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The electrical ageing of photovoltaic modules during extended damp-heat tests at different stress levels is investigated for three types of crystalline silicon photovoltaic modules with different backsheets, encapsulants and cell types. Deploying different stress levels allows determination of an equivalent stress dose function, which is a first step towards a lifetime prediction of devices. The derived humidity dose is used to characterise the degradation of power as well as that of the solar cell's equivalent circuit parameters calculated from measured current–voltage characteristics. An application of this to the samples demonstrates different modes in the degradation and thus enables better understanding of the module's underlying ageing mechanisms. The analysis of changes in the solar cell equivalent circuit parameters identified the primary contributors to the power degradation and distinguished the potential ageing mechanism for each types of module investigated in this paper. © 2016 The Authors. Progress in Photovoltaics: Research and Applications published by John Wiley & Sons Ltd. © 2016 The Authors. Progress in Photovoltaics: Research and Applications published by John Wiley & Sons Ltd. This work was supported in part by the European Commission under FP7 grant N° 262533 SOPHIA (INFRA-2010- 1.1.22_CP-CSA-Infra) and by the Research Councils UK (RCUK) under project ‘Stability and Performance of Photovoltaics (STAPP)’ (contract no: EP/H040331/1).

Electric water heaters have the ability to store energy in their water buffer without impacting the comfort of the end user. This feature makes them a prime candidate for residential demand response. However, the stochastic and nonlinear dynamics of electric water heaters, makes it challenging to harness their flexibility. Driven by this challenge, this paper formulates the underlying sequential decision-making problem as a Markov decision process and uses techniques from reinforcement learning. Specifically, we apply an auto-encoder network to find a compact feature representation of the sensor measurements, which helps to mitigate the curse of dimensionality. A wellknown batch reinforcement learning technique, fitted Q-iteration, is used to find a control policy, given this feature representation. In a simulation-based experiment using an electric water heater with 50 temperature sensors, the proposed method was able to achieve good policies much faster than when using the full state information. In a lab experiment, we apply fitted Q-iteration to an electric water heater with eight temperature sensors. Further reducing the state vector did not improve the results of fitted Q-iteration. The results of the lab experiment, spanning 40 days, indicate that compared to a thermostat controller, the presented approach was able to reduce the total cost of energy consumption of the electric water heater by 15%. Submitted to IEEE transaction on smart grid

AbstractMixed‐halide lead perovskites have attracted significant attention in the field of photovoltaics and other optoelectronic applications due to their promising bandgap tunability and device performance. Here, the changes in photoluminescence and photoconductance of solution‐processed triple‐cation mixed‐halide (Cs0.06MA0.15FA0.79)Pb(Br0.4I0.6)3 perovskite films (MA: methylammonium, FA: formamidinium) are studied under solar‐equivalent illumination. It is found that the illumination leads to localized surface sites of iodide‐rich perovskite intermixed with passivating PbI2 material. Time‐ and spectrally resolved photoluminescence measurements reveal that photoexcited charges efficiently transfer to the passivated iodide‐rich perovskite surface layer, leading to high local carrier densities on these sites. The carriers on this surface layer therefore recombine with a high radiative efficiency, with the photoluminescence quantum efficiency of the film under solar excitation densities increasing from 3% to over 45%. At higher excitation densities, nonradiative Auger recombination starts to dominate due to the extremely high concentration of charges on the surface layer. This work reveals new insight into phase segregation of mixed‐halide mixed‐cation perovskites, as well as routes to highly luminescent films by controlling charge density and transfer in novel device structures.

The ATLAS Inner Detector is a composite tracking system consisting of silicon pixels, silicon strips and straw tubes in a 2 T magnetic field. Its installation was completed in August 2008 and the detector took part in data- taking with single LHC beams and cosmic rays. The initial detector operation, hardware commissioning and in-situ calibrations are described. Tracking performance has been measured with 7.6 million cosmic-ray events, collected using a tracking trigger and reconstructed with modular pattern-recognition and fitting software. The intrinsic hit efficiency and tracking trigger efficiencies are close to 100%. Lorentz angle measurements for both electrons and holes, specific energy-loss calibration and transition radiation turn-on measurements have been performed. Different alignment techniques have been used to reconstruct the detector geometry. After the initial alignment, a transverse impact parameter resolution of 22.1+/-0.9 ��m and a relative momentum resolution ��p/p = (4.83+/-0.16) \times 10-4 GeV-1 \times pT have been measured for high momentum tracks. 34 pages, 25 figures