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Advances in Smart Grid
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Advances in Smart Grid

A topical collection in Sensors (ISSN 1424-8220). This collection belongs to the section "Intelligent Sensors".

Viewed by 3635

Editors

Dr. Naveen Chilamkurti

E-Mail Website
Collection Editor
Department of Computer Science and Information Technology, La Trobe University, Melbourne, VIC 3086, Australia
Interests: network security; CPS; sensor network; IoT; AI-based information processing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jong-Hyouk Lee

E-Mail Website
Collection Editor
Department of Computer and Information Security, Sejong University, Seoul 05006, Korea
Interests: security; blockchain; mobility management

Topical Collection Information

Dear Colleagues,

Recent technological trends such as in communications, big data, smart infrastructure and business economics have transformed our social environment. The increased connectedness between people, processes, data, and things, which defines the Internet of Everything (IoE), is revolutionizing the way utility companies monitor, control, and distribute energy over the electrical grid. With the help of the infor­mation and communication infrastructure, the smart grid enables the collection and process­ing of huge amounts of energy-related data.

The enhanced smart grid features and privileges have resulted in a larger surface for cyber­attacks, enabling the remote exploitation of these smart devices without the need for physical access. Given these considerations, specific topics of interest for this Collection include:

  • Advances in information and communication technologies in cyberphysical systems—data analytics, AI, big data, machine learning, etc.
  • Privacy and security of advanced metering in smart grids
  • Energy-aware applications and hardware in smart grids
  • Smart management of energy storage and distributed energy resources in smart grids
  • Smart metering, real-time pricing, and demand—response in smart grids
  • Dynamic load forecasting modeling and simulation
  • Secure and reliable integration of IoT in smart grids
  • Micro-grid and renewal energy resources in Smart Grids
  • Self-healing technologies for Smart Grid
  • Prosumer based energy management in Smart Grid
  • Big Data and Data management in Smart Grid
  • Security and privacy in Smart Grid
  • AI and ML based solutions for security in Smart Grid
  • Deep learning and Federated learning-based security in Smart Grid

Prof. Dr. Naveen Chilamkurti
Prof. Dr. Jong-Hyouk Lee 
Collection Editors

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Published Papers (2 papers)

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2023

24 pages, 10146 KiB  
Article
Small-Signal Stability Analysis and MOSMA-Based Optimization Control Strategy of OWF with MMC-HVDC Grid Connection
by Jie Zheng, Hui Li, Bo Zhang and Qinghe Li
Sensors 2024, 24(1), 139; https://doi.org/10.3390/s24010139 - 26 Dec 2023
Viewed by 526
Abstract
The recent oscillation events in offshore wind farms (OWFs) connected via a modular multilevel-converter-based HVDC (MMC-HVDC) system are developing towards a wider frequency band, which causes complex a small-signal interaction phenomenon and difficulties in the stability analysis and control. In this paper, the [...] Read more.
The recent oscillation events in offshore wind farms (OWFs) connected via a modular multilevel-converter-based HVDC (MMC-HVDC) system are developing towards a wider frequency band, which causes complex a small-signal interaction phenomenon and difficulties in the stability analysis and control. In this paper, the wideband dynamic interaction mechanism is investigated based on the impedance analysis method and an improved control strategy using an optimization algorithm is proposed to improve the small-signal stability and reduce the oscillation risks. First, the detailed impedance models of the grid-connected system are established considering the distribution characteristics of the submarine cable, control delay and frequency coupling effect. Then, combined with the active damping control method, the wideband resonance mechanism is analyzed, and the stability constraints of controller parameters are obtained using the impedance stability criterion. Finally, an improved multi-objective slime mold algorithm (MOSMA)-based coordinated optimization control strategy is proposed to enhance the adaptability of the controller parameters and the wideband damping ability of a grid-connected system, which can improve the wideband stability of the system. The simulation and experimental results verify the proposed control strategy. Full article
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21 pages, 3347 KiB  
Article
Detection of False Data Injection Attacks in Smart Grids Based on Expectation Maximization
by Pengfei Hu, Wengen Gao, Yunfei Li, Minghui Wu, Feng Hua and Lina Qiao
Sensors 2023, 23(3), 1683; https://doi.org/10.3390/s23031683 - 03 Feb 2023
Cited by 3 | Viewed by 2425
Abstract
The secure operation of smart grids is closely linked to state estimates that accurately reflect the physical characteristics of the grid. However, well-designed false data injection attacks (FDIAs) can manipulate the process of state estimation by injecting malicious data into the measurement data [...] Read more.
The secure operation of smart grids is closely linked to state estimates that accurately reflect the physical characteristics of the grid. However, well-designed false data injection attacks (FDIAs) can manipulate the process of state estimation by injecting malicious data into the measurement data while bypassing the detection of the security system, ultimately causing the results of state estimation to deviate from secure values. Since FDIAs tampering with the measurement data of some buses will lead to error offset, this paper proposes an attack-detection algorithm based on statistical learning according to the different characteristic parameters of measurement error before and after tampering. In order to detect and classify false data from the measurement data, in this paper, we report the model establishment and estimation of error parameters for the tampered measurement data by combining the the k-means++ algorithm with the expectation maximization (EM) algorithm. At the same time, we located and recorded the bus that the attacker attempted to tamper with. In order to verify the feasibility of the algorithm proposed in this paper, the IEEE 5-bus standard test system and the IEEE 14-bus standard test system were used for simulation analysis. Numerical examples demonstrate that the combined use of the two algorithms can decrease the detection time to less than 0.011883 s and correctly locate the false data with a probability of more than 95%. Full article
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