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Regional non-intrusive electric vehicle monitoring based on graph signal processing

Electricity network is leading to a low carbon future with high penetration of plug-in electric vehicles (EVs). However, it is extraordinarily difficult to acquire detailed information on regional EV electrification with an...

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Regional non-intrusive electric vehicle monitoring based on graph signal processing

Electricity network is leading to a low carbon future with high penetration of plug-in electric vehicles (EVs). However, it is extraordinarily difficult to acquire detailed information on regional EV electrification with an...

Published by:
Economic planning of electric vehicle charging stations considering traffic constraints and load profile templates

This paper develops a novel solution to integrate electric vehicles and optimally determine the siting and sizing of charging stations (CSs), considering the interactions between power and transportation industries. Firstly...

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Economic planning of electric vehicle charging stations considering traffic constraints and load profile templates

This paper develops a novel solution to integrate electric vehicles and optimally determine the siting and sizing of charging stations (CSs), considering the interactions between power and transportation industries. Firstly...

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Model Order Reduction for Reliability Assessment of Flexible Power Networks
Model order reduction (MOR) has demonstrated its robustness and wide applicability in simulating large-scale mathematical models in the engineering research domain. In this paper, MOR techniques are applied to quantify relevant...
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Model Order Reduction for Reliability Assessment of Flexible Power Networks
Model order reduction (MOR) has demonstrated its robustness and wide applicability in simulating large-scale mathematical models in the engineering research domain. In this paper, MOR techniques are applied to quantify relevant...
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Revealing the Drag Instability in One-fluid Nonideal Magnetohydrodynamic Simulations of a 1D Isothermal C-shock
PG Gu, CY Chen, E Shen, CC Yen, MK Lin
Aug 19, 2022
Abstract C-type shocks are believed to be ubiquitous in turbulent molecular clouds thanks to ambipolar diffusion. We investigate whether the drag instability in 1D isothermal...
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A Novel Closed-Loop Clustering Method for Hierarchical Load Forecasting
Chi Zhang, Ran Li
Jan 31, 2021
Hierarchical load forecasting (HLF) is an approach to generate forecasts for hierarchical loadtime series. The performance of HLF can be improved by optimizing the forecasting model and the hierarchical structure. Previous...
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YouIdiot.com
Mark Y. Herring
Jan 01, 0001
While researching something else, I ran across an item in a business journal my eye ran across another item. In research this is called serendipity, something we do not hear so much about any more these days.
Published by: Winthrop University
Load Characterization and Low-order Approximation for Smart Metering Data in the Spectral Domain
Smart metering data are providing new opportunities for various energy analyses at household level. However traditional load analyses based on time-series techniques are challenged due to the irregular patterns and large volume...
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Reading Is, Like, You Know, Sooooo Gross!
Mark Y. Herring
Jan 01, 0001
"Huge Decline in Book Reading" ran one headline. "Cultural Atrophy!" read another. "Study Links Drop in Test Scores to a Decline Spent in Reading" ran one for the "Duh!" award. "Americans are Closing the Book on Reading" said...
Published by: Winthrop University
Student Body Selects CSL Leadership for 2019-20
Winthrop University
Jan 01, 0001
HIGHLIGHTS Approximately 1,132 students voted in the March election, with only 16 votes separating Belton and Jackson from the runners-up. The pair ran on the platform "Be More," which will focus on cross-collaboration between...
Published by: Winthrop University
A Novel Closed-Loop Clustering Method for Hierarchical Load Forecasting
Chi Zhang, Ran Li
Jan 31, 2021
Hierarchical load forecasting (HLF) is an approach to generate forecasts for hierarchical loadtime series. The performance of HLF can be improved by optimizing the forecasting model and the hierarchical structure. Previous...
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Deep Learning for Household Load Forecasting – A Novel Pooling Deep RNN
Heng Shi, Minghao Xu, Ran Li
Sep 30, 2018
The key challenge for household load forecasting lies in the high volatility and uncertainty of load profiles. Traditional methods tend to avoid such uncertainty by load aggregation (to offset uncertainties), customer...
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Utility-Scale Estimation of Additional Reinforcement Cost from 3-Phase Imbalance Considering Thermal Constraints
Kang Ma, Ran Li, Furong Li
Sep 01, 2017
Widespread three-phase imbalance causes inefficient uses of low voltage (LV) network assets, leading to additional reinforcement costs (ARCs). Previous work that assumed balanced three phases underestimated the reinforcement...
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