Determining electric vehicle charging point locations considering drivers' daily activities

In this paper the daily temporal and spatial behavior of electric vehicles (EVs) is modelled using an activity-based (ActBM) microsimulation model for Flanders region (Belgium). Assuming that all EVs are completely charged at the beginning of the day, this mobility model is used to determine the percentage of Flemish vehicles that cannot cover their programmed daily trips and need to be recharged during the day. Assuming a variable electricity price, an optimization algorithm determines when and where EVs can be recharged at minimum cost for their owners. This optimization takes into account the individual mobility constraint for each vehicle, as they can only be charged when the car is stopped and the owner is performing an activity. From this information, the aggregated electric demand for Flanders is obtained, identifying the most overloaded areas at the critical hours. Finally it is also analyzed what activities EV owners are underway during their recharging period. From this analysis, different actions for public charging point deployment in different areas and for different activities are proposed.

On the actions that one nerve cell can have on another: Distinguishing “drivers��� from “modulators”

When one nerve cell acts on another, its postsynaptic effect can vary greatly. In sensory systems, inputs from “drivers��� can be differentiated from those of “modulators.” The driver can be identified as the transmitter of receptive field properties; the modulator can be identified as altering the probability of certain aspects of that transmission. Where receptive fields are not available, the distinction is more difficult and currently is undefined. We use the visual pathways, particularly the thalamic geniculate relay for which much relevant evidence is available, to explore ways in which drivers can be distinguished from modulators. The extent to which the distinction may apply first to other parts of the thalamus and then, possibly, to other parts of the brain is considered. We suggest the following distinctions: Cross-correlograms from driver inputs have sharper peaks than those from modulators; there are likely to be few drivers but many modulators for any one cell; and drivers are likely to act only through ionotropic receptors having a fast postsynaptic effect whereas modulators also are likely to activate metabotropic receptors having a slow and prolonged postsynaptic effect.

Drivers of atmospheric methane uptake by montane forest soils in the southern Peruvian Andes

Peer reviewed

The steel industry in the European Union: Composition and drivers of energy prices and costs. CEPS Special Report No. 80, 17 December 2013

This report assesses the energy costs borne by the steel industry in the EU between 2010 and 2012, and compares the energy costs, including both the energy components and other regulatory costs, to production costs, turnover and margins of steel-makers. The estimates of energy costs are based on primary sources, i.e. is on information provided by steel-makers through a written questionnaire. This information was validated by the research team by checking annual energy bills, when available, and other public sources. In this respect, this exercise represents a unique fact-based investigation into the costs of energy for steel-makers in Europe, whereas most of the information currently available in the public domain is based on secondary or statistical information. In 2012, the median EU steel plant pays about €33/MWh for gas, up from €26/MWh in 2010. As for electricity, in 2012 the EU median plant pays €62/MWh, up from €59/MWh in 2010. The report also includes a comparison with the prices of energy carriers paid by producers based in the US.

The Composition and Drivers of Energy Prices and Costs in Energy-Intensive Industries: The Case of Ceramics, Glass and Chemicals. CEPS Special Report No. 85, 27 March 2014

In May 2013, the European Commission received a mandate from the European Council to “to present an analysis of the composition and drivers of energy prices and costs in Member States, with a particular focus on the impact on households, SMEs and energy intensive industries, and looking more widely at the EU's competitiveness vis-à-vis its global economic counterparts”. Following such mandate and in view of the preparation by the Commission of a Communication and a Staff Working Document, DG Enterprise and Industry commissioned CEPS to carry out a set of studies aimed at providing well-grounded evidence about the evolution and composition of energy prices and costs at plant level within individual industry sectors. A team of CEPS researchers conducted the research, led by Christian Egenhofer and Lorna Schrefler. Vasileios Rizos served as Project Coordinator. Other CEPS researchers contributing to the project included: Fabio Genoese, Andrea Renda, Andrei Marcu, Julian Wieczorkiewicz, Susanna Roth, Federico Infelise, Giacomo Luchetta, Lorenzo Colantoni, Wijnand Stoefs, Jacopo Timini and Felice Simonelli. In addition to an introductory report entitled “About the Study and Cross-Sectoral Analysis”, CEPS prepared five sectoral case studies: two on ceramics (wall and floor tiles and bricks and roof tiles), two on chemicals (ammonia and chlorine) and one on flat glass. Each of these six studies has been consolidated in this single volume for free downloading on the CEPS website. The specific objective was to complement information already available at macro level with a bottom-up perspective on the operating conditions that industry stakeholders need to deal with, in terms of energy prices and costs. The approach chosen was based on case studies for a selected set (sub-)sectors amongst energy-intensive industries. A standard questionnaire was circulated and respondents were sampled according to specified criteria. Data and information collected were finally presented in a structured format in order to guarantee comparability of results between the different (sub-)sectors analysed. The complete set of files can also be downloaded from the European Commission’s website: http://ec.europa.eu/enterprise/newsroom/cf/itemdetail.cfm?item_id=7238&lang=en&title=Study-on-composition-and-drivers-of-energy-prices-and-costs-in-energy-intnsive-industries The results of the studies were presented at a CEPS Conference held on February 26th along with additional evidence from other similar studies. The presentations can be downloaded at: http://www.ceps.eu/event/level-and-drivers-eu-energy-prices-energy-inten...

Drivers of Agricultural Physical Capital Development: Theoretical Framework and Hypotheses. Factor Markets Working Paper No. 18, February 2012

This paper aims to identify drivers of physical capital adjustments in agriculture. It begins with a review of some of the most important theories and modelling approaches regarding firms’ adjustments of physical capital, ranging from output-based models to more recent approaches that consider irreversibility and uncertainty. Thereafter, it is suggested that determinants of physical capital adjustments in agriculture can be divided into three main groups, namely drivers related to: i) expected (risk-adjusted) profit, ii) expected societal benefits and costs and iii) expected private nonpecuniary benefits and costs. The discussion that follows focuses on the determinants belonging to the first group and covers aspects related to product market conditions, technological conditions, financial conditions and the role of firm structure and organization. Furthermore, the role of subjective beliefs is emphasized. The main part of this paper is concerned with the demand side of the physical capital market and one section also briefly discusses some aspects related to supply of farm assets.

Drivers of agricultural capital productivity in selected EU member states. Factor Markets Working Paper No. 30, September 2012

The aim of this Working Paper is to provide an empirical analysis of the marginal return on working capital and fixed capital in agriculture, based on data gathered by the Farm Accountancy Data Network from seven EU member states. Particular emphasis is placed on the detection of credit market imperfections. The key idea is to provide farm group-specific estimates of the shadow price of capital, and to use these to analyse the drivers of on-farm capital use in European agriculture. Based on Cobb Douglas estimates of farm-type specific production functions, we find that working capital is typically used in more than economically optimal quantities and often displays negative marginal returns across countries and farm types. This is less often the case with regard to fixed capital, but it is only in a small set of sectors where access to fixed capital appears severely constrained. These sectors include field crop and mixed farms in Denmark, dairy farms in East Germany, as well as mixed farms in Italy and the UK. The relationship between farm financial indicators and the estimated shadow prices of capital varies considerably across countries and sectors. Among the farms with a high shadow price for fixed capital in Denmark, high debt levels and little owned land tended to induce more intensive capital use, which may reflect the liberal Danish banking system. In East Germany, Italy and the UK, high debt levels made farmers more tightly capital constrained. Hence, in the latter group of countries, more traditional mechanisms of capital allocation based on debt capacity seemed to be at work. As a general conclusion, EU agriculture appears to be characterised by overcapitalisation rather than by credit constraints.