Power and Energy
Modern power systems face growing risks from cyber-physical attacks, necessitating enhanced resilience due to their societal function as critical infrastructures. The challenge is that defense of large-scale systems-of-systems requires scalability in their threat and risk assessment environment for cyber-physical analysis including cyber-informed transmission planning, decision-making, and intrusion response. Hence, we present a scalable discrete event simulation tool for analysis of energy systems, called DESTinE.
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A significant portion of the end users of electricity consists of residential consumers, often exceeding that of other consumer categories, particularly in developing countries. Effective demand side management strategies increasingly rely on Artificial Intelligence (AI) and Machine Learning (ML), yet their success depends on access to high-quality, comprehensive datasets.
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58 Views
State-space representation is a practical, efficient and reliable way to evaluate the high-frequency interaction of a transformer with the power network under different types of disturbances. Currently, this representation is available in commercial electromagnetic transient programs; however, this important tool is not yet implemented in the alternative transient program ATP. This paper describes the implementation methodology of the state-space model of the power transformer in ATP using the Norton type-94 component and foreign models.
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The measurements in this study were carried out at Xidian University's north campus in China. The building density and height in this area are typical of urban environments, and there are fewer uncertainties that could affect the experimental results. Figure shows an aerial view of the measurement environment, including the chosen Tx and Rx locations. Centered at each receiver, a square with a side length 15 times the wavelength of the transmitted signal was constructed. The receiving antenna was moved inside each square following the path shown in the figure.
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This dataset presents the captures of data packets in Wireshark for the scalability analysis of the Process Bus in Digital Substations based on the traffic of Sampled Values, through connection in redundant local area networks (LAN A and LAN B). LAN A is a 100 Mbps network that is saturated close to 10 Sampled Values suscriptions, while LAN B is a 1Gbps network that is not saturated and is used as a reference for the loss of data packets in each case. Emulated SV data is provided by software and a laboratory signal injector.
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130 Views
This dataset contains 70,176 records with data from 2021 - 01 - 11 onwards. It features eight columns including `date`, `pressure`, `humidity`, etc. The `date` is in datetime format, while others are of float type. These data likely relate to environmental factors and photovoltaic real - power, enabling studies on photovoltaic performance and its influencing elements.
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30 Views
With the increasing uncertainties introduced by intermittent renewable energy sources, as a critical decision-making tool for power system operations, security-constrained unit commitment (SCUC) provides an efficient solution for economically and robustly responding to the changes in the power system operating state. In this study, a graph reinforcement learning (GRL)-based approach is proposed to address the day-ahead SCUC problem, incorporating alternating current (AC) power flow constraints.
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38 Views
This video shows the experiments of full power transfer of a new CP-TFQP magnetic topology. Power transfer is demonstrated at 50 kW, when the system is both fully aligned and misaligned. The proposed system operates at consistent efficiency, with a lower input dc bus range compared to traditional systems. The TFQP topology is the main contribution, and comprises four coils, built in only three layers.
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22 Views
Dual active bridge (DAB) converter is an important converter for electric vehicles, energy storage systems. Data sets are introduced to control the DC-DC power control. Triple phase-shift of DAB is controlled by the range of zero voltage switching. Optimal switching to reduce high current stress DC-DC converter is In presented data sets are used with python program to execute the different stages of machine learning. Performance of all stages are well addressed each data output file.
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31 ViewsDual active bridge (DAB) converter is an important converter for electric vehicles, energy storage systems. Data sets are introduced to control the DC-DC power control. Triple phase-shift of DAB is controlled by the range of zero voltage switching. Optimal switching to reduce high current stress DC-DC converter is In presented data sets are used with python program to execute the different stages of machine learning. Performance of all stages are well addressed each data output file.
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17 Views