Electric Utility
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The data for PVs and loads are sourced from “Multi-agent reinforcement learning for active voltage control on power distribution networks”, collected from Jan. 1 st, 2012 to Dec. 31 st, 2014 over a 3-minute interval. In this paper, the data is described as follows:
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The data for PVs and loads are sourced from “Multi-agent reinforcement learning for active voltage control on power distribution networks”, collected from Jan. 1 st, 2012 to Dec. 31 st, 2014 over a 3-minute interval. In this paper, the data is described as follows:
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The recent developments in the field of the Internet of Things (IoT) bring alongside them quite a few advantages. Examples include real-time condition monitoring, remote control and operation and sometimes even remote fault remediation. Still, despite bringing invaluable benefits, IoT-enriched entities inherently suffer from security and privacy issues. This is partially due to the utilization of insecure communication protocols such as the Open Charge Point Protocol (OCPP) 1.6. OCPP 1.6 is an application-layer communication protocol used for managing electric vehicle chargers.
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It contains genuine user feedback on electric bikes, gathered through comments shared by customers after purchasing and using an electric vehicle (EV). These comments provide valuable insights into the user experience, highlighting aspects such as performance, convenience, challenges, and satisfaction levels. This information is particularly useful for conducting sentiment analysis to understand customer emotions, preferences, and concerns.
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This dataset supports the manuscript titled “Strategies for Mitigating Degradation of Medium Voltage Electrical Equipment in Harsh Saline Environments.” The study focuses on identifying and addressing the challenges faced by medium voltage equipment in coastal environments characterized by high salinity, humidity, and extreme weather conditions. The dataset includes:
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We establish topological and parametric conditions under which phase angles across three identical impedances can be balanced with small-signal stability guarantees when served from three single-phase sources executing active-power frequency droop control. All standard topologies involving Delta and Wye interconnections of sources and loads are examined.
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Following a series of unusual transmission system disturbances involving unexpected IBR behaviors, there has been a significant need for monitoring, control, and protection functions that can help system operators more rapidly understand and respond to these disturbances. The IBR-rich transmission system datakit (IRTSD) is focused on transient disturbances in IBR-rich transmission systems and consists of a dataset, power system model, and automation scripting.
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The given data contains the results from laboratory trials related to the paper "Optimizing Congestion Management andEnhancing Resilience in Low-Voltage Grids Using OPF and MPC Control Algorithms Through Edge Computing and IEC 61850 Standards" currently in publication in IEEE Access.
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This repository contains the datasets produced using different data generation strategies to train data driven models (e.g., decision trees, gradient tree boosting, and deep neural networks), and to evaluate their performances. The data generation strategies are described, and the results are presented in the conference paper: "Training Data Generation Strategies for Data-driven Security Assessment of Low Voltage Smart Grids" J. Cuenca, E. Aldea, E. Le Guern-Dall'o, R. Féraud, G. Camilleri, and A. Blavette. IEEE ISGT EU 2024, Dubrovnik, Croatia, Oct 2024.
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