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Abstract Many countries committed themselves in the Kyoto protocol to reduce greenhouse gas (GHG) emissions. Some of these targeted emission reductions could result from a switch from coal-fired to gas-fired electricity generation. The focus in this work lies on Western Europe, with the presence of the European Union Emission Trading Scheme (EU ETS). For the switching to occur, several conditions have to be fulfilled. First, an economical incentive must be present, i.e. a sufficiently high European Union Allowance (EUA) price together with a sufficiently low natural gas price. Second, the physical potential for switching must exist, i.e. at a given load, there must remain enough power plants not running to make switching possible. This paper investigates what possibilities exist for switching coal-fired plants for gas-fired plants, dependent on the load level (the latter condition above). A fixed allowance cost and a variable natural gas price are assumed. The method to address GHG emission reduction potentials is first illustrated in a methodological case. Next, the GHG emission reduction potentials are addressed for several Western European countries together with a relative positioning of their electricity generation. GHG emission reduction potentials are also compared with simulation results. GHG emission reduction potentials tend to be significant. The Netherlands have a very widespread switching zone, so GHG emission reduction is practically independent of electricity generation. Other counties, like Germany, Spain and Italy could reduce GHG emissions significantly by switching. With an allowance cost following the switch level of a 50% efficient gas-fired plant and a 40% efficient coal-fired plant in the summer season (like in 2005), the global GHG emission reduction (in the electricity generating sector) for the eight modeled zones could amount to 19%.

Anthropogenically generated underwater noise in the marine environment is ubiquitous, comprising both intense impulse and continuous noise. The installation of offshore wind farms across the North Sea has triggered a range of ecological questions regarding the impact of anthropogenically produced underwater noise on marine wildlife. Our interest is on the impact on the "passive drifters," i.e., the early life stages of fish that form the basis of fish populations and are an important prey for pelagic predators. This study deals with the impact of pile driving and operational noise generated at offshore wind farms on Dicentrarchus labrax (sea bass) larvae.

The presented article will describe an 'effect-cause' model for the purpose of simulating the energy consumption of DC fed light rail vehicles. The model will assess the advantages of hybrid vehicles in terms of energy consumption, network power and voltage variations, line current and losses; and will help sizing and designing a supercapacitor based energy storage system (ESS) for both on-board, and stationary applications. The proposed modeling needs to allow the ESS sizing according to the objective that needs to be achieved, being braking energy recovery, voltage drop compensation and peak power shaving the most common goals of ESS use in hybrid vehicles. The needed power and energy levels will vary in function of the vehicle features and the driving cycle followed. This all can be determined by the quasi-static simulation tool to ease the design process. Another objective of the modeling tool is to evaluate the behaviour of the vehicle power flow controller, which manages the power from/to the ESS in function of the state of several variables.

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).

The widespread use of optimization methods in the design phase of District Heating Networks is currently limited by the availability of scalable optimization approaches that accurately represent the network. In this paper, we compare and benchmark two different approaches to non-linear topology optimization of District Heating Networks in terms of computational cost and optimality gap. The first approach solves a mixed-integer non-linear optimization problem that resolves the binary constraints of pipe routing choices using a combinatorial optimization approach. The second approach solves a relaxed optimization problem using an adjoint optimization approach, and enforces a discrete network topology through penalization. Our benchmark shows that the relaxed penalized problem has a polynomial computational cost scaling, while the combinatorial solution scales exponentially, making it intractable for practical-sized networks. We also evaluate the optimality gap between the two approaches on two different District Heating Network optimization cases. We find that the mixed-integer approach outperforms the adjoint approach on a single-producer case, but the relaxed penalized problem is superior on a multi-producer case. Based on this study, we discuss the importance of initialization strategies for solving the optimal topology and design problem of District Heating Networks as a non-linear optimization problem.

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

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