid. J Comput Netw Comms 2012

  59. Hahn A et al (2013) Cyber-physical security testbeds: architecture, application, and evaluation for smart grid. IEEE Trans Smart Grid 4(2):847–855

    Google Scholar 

  60. Monshi MM et al (2013) A study on the efficient wireless sensor networks for operation monitoring and control in smart grid applications. In: 2013 Proceedings of IEEE Southeastcon

  61. Gungor VC et al (2010) Opportunities and challenges of wireless sensor networks in smart grid. IEEE Trans Ind Electron 57(10):3557

    Google Scholar 

  62. Brak ME, Brak SE, Essaaidi M, Benhaddou D (2014) Wireless sensor network applications in smart grid. In: 2014 International renewable and sustainable energy conference

  63. Zhang Y et al (2012) Wireless sensor network in smart grid: applications and issue. In: 2012 world congress on information and communication technologies

  64. Mohammadi F et al (2020) Emerging issues and challenges with the integration of solar power plants into power systems. In: Solar energy conversion in communities–Springer proceedings in energy. Springer, Cham

  65. Amjad S et al (2010) Review of design considerations and technological challenges for successful development and deployment of plug-in hybrid electric vehicles. Renew Sust Energy Rev 14(3):1104–1110

    Google Scholar 

  66. Gibbons PB et al (2003) IrisNet: an architecture for a worldwide sensor web. IEEE Pervasive Comput 2(4):22–33

    Google Scholar 

  67. Moodley D et al (2006) A new architecture for the sensor web: the SWAP-framework. In: 5th international semantic web conference

  68. Martinez-Sandoval R et al (2014) A comprehensive WSN-based approach to efficiently manage a smart grid. Sensors 14(10):18748–18783

    Google Scholar 

  69. Namboodiri V et al (2014) Toward a secure wireless-based home area network for metering in smart grids. IEEE Systems J 8(2):509–520

    Google Scholar 

  70. Kumar A et al (2021) Cyber physical systems-reliability modelling: critical perspective and its impact. Int J Syst Assur Eng Manag 12:1334–1347

    Google Scholar 

  71. Mishra A et al (2022) Emerging technologies and design aspects of next generation cyber physical system with a smart city application perspective. Int J Syst Assur Eng Manag

  72. Mohammadi F et al (2019) A bidirectional power charging control strategy for plug-in hybrid electric vehicles. Sustainability 11(16):4317

    Google Scholar 

  73. Kim KJ et al (2010) Energy scavenging for energy efficiency in networks and applications. Bell Labs Tech J 15(2):62–72

    Google Scholar 

  74. Sallabi FM et al (2014) Evaluation of ZigBee wireless sensor networks under high power disturbances. IEEE Trans Power Deliv 29(1):13–20

    Google Scholar 

  75. Brak ME et al (2014) Wireless sensor network applications in smart grid. In: 2014 international renewable and sustainable energy conference

  76. Erol-Kantarci M et al (2010) Using wireless sensor networks for energy-aware homes in smart grids. In: The IEEE symposium on computer and communications

  77. Mohammadi F, Rashidzadeh R (2021) An overview of IoT-enabled monitoring and control systems for electric vehicles. IEEE Instrum Meas Mag 24:91–97

    Google Scholar 

  78. Mohammadi F, Rashidzadeh R (2022) Impact of stealthy false data injection attacks on power flow of power transmission lines—a mathematical verification. Int J Electr Power Energy Syst 142:108293

    Google Scholar 

  79. Sadeghian O et al (2022) Protecting power transmission systems against intelligent physical attacks: a critical systematic review. Sustainability 14(19):12345

    Google Scholar 

  80. Brak ME et al (2012) Wireless sensor network in smart grid technology: challenges and opportunities. In: 2012 6th Int. Conf. Sci. Electron., Tech. Info. Telecom.

