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.

Abstract
Environmental policies could accelerate the