Energy
The paper is aimed at an investigation of the effects of the mover eccentricity on the PM eddy current loss of tubular-linear synchronous machines (T-LSMs) equipped with quasi-Halbach magnetized PMs. The study is initiated by an analytical prediction of the no-load spatial repartition of the flux density taking into account the non-coaxiality of the mover and stator, and its validation by a 3D finite element analysis (FEA). Then a special attention is paid to an analytical formulation of the PM eddy current loss in presence of eccentricity.
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Behavioral traits for 115 employees in public buildings, namely sensitivity to personal comfort loss, desire for conformance to social norms, desire for teaming, desire for rewards. Data has been collected in the pilot studies of H2020 ChArGED for gamified energy conservation in public buildings (grant agreement no. 696170).
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The purpose of distribution network reconfiguration (DNR) is to determine the optimal topology of an electricity distribution network, which is an efficient measure to reduce network power losses. Electricity load demand and photovoltaic (PV) output are uncertain and vary with time of day, and will affect the optimal network topology. Single-hour deterministic DNR is incapable of handling this uncertainty and variability. Therefore, this paper proposes to solve a multi-hour stochastic DNR (SDNR).
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Four groups of wind speed series
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A new dataset to prepare for a new project
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This data includes a 24-hour monitoring zero-sequence voltage and current. The first four inputs are phase voltages and neutral voltage. The next three inputs are three-phase currents. The last input is the zero-sequence current, measured with 4 turns in primary.
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Dataset consists of various open GIS data from the Netherlands as Population Cores, Neighbhourhoods, Land Use, Neighbourhoods, Energy Atlas, OpenStreetMaps, openchargemap and charging stations. The data was transformed for buffers with 350m around each charging stations. The response variable is binary popularity of a charging pool.
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Attempts to prevent invasion of marine biofouling on marine vessels are demanding. By developing a system to detect marine fouling on vessels in an early stage of fouling is a viable solution. However, there is a lack of database for fouling images for performing image processing and machine learning algorithm.
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