Abstract
In this work we study a way to explore and extract more information from data sets with a hierarchical tree structure. We propose that any statistical study on this type of data should be made by group, after clustering. In this sense, the most adequate approach is to use the Mahalanobis-Wasserstein distance as a measure of similarity between the cases, to carry out clustering or unsupervised classification. This methodology allows for the clustering of cases, as well as the identification of their profiles, based on the distribution of all the variables that characterises each subject associated with each case. An application to a set of teenagers' interviews regarding their habits of communication is described. The interviewees answered several questions about the kind of contacts they had on their phone, Facebook, email or messenger as well as the frequency of communication between them. The results indicate that the methodology is adequate to cluster this kind of data sets, since it allows us to identify and characterise different profiles from the data. We compare the results obtained with this methodology with the ones obtained using the entire database, and we conclude that they may lead to different findings.

Abstract
Electric vehicles (EVs) are to play an important role in electricity markets, since their energy storage capability can be beneficial to power systems operation. Electric vehicle aggregators will consequently develop adequate offering strategies to participate in energy and reserve markets, accounting for the market rules and operational capabilities of EVs aggregators (e.g., fleet of EVs). In this paper, we propose an offering strategy model for an EV aggregator to participate in the frequency-controlled normal operation reserve service (FCR-N) in Eastern Denmark. The aim is to maximize the expected revenue of the aggregator, accounting for potential penalties for missing the provision of both upward and downward reserves. The methodology has been modeled and tested under the scope of the PARKER project, which considers a case study based on real data from a small fleet of electric vehicles. An important conclusion relates to the availability patterns of the EVs that significantly changes the strategical participation of the EV aggregator in the service.

Abstract
The coordination of various energy vectors under the concept of multi-energy system (MES) has introduced new sources of operational flexibility to system managers. In this paper, the behavior of multi-energy players (MEP) who can trade with more than one energy carrier to maximize their profits and mitigate their operational risks has been investigated. The MES is represented based on a multilayer structure, namely the energy market, MEP, the local energy system (LES), and multi-energy demand. In such environment, an MEP aggregates LES and participates in the wholesale electricity market, simultaneously to maximize its profit. The decision-making conflict of the MEP with other energy players for the aggregation of LES and participation in the electricity market is modeled based on a bilevel approach. Numerical results show the behavior of the MEP as a prosumer in the electricity market to produce smoother demand and price profiles. Results reveal a mutual effect of local and wholesale equilibrium prices by increasing the share of the MEP.

Abstract
The introduction of plug-in electric vehicles (PEVs) in the electrical system is bringing various challenges. The main issue is incorporating the PEV owner's preferences in the models. One of the main attributes representing the preference of the owners is their travel purposes, impacting on the traffic flow pattern. The PEVs' traffic pattern defines the required charging schedule of the PEVs, and consequently, characterizes the operation of the charging facilities such as PEV parking lots (PLs). The deployment of resources such as PEV PL requires a detailed modeling of the factors affecting their operation. In this regard, this paper aims to model the power flow of the PEVs based on their traffic flow. Different travel types and purposes are considered for the PEVs traffic modeling. Two types of charging infrastructure (i.e., PLs and individual charging stations) are considered. The study is performed on a distribution network categorized based on the consumption patterns of the zones.

Abstract

Abstract
This paper analyzes a set of selected German and French cities' performance in terms of the relative behavior of their eco-efficiencies, computed as the ratio of their gross domestic product (GDP) over their CO2 emissions. For this analysis, eco-efficiency scores of the selected cities are computed using the data envelopment analysis (DEA) technique, taking the eco-efficiencies as outputs, and the inputs being the energy consumption, the population density, the labor productivity, the resource productivity, and the patents per inhabitant. Once DEA results are analyzed, the Malmquist productivity indexes (MPI) are used to assess the time evolution of the technical efficiency, technological efficiency, and productivity of the cities over the window periods 2000 to 2005 and 2005 to 2008. Some of the main conclusions are that (1) most of the analyzed cities seem to have suboptimal scales, being one of the causes of their inefficiency; (2) there is evidence that high GDP over CO2 emissions does not imply high eco-efficiency scores, meaning that DEA like approaches are useful to complement more simplistic ranking procedures, pointing out potential inefficiencies at the input levels; (3) efficiencies performed worse during the period 2000-2005 than during the period 2005-2008, suggesting the possibility of corrective actions taken during or at the end of the first period but impacting only on the second period, probably due to an increasing environmental awareness of policymakers and governors; and (4) MPI analysis shows a positive technological evolution of all cities, according to the general technological evolution of the reference cities, reflecting a generalized convergence of most cities to their technological frontier and therefore an evolution in the right direction.