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International audience Distributed Battery Energy Storage Systems, controlled either per resource or in coordination, can provide many services to the network operators. The present study emphasizes the contributions of dedicated scheduling applications in order to enhance the reliability, performance and life expectation of the storage assets, based on the Nice Grid case, a Smart Grid pilot project.

International audience Distributed Battery Energy Storage Systems, controlled either per resource or in coordination, can provide many services to the network operators. The present study emphasizes the contributions of dedicated scheduling applications in order to enhance the reliability, performance and life expectation of the storage assets, based on the Nice Grid case, a Smart Grid pilot project.

With the increase in energy of the Large Hadron Collider to a centre-of-mass energy of 13 TeV for Run 2, events with dense environments, such as in the cores of high-energy jets, became a focus for new physics searches as well as measurements of the Standard Model. These environments are characterized by charged-particle separations of the order of the tracking detectors sensor granularity. Basic track quantities are compared between 3.2 fb$^{-1}$ of data collected by the ATLAS experiment and simulation of proton-proton collisions producing high-transverse-momentum jets at a centre-of-mass energy of 13 TeV. The impact of charged-particle separations and multiplicities on the track reconstruction performance is discussed. The efficiency in the cores of jets with transverse momenta between 200 GeV and 1600 GeV is quantified using a novel, data-driven, method. The method uses the energy loss, dE/dx, to identify pixel clusters originating from two charged particles. Of the charged particles creating these clusters, the measured fraction that fail to be reconstructed is $0.061 \pm 0.006 \textrm{(stat.)} \pm 0.014 \textrm{(syst.)}$ and $0.093 \pm 0.017 \textrm{(stat.)}\pm 0.021 \textrm{(syst.)}$ for jet transverse momenta of 200-400 GeV and 1400-1600 GeV, respectively. The European physical journal / C 77(10), 673 (2017). doi:10.1140/epjc/s10052-017-5225-7 Published by Springer, Berlin

With the increase in energy of the Large Hadron Collider to a centre-of-mass energy of 13 TeV for Run 2, events with dense environments, such as in the cores of high-energy jets, became a focus for new physics searches as well as measurements of the Standard Model. These environments are characterized by charged-particle separations of the order of the tracking detectors sensor granularity. Basic track quantities are compared between 3.2 fb$^{-1}$ of data collected by the ATLAS experiment and simulation of proton-proton collisions producing high-transverse-momentum jets at a centre-of-mass energy of 13 TeV. The impact of charged-particle separations and multiplicities on the track reconstruction performance is discussed. The efficiency in the cores of jets with transverse momenta between 200 GeV and 1600 GeV is quantified using a novel, data-driven, method. The method uses the energy loss, dE/dx, to identify pixel clusters originating from two charged particles. Of the charged particles creating these clusters, the measured fraction that fail to be reconstructed is $0.061 \pm 0.006 \textrm{(stat.)} \pm 0.014 \textrm{(syst.)}$ and $0.093 \pm 0.017 \textrm{(stat.)}\pm 0.021 \textrm{(syst.)}$ for jet transverse momenta of 200-400 GeV and 1400-1600 GeV, respectively. The European physical journal / C 77(10), 673 (2017). doi:10.1140/epjc/s10052-017-5225-7 Published by Springer, Berlin