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Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security.

The paper presents a preliminary technical-economic comparison between a 3 kV DC railway and the use of trains with on-board storage systems. Numerical simulations have been carried out on a real railway line, which presents an electrified section at 3 kV DC and a non-electrified section, currently covered by diesel-powered trains. Different types of ESS have been analyzed, implementing the models in Matlab/Simulink environment. A preparatory economic investigation has been carried out.

This deliverable includes the methodology in EnergyPROSPECTS for an in-depth study of energy citizenship. It features the criteria used for selecting the cases for indepth study, the list of cases selected for in-depth study as well as key research foci and empirical research questions.

Abstract In this paper, a general mathematical model for the dynamic simulation of a single-effect LiBr/water absorption chiller is presented. The model is based on mass and energy balances applied to the internal components of the machine, and it accounts for the non-steady behaviour due to thermal and mass storage in the components. The validation of the mathematical model is performed through experimental data collected on a commercial small-capacity water-cooled unit. Due to the peculiar technology adopted in the real chiller, a special effort was made to identify the appropriate values of the main physical parameters. The validation of the model is based on the values of the water temperature at the outlet of the machine, as no measurement inside the machine was possible; anyway, a consistency analysis applied to the internal parameters is also presented. The agreement between experimental and simulated results is very good, both on a daily and on a seasonal basis.

AbstractEuropean climate is associated with variability and changes in the mid-latitude atmospheric circulation. In this study, we aim to investigate potential future change in circulation over Europe by using the EURO-CORDEX regional climate projections at 0.11° grid mesh. In particular, we analyze future change in 500-hPa geopotential height (Gph), 500-hPa wind speed and mean sea level pressure (MSLP) addressing different warming levels of 1 °C, 2 °C and 3 °C, respectively. Simple scaling with the global mean temperature change is applied to the regional climate projections for monthly mean 500-hPa Gph and 500-hPa wind speed. Results from the ensemble mean of individual models show a robust increase in 500-hPa Gph and MSLP in winter over Mediterranean and Central Europe, indicating an intensification of anticyclonic circulation. This circulation change emerges robustly in most simulations within the coming decade. There are also enhanced westerlies which transport warm and moist air to the Mediterranean and Central Europe in winter and spring. It is also clear that, models showing different responses to circulation depend very much on the global climate model ensemble member in which they are nested. For all seasons, particularly autumn, the ensemble mean is much more correlated with the end of the century than most of the individual models. In general, the emergence of a scaled pattern appears rather quickly.

Energy management within microgrids under the presence of large number of renewables such as photovoltaics is complicated due to uncertainties involved. Randomness in energy production and consumption make both the prediction and optimality of exchanges challenging. In this paper, we evaluate the impact of uncertainties on optimality of different robust energy exchange strategies. To address the problem, we present AIROBE, a data-driven system that uses machine-learning-based predictions of energy supply and demand as input to calculate robust energy exchange schedules using a multiband robust optimization approach to protect from deviations. AIROBE allows the decision maker to tradeoff robustness with stability of the system and energy costs. Our evaluation shows, how AIROBE can deal effectively with asymmetric deviations and how better prediction methods can reduce both the operational cost while at the same time may lead to increased operational stability of the system.