  81. Mahmood A et al (2015) A review of wireless communications for smart grid. Renew Sust Energy Rev 41:248–260

    Google Scholar 

  82. Do TT et al (2022) A direct reinforcement learning approach for nonautonomous thermoacoustic generator. Math Probl Eng 2022

  83. Ji X-P et al (2020) Optimal attack strategy selection of an autonomous cyber-physical micro-grid based on attack-defense game model. J Ambient Intell Humaniz Comput

  84. Oliveira L et al (2019) MAC layer protocols for internet of things: a survey. Future Internet 11(1):16

    Google Scholar 

  85. Krishnamurthy L et al (2005) Design and deployment of industrial sensor networks: experiences from a semiconductor plant and the North Sea. In: 3rd international conference on embedded networked sensor

  86. Horvath P et al (2015) Efficient evaluation of wireless real-time control networks. Sensors 15(2):4134–4153

    Google Scholar 

  87. Rodenas-Herraiz D et al (2013) Current trends in wireless mesh sensor networks: a review of competing approaches. Sensors 13(5):5958–5995

    Google Scholar 

  88. Kumar S et al. (2022) Sensor network driven novel hybrid model based on feature selection and SVR to predict indoor temperature for energy consumption optimisation in smart buildings. Int J Syst Assur Eng Manag

  89. S. Han, et al (2011) Reliable and real-time communication in industrial wireless mesh networks. In: 2011 17th IEEE real-time and embedded technology and applications symposium

  90. Lu Z et al (2010) Review and evaluation of security threats on the communication networks in the smart grid. In: 2010 IEEE international military communications conference

  91. Dini G et al (2013) On simulative analysis of attack impact in wireless sensor networks. In: 2013 IEEE 18th conference on emerging technologies & factory automation

  92. Radmand P et al. (2010) Taxonomy of wireless sensor network cyber security attacks in the oil and gas industries. In: 2010 24th IEEE international conference on advanced information networking and applications

  93. Jithish J et al (2020) A decision-centric approach for secure and energy-efficient cyber-physical systems. J Ambient Intell Humaniz Comput

  94. Mahmood A et al (2014) Threats in end to end commercial deployments of wireless sensor networks and their cross layer solution. In: 2014 conference on information assurance and cyber security

  95. Barsocchi P et al (2011) A cyber-physical approach to secret key generation in smart environments. J Ambient Intell Humaniz Comput

  96. Neogy S (2015) Security management in wireless sensor networks. In: 2015 international conference on cyber situational awareness, data analytics and assessment

  97. Agrawal S et al (2019) Detection of node capture attack in wireless sensor networks. IEEE Syst J 13(1):238–247

    Google Scholar 

  98. Padmavathi G et al (2009) A survey of attacks, security mechanisms and challenges in wireless sensor networks. Int J Comput Sci Inf Sec 4(1–2):15

    Google Scholar 

  99. Yasir Malik M (2013) An outline of security in wireless sensor networks: threats, countermeasures and implementations. In: Wireless sensor networks and energy efficiency: protocols, routing and management

  100. Shukla J et al (2013) Security threats and defense approaches in wireless sensor networks: an overview. Int J Appl Innov Eng Manag 2:3

    Google Scholar 

  101. Nguyen HL et al (2008) A study of different types of attacks on multicast in mobile ad hoc networks. Ad Hoc Netw 6(1):32–46

    Google Scholar 

  102. Chowdhury M et al (2013) Security issues in wireless sensor networks: a survey. Int J Future Gen Comms Netw 6(5):97–116

    Google Scholar 

  103. Riaz MN et al (2018) Classification of attacks on wireless sensor networks: a survey. Int J Wirel Microw Techn 8(6):15–39

    MathSciNet  Google Scholar 

  104. Desnitsky VA et al (2020) Neural network based classification of attacks on wireless sensor networks. In: 2020 IEEE conference of Russian young researchers in electrical and electronic engineering

  105. Lupu T-G (2009) Main types of attacks in wireless sensor networks. Recent Adv Sig Syst 5:1–9

    Google Scholar 

  106. Karlof C et al (2003) Secure routing in wireless sensor networks: attacks and countermeasures. Ad Hoc Netw 1(2–3):293–315

