![]() ![]() The second tool is designed for planning grid extension or reinforcement while the third tool is mainly used to quickly discover potential conflicts of grid operation approaches through load flow analysis. One of the tools aims at a combined techno-economic design and operation, primarily modeling plants on contracts or the spot market, at the same time participating in balancing markets. It is a combination of three professional tools. E-MObility grid model) was developed within a European research project and is currently being tested using realistic showcases. The simulation and optimization tool suite NEMO (Novel. Tools and methodologies are required to characterize grid problems resulting from the interconnection of EV with the grid. With an increasing use of electric vehicles (EV) grid operators need to predict energy flows depending on electromobility use profiles to accordingly adjust grid infrastructure and operation control accordingly. The online version of this article (10.1007/s1068-5) contains supplementary material, which is available to authorized users. Thus, to the extent that such concentrations contribute to spatial inequalities, these countries are facing similar policy challenges. For large-scale, migrant-dense neighbourhoods, however, levels of concentration are similar in Belgium, the Netherlands, and Sweden. Thus, in both migrant-dense and native-born-dense areas, Swedish neighbourhoods have a higher concentration and Denmark a lower concentration of non-European migrants than the other countries. ![]() Sweden has the largest and Denmark the smallest non-European migrant population, in relative terms. Possible explanations for the variation across countries are differences in housing policies and refugee placement policies. In the other countries, the corresponding figures are between 30 and 40%. More than 55% of the Belgian population lives in large-scale neighbourhoods with moderate under- or over-representation of non-European migrants. At larger-scale levels, Belgium stands out as having relatively strong over- and under-representation. ![]() At the smallest scale level, corresponding to neighbourhoods with 200 persons, patterns of over- and under-representation are strikingly similar. The focus is on non-European migrants, for whom aggregates of egocentric neighbourhoods (with different population counts) are used to assess small-scale, medium-scale, and large-scale segregation. In this paper, we use geo-coded, individual-level register data on four European countries to compute comparative measures of segregation that are independent of existing geographical sub-divisions. ![]()
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