Power and Energy

This dataset contains high-resolution solar and wind measurement data collected from the Feni region, Bangladesh, spanning from 2017 to 2019. Logged at a 1-minute interval, the dataset provides a comprehensive record of atmospheric and meteorological conditions, essential for renewable energy analysis, climatological studies, and resource assessment.

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This dataset contains high-resolution wind measurement data collected from 22 channels at varying heights, providing valuable insights for wind energy assessment, atmospheric research, and meteorological studies. The dataset includes wind speed, wind direction, and environmental parameters measured at multiple altitudes ranging from 10m to 120m. Each channel records parameters such as average wind speed, standard deviation, minimum and maximum values, gust speed, and wind vane direction. Additionally, atmospheric parameters such as temperature, relative humidity, and pressure are included.

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Clean energy technologies, encompassing renewable resources like solar, wind, and hydropower, are essential in the global effort to reduce greenhouse gas emissions and combat climate change. As the globe prepares to transition away from fossil fuels, understanding the factors and parameters influencing the penetration of clean energy into existing energy markets has become a critical step. Controversies surrounding the environmental impacts of renewable technologies, variability in market structures, and economic pressures on clean energy companies can complicate this transition.

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All three datasets are in CSV file format and contain renewable energy and load demand data from August 1, 2024 to August 30, 2024. The dataset is sourced from California ISO and is stored through an open-source repository https://github.com/gridstatus/gridstatus. Renewable energy sources include wind and solar energy, and the load demand is based on data from the Trinity Public Utility District (TIDC) and the Trook Irrigation District (TPWR).

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The power generated by electricity industry is presently concentrating on the mitigation of power quality (PQ) difficulties. Numerous PQ issues are brought about by automation in industry andthe integration of distributedgeneration using powerelectronic converters this calls for PQ enhancement. This contributes to the equipment'sextendedlifespanandincreasedependabilityofsupplies for feeding vital loads into the system. Electric power transmission efficiency from the source to industrial, home, and commercial consumersis measured byPQ.

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In this study, we propose a type of single-phase simplified split-source single-stage DC-to-AC boost inverter topology with the capabilities of providing continuous constant input and output power flow with low input current ripple. These features are crucial for increased efficiency during the inverter’s interface between the PV source and the load, particularly for maximum power point tracking (MPPT) applications.

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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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271 Views

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