    Google Scholar 

  107. Sinha P et al (2017) Security vulnerabilities, attacks and countermeasures in wireless sensor networks at various layers of OSI reference model: a survey. In: 2017 international conference on communication and signal processing

  108. Chen X et al (2009) Sensor network security: a survey. IEEE Comms Surv Tutor 11(2):52–73

    Google Scholar 

  109. Mohammadi S et al (2011) A comparison of link layer attacks on wireless sensor networks. Int J Appl Graph Theory Wirel Ad Hoc Netw Sens Netw 3(1):69–84

    MathSciNet  Google Scholar 

  110. Can O et al (2015) A survey of intrusion detection systems in wireless sensor networks. In: 2015 6th international conference on modeling, simulation, and applied optimization

  111. Rajkumar VBA et al (2014) Security attacks and its countermeasures in wireless sensor networks. Int J Eng Res Apps 4(10):4–15

    Google Scholar 

  112. Tamil K et al (2010) Security vulnerabilities in wireless sensor networks: a survey. J Inf Assur Sec 5(1):31–44

    Google Scholar 

  113. Butun I et al (2014) A survey of intrusion detection systems in wireless sensor networks. IEEE Commun Surv Tutor 16(1):4–30

    Google Scholar 

  114. Granjal J et al (2015) Security for the internet of things: a survey of existing protocols and open research issues. IEEE Comms Surv Tutor 17(3):1294–1312

    Google Scholar 

  115. Diaz A et al (1932) Simulation of attacks for security in wireless sensor network. Sensors 16(11):2016

    Google Scholar 

  116. Sun C-C et al (2016) Cyber-physical system security of a power grid: state-of-the-art. Electronics 5(3):40

    Google Scholar 

  117. Wang Y et al (2016) Detection of intelligent intruders in wireless sensor networks. Future Internet 8(1):2

    Google Scholar 

  118. Chelli K (2015) Security issues in wireless sensor networks: attacks and countermeasures. In: Proceedings of world congress on engineering, vol 1

  119. Zhang Y et al (2015) A network topology control and identity authentication protocol with support for movable sensor nodes. Sensors 15(12):29958–29969

    Google Scholar 

  120. Di Pietro R et al (2004) Connectivity properties of secure wireless sensor networks. In: 2nd ACM workshop sec. ad‐hoc and sensor network

  121. Di Pietro R et al (2008) Redoubtable sensor networks. ACM Trans Inf Syst Sec

  122. Yagan O (2012) Performance of the Eschenauer-Gligor key distribution scheme under an ON/OFF channel. IEEE Trans Inf Theory 58(6):3821–3835

    MathSciNet  MATH  Google Scholar 

  123. Jutla CS (2001) Encryption modes with almost free message integrity. International conference on the theory and applications of cryptographic techniques

  124. Blackburn SR et al (2008) Connectivity of the uniform random intersection graph. Discrete Math 309(16):5130–5140

    MathSciNet  MATH  Google Scholar 

  125. Bloznelis M (2013) Degree and clustering coefficient in sparse random intersection graphs. Ann Appl Probab 23(3):1254–1289

    MathSciNet  MATH  Google Scholar 

  126. Krishnan BS et al (2013) On connectivity thresholds in superposition of random key graphs on random geometric graphs. In: 2013 IEEE international symposium on information theory

  127. Krzywdziński K et al (2012) Geometric graphs with randomly deleted edges—connectivity and routing protocols. In: International symposium on mathematical foundations of computer science

  128. Ahmed M et al (2009) NIDS: a network based approach to intrusion detection and prevention. In: 2009 international association of computer science and information technology

  129. Yousufi RM et al (2017) A network-based intrusion detection and prevention system with multi-mode counteractions. In: 2017 International conference on innovations in information, embedded and communication systems

  130. Wattanapongsakorn N et al (2012) A practical network-based intrusion detection and prevention system. In: 2012 IEEE 11th international conference on trust, security and privacy in computing and communications

  131. Zhang L et al (2016) A survey on security and privacy in emerging sensor networks: from viewpoint of close-loop. Sensors 16(4):443

