Power and Energy
This dataset contains daily maximum load data with the average demand, customer count and PV capacity at two substations Arkana and Muchea, Western Australia used in the accepted IEEE Transactions on Power Systemspaper titled “The Use of Extreme Value Theory for Forecasting Long-Term Substation Maximum Electricity Demand” by Li and Jones (2019). The dataset spans from 01/01/2008 to 30/06/2022, part history (01/01/2008 to 16/09/2018) and part forecast (17/09/2018 to 30/06/2022). The dataset is beneficial to various research such as long-term load forecast.
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The LCL filter design procedure presented here is similar to that presented in references [1] and [2]. Here, the procedure is presented in a step-by-step way and the simulation file is freely available on http://busarello.prof.ufsc.br/
[1] Teodorescu, R. ; Liserre, M. ; Rodriguez, P. . Grid Converters for Photovoltaic and Wind Power Systems. 2011, Wiley.
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The DFT and FFT are used mainly to obtain the amplitude of a harmonic component from a periodic signal containing several harmonics. For instance, it is desired to know the 180 Hz harmonic amplitude from a signal. Then, the DFT and FFT are the best choices to do that.
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It is often the case that the frequency response data of a system or a network is available and one wants to identify a linear equivalent from the frequency response data for time-domain simulations and other purposes. To this end, a variety of methods have been proposed, and the vector fitting (VF) method and the frequency-partitioning fitting (FpF) method are often used for electromagnetic transient (EMT) simulations of power systems.
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This real-life current signal was acquired from a wind generator.
The nominal fundamental frequency of the system is 60 Hz.
The sampling rate is 7.680 kHz, which corresponds to 128 samples per fundamental cycle.
The magnitude is given in amperes (A). The length of the signal is approximately one hour (3640 s).
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This dataset includes gathering 18-month raw PV data at time intervals of about 200 µs (5 kHz sampling). A post-processing 365-day day-by-day downsampled version, converted to 10 ms intervals (100 Hz sampling), is also included. The end results are two databases: 1. The original, raw, data, including both fast (short circuit, 200 µs) and slow (sweep, 2.5-3.9 s) information for 18 months. These show intervals of missing points, but are provided to allow potential users to reproduce any new work. 2.
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This DATASET serves as a contemporary benchmark data set for solving multiple (or all) real-valued solutions for algebraic power flow problems. When this DATASET was originally created in 2019, it contained a huge collection of real-valued power flow solutions (up to dozens of thousands for some cases) for five standard IEEE test cases, i.e.
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This dataset lets the users to rapidally estimate electric generator size, mass and losses for given power requirement, speed and DC bus voltage.This is accomplished through the metamodeling of a normalized optimization based machine design framework. The method is applied to a permanent magnet ac machine. This work is developed using the paper Metamodeling of Rotating Electric Machinery published in IEEE Transactions on Energy Conversion.
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This report outlines the derivation of the first-, second-, and third-order Taylor series expansions of the power flow solution; it is the Electronic Companion of the following paper:
R. A. Jabr, “High-order approximate power flow solutions and circular arithmetic applications,” IEEE Transactions on Power Systems, vol. 34, no. 6, pp. 5053-5062, November 2019.
The derivation is carried out in complex variables via the use of Wirtinger calculus.
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