Power and Energy
Where one can find videos about the innovative algorithms and experimental procedures of this paper. The algorithm files contain both the MATLAB version and the Code Composer Studio (CCS) version. In the video, here is the permanent magnet synchronous motor control platform used in the study.
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Ionic wind has shown promising applications in many fields, but it still encounters the challenges of low wind velocity and high discharge voltage. Here we propose a method of enhancing the velocity of ionic wind at given discharge voltages by Joule-heating the discharge electrode in a wire-grid corona discharge scheme.
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Dataset from UCI contains the electricity consumption (in kWh) of 320 customers every 15 minutes from 2011 to 2014. For some customers, their electricity consumption data was recorded starting from a different time, and the data before the first record was marked as 0. As training model requires a starting point for the time series, and different customers have different starting times, some features remain 0 before a certain time point. Using all the data for training would inevitably have a negative impact. Therefore, the data from 2011 is removed and set the starti
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This dataset contains simulation results for the research article "Reserve Provision from Electric Vehicles: Aggregate Boundaries and Stochastic Model Predictive Control". Each CSV file corresponds to an experimental setup with a certain number of EVs included in the fleet and the risk-aversion determined by the risk-aversion factor Ω.
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The evolution of the power grid is progressively shifting towards a much more dynamic and complex system. Generation sources that are more decentralized and reliant on inverter-based technologies, plus increasing demand for electrification of new types of loads are introducing more challenges to grid stability. Grid operators must adapt, requiring more extensive, granular, and timely data to enable analytics for improved efficiency and development of proactive mitigation strategies.
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This dataset was used for the capacity planing of ahybrid solar PV-small hydro power plant located in Buseruka, Hoima District in Uganda. The data consitss of four files namely:
1. 20240601_GenerationStatisticsQ1_2024-Kabalega-Hydromax: Represents power generation statistics from ERA for Kabalega/HYdromax HPP.
2. Hydrology from Buseruka HPP - 2015-2022: Represents the hydrology or river flow data in cumecs for the period 2015 to 2022 as provided by the plant operators.
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Health degradation issues in automotive power electronics converter systems (PECs) arise due to repetitive thermomechanical stress experienced during real-world vehicle operation. This stress, caused by heat generated during semiconductor operation within PECs, leads to the degradation of semiconductor's operating life. Estimating the power semiconductor junction temperature (Tj) is crucial for assessing semiconductor degradation in operation. Although physics-of-failure-based models can estimate Tj, they require substantial computational power.
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This dataset is shared for capacitor C and ESR estimation using convolution neural network. The dataset is collected in a experimental modular moultilevel converter, which includes the capacitor voltage at low and medium frequency band, and the arm current. Wavelet transform is used to transfer the time series data to images, which present the inherent data features to image patterns. In a degraded capacitor, the C decreases and the ESR increases, which result in different image patterns.
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This research presents a multi-channel phase shift inductor-inductor-capacitor (LLC) resonant converter with a wide input and output voltage range that has been specially optimized for fuel cell applications. The worst-case minimum stack voltage and the battery voltage range were used to determine the optimal parameters of the LLC converter. The voltage gain of the converter operating at a constant power was considered, and an algorithm for such a calculation is proposed.
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