Smart grid
This dataset contains synthetic smart meter data with simulated cyber attacks, designed to support research in anomaly detection, cybersecurity, and energy consumption analysis. The dataset is based on 159 users from the Smart Meters in London dataset, selected for their regular consumption patterns. This larger dataset can be found in
https://www.kaggle.com/datasets/jeanmidev/smart-meters-in-london,
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This paper provides a comprehensive evaluation of the BESS's optimum size targets, limitations, methodology, benefits and disadvantages. Furthermore, energy storage technologies and improved application targets have been presented and discussed for greater clarity. This study focuses primarily on BESS deployments, methodologies, and environmental impact. BEES innovations and achievements for electrical networks are also compared to other energy storage technologies. Concerns and obstacles are discussed to offer researchers in BESS a comprehensive picture.
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The current paper examines and highlights the numerous energy storage system (ESS) technologies used in microgrids, as well as their architectures, configurations, performances, benefits, and drawbacks, also by providing a tangible outline for prospective efficient and sustainable ESS. As a result, there is also a comparison of the various technologies. As a consequence, there is also a comparison of the different technologies. Finally, some of the present ESS concerns and difficulties are explored.
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Smart grid, an application of Internet of Things (IoT) is modern power grid that encompasses power and communication network from generation to utilization. Home Area Network (HAN), Field or Neighborhood Area Network (FAN/NAN) and Wide Area network (NAN) using Wireless LAN and Wireless/Wired WAN protocols are employed from generation to utilization . Advanced Metering Infrastructure, a utilization side infrastructure facilitates communication between smart meters and the server where energy efficient protocols are mandate to support smart grid .
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With the continuous expansion of grid nodes, traditional centralized methods exhibit certain limitations in the amount of communication data and computational cost for state estimation. In the past few decades, distributed state estimation has been fully developed in Multi-area Power Systems (SG). According to different regions or electrical equipment, the SG is divided into several regional nodes, and each node can estimate the entire state of the SG through local sensor measurement information and neighbor state estimation information.
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The Advanced Metering Infrastructure is established in Electrical Drives Laboratory, School of Electrical and Electronics Engineering, SASTRA Deemed to be University, Thanjavur, Tamil Nadu,India. Further, the ARP spoofing attack emulation is deliberated between Smart Meter and Data Concentrator through the Ettercap tool in two different test beds by incorporating Modbus TCP/IP and MQTT.Then, the benign and malicious traffic patterns of two protocols are captured using Wireshark to form the dataset.
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692 Views