CLASH: the concentration-mass relation of galaxy clusters

J Merten, M Meneghetti, M Postman… - The Astrophysical …, 2015 - iopscience.iop.org
We present a new determination of the concentration–mass (c–M) relation for galaxy
clusters based on our comprehensive lensing analysis of 19 X-ray selected galaxy clusters …

Predictive segmentation of energy consumers

A Albert, M Maasoumy - Applied energy, 2016 - Elsevier
This paper proposes a predictive segmentation technique for identifying sub-groups in a
large population that are both homogeneous with respect to certain patterns in customer …

Joint energy procurement and demand response towards optimal deployment of renewables

X Cao, J Zhang, HV Poor - IEEE Journal of Selected Topics in …, 2018 - ieeexplore.ieee.org
In this paper, joint energy procurement and demand response is studied from the
perspective of the operator of a power system. The operator procures energy from both …

Consistent use of Type Ia Supernovae highly magnified by galaxy clusters to constrain the cosmological parameters

A Zitrin, M Redlich, T Broadhurst - The Astrophysical Journal, 2014 - iopscience.iop.org
ABSTRACT We discuss how Type Ia supernovae (SNe) strongly magnified by foreground
galaxy clusters should be self-consistently treated when used in samples fitted for the …

[PDF][PDF] Benchmarking big data technologies for energy procurement efficiency

M Fritz, S Albrecht, H Ziekow, J Strüker - 2017 - researchgate.net
The electrical power industry is undergoing radical change due to the push for renewable
energy that makes energy supply less predictable. Smart meters along with analytics …

[图书][B] New insights into peculiar thermonuclear supernovae and line of sight effects in gravitational lensing

C McCully - 2014 - search.proquest.com
Abstract Type Ia supernovae (SNe Ia) and gravitational lensing are important cosmological
probes, but both are limited by theoretical, systematic uncertainties. One key uncertainty in …

[引用][C] Development of prediction models of day-ahead hourly building electricity consumption and peak power demand using the machine learning method

D Si, A Aziz, B Lasternas - International Journal of Energy and Power Engineering, 2017

[引用][C] Minimizing Cost Sharing Among Residential Electric Customers with Solar and Storage

M Levine, A Sun, Z Zhang