    Google Scholar 

  132. Salehian S et al (2012) Energy-efficient intrusion detection in wireless sensor network. In: 2012 international conference on cyber security, cyber warfare and digital forensic

  133. Farraj A et al (2016) A game-theoretic analysis of cyber switching attacks and mitigation in smart grid systems. IEEE Trans Smart Grid 7(4):1846–1855

    Google Scholar 

  134. Ten C-W et al (2010) Cybersecurity for critical infrastructures: attack and defense modeling. IEEE Trans Syst Man Cybernet Part A Syst Hum 40(4):17

    Google Scholar 

  135. Darwish I et al (2015) Experimental and theoretical modeling of DNP3 attacks in smart grids. In: 2015 36th IEEE Sarnoff symposium

  136. Patil A et al (2022) Data-driven approaches for impending fault detection of industrial systems: a review. Int J Syst Assur Eng Manag

  137. Albashear AMM et al (2018) Detection of man-in-the-middle attacks by using the TCP retransmission timeout: key compromise impersonation attack as study case. In: 2018 international conference computing, control, electrical, electronics engineering

  138. Yang X et al (2017) Toward a Gaussian-mixture model-based detection scheme against data integrity attacks in the smart grid. IEEE Internet Things J 4(1):674

    Google Scholar 

  139. Zhou Y et al (2019) Robust energy-efficient resource allocation for IoT-powered cyber-physical-social smart systems with virtualization. IEEE Internet Things J 6(2):2413–2426

    Google Scholar 

  140. Li F et al (2019) System statistics learning-based IoT security: feasibility and suitability. IEEE Internet Things J 6(4):6396–6403

    Google Scholar 

  141. Tian J et al (2021) TOTAL: optimal protection strategy against perfect and imperfect false data injection attacks on power grid cyber–physical systems. IEEE Internet Things J 8(2):1001–1015

    MathSciNet  Google Scholar 

  142. Zou T et al (2020) Smart grids cyber-physical security: Parameter correction model against unbalanced false data injection attacks. Electr Power Syst Res 187:99

    Google Scholar 

  143. Rivas AEL et al (2020) Faults in smart grid systems: Monitoring, detection and classification. Electr Power Syst Res 189:106602

    Google Scholar 

  144. Bowker D et al (2020) The role of Blockchain technologies in power markets. In: CIGRE WG C5.30 Technical Brochure

  145. Mohammadi F, Sanjari M et al (2022) A real-time Blockchain-based state estimation system for battery energy storage systems. In: 2022 IEEE Kansas power and energy conference (KPEC)

  146. Mohammadi F, Sanjari M et al (2022) A real-time Blockchain-based multifunctional integrated smart metering system. In: 2022 IEEE Kansas Power and Energy Conference (KPEC)

  147. Bowker D et al (2022) The applications of Blockchain technologies to electricity markets. In: CIGRE session

  148. Mohammadi F, Saif M (2023) Blockchain technology in modern power systems: a systematic review. IEEE Syst Man Cybernet Mag

  149. Bowker D et al (2023) Trading electricity with Blockchain systems. In: CIGRE WG C5.33 Technical Brochure

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Authors and Affiliations

  1. Power System Optimization Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, 700000, Vietnam

    Thang Trung Nguyen

  2. Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, N9B 1K3, Canada

    Fazel Mohammadi

  3. Electrical and Computer Engineering and Computer Science Department, University of New Haven, West Haven, CT, 06516, USA

    Fazel Mohammadi

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  1. Thang Trung Nguyen
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The authors confirm contributions to the paper as follows: TTN was responsible for conceptualization, review and editing; and FM was responsible for conceptualization, methodology, formal analysis and investigation, collecting resources, data analysis, writing—original draft preparation, and writing—review and editing. Both authors have read and agreed to the current version of the manuscript. Both authors have read and agreed to the current version of the manuscript.

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Nguyen, T.T., Mohammadi, F. Cyber-Physical Power and Energy Systems with Wireless Sensor Networks: A Systematic Review. J. Electr. Eng. Technol. 18, 4353–4365 (2023). https://doi.org/10.1007/s42835-023-01482-3

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