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This paper develops a data-driven model for assessing the availability of flexibility from individual household devices, at house level. The model predicts the potential shift, increase or decrease of the energy consumption of a particular type of device at a given time, in response to a price signal, and for each house separately. Therefore, the location of the flexibility source is known with accuracy. The model has an Auto-Encoder architecture based on Convolution Neural Network. The augmented model demonstrates good performance in terms of predicting the time-shift in load.

A theoretical and empirical model is developed to analyze the effect of a biodiesel mandate, a tax exemption (tax credit) and an exogenous diesel price shock on world soybean and canola markets. The jointness in crushing oil and meal from the oilseed reduces the size of the link between biodiesel and oilseed prices. A diesel price shock with a mandate results in a smaller change in oilseed prices compared with a tax exemption. Higher diesel prices increase biodiesel prices under a tax exemption but lower them with a blend mandate. When both canola and soybeans are used to produce biodiesel, an increase in the diesel price leads to higher canola prices, but the effect on soybean prices is ambiguous and depends on relative elasticities of meal demand and canola supply because canola produces more oil than soybeans.

Little is known about the validity of repeated 24-h dietary recalls (24-HDR) as a measure of total energy intake (EI) in young children. This study aimed to evaluate the validity of proxy-reported EI by comparison with total energy expenditure (TEE) measured by the doubly labeled water (DLW) technique.The agreement between EI and TEE was investigated in 36 (47.2% boys) children aged 4-10 years from Belgium and Spain using subgroup analyses and Bland-Altman plots. Low-energy-reporters (LER), adequate-energy-reporters (AER) and high-energy-reporters (HER) were defined from the ratio of EI over TEE by application of age- and sex-specific cut-off values.There was good agreement between means of EI (1500 kcal/day) and TEE (1523 kcal/day) at group level though in single children, i.e. at the individual level, large differences were observed. Almost perfect agreement between EI and TEE was observed in thin/normal weight children (EI: 1511 kcal/day; TEE: 1513 kcal/day). Even in overweight/obese children the mean difference between EI and TEE was only -86 kcal/day. Among the participants, 28 (78%) were classified as AER, five (14%) as HER and three (8%) as LER.Two proxy-reported 24-HDRs were found to be a valid instrument to assess EI on group level but not on the individual level.

Cogeneration of heat and electricity is an important pillar of energy and climate policy. To plan the production and distribution system of combined heat and power (CHP) systems for residential heating, suitable methods for decision support are needed. For a comprehensive feasibility analysis, the integration of the location and capacity planning of the power plants, the choice of customers, and the network planning of the heating network into one optimization model are necessary. Thus, we develop an optimization model for electricity generation and heat supply. This mixed integer linear program (MILP) is based on graph theory for network flow problems. We apply the network location model for the optimization of district heating systems in the City of Osorno in Chile, which exhibits the “checkerboard layout” typically found in many South American cities. The network location model can support the strategic planning of investments in renewable energy projects because it permits the analysis of changing energy prices, calculation of break-even prices for heat and electricity, and estimation of greenhouse gas emission savings.

Pervasive computing and business process modeling are increasingly joining forces, as mobile human users shall be seamlessly integrated into business processes. In respective scenarios, humans use mobile devices and wireless technology to interact with workflows running in a powerful back-end infrastructure. However, the frequent interaction between humans and workflows causes a high communication overhead and, thus, high energy consumption on mobile devices. This impacts the usability and efficiency of the business process due to rapidly drained batteries and the resulting short life-times of the devices and applications. We present an approach based on a minimum-cut algorithm for reducing costly data transmissions during workflow execution by distributing parts of a workflow to the users' devices. Our motivation is to reduce the energy consumption on the mobile devices and, thus, avoid draining batteries in the field. We prove that our algorithm finds the optimal solution for a given network and workflow, decreasing the energy consumed on mobile devices by 32-37% compared to an approach where the entire workflow is executed in the infrastructure. Thus, in typical domains like logistics and health care, one third of the energy can be saved. This either means that devices have to be charged less frequently, leading to less distraction in the business process, or that mobile device specifications can be lowered. Significant cost reductions result in both cases.

After a halt of four years, the n TOF spallation neutron facility at CERN has resumed operation in November 2008 with a new spallation target characterized by an improved safety and engineering design, resulting in a more robust overall performance and e cient cooling. The rst measurement during the 2009 run has aimed at the full characterization of the neutron beam. Several detectors, such as calibrated ssion chambers, the n TOF Silicon Monitor, a Mi- croMegas detector with 10B and 235U samples, as well as liquid and solid scintillators have been used in order to characterize the properties of the neutron uence. The spatial pro le of the beam has been studied with a specially designed \X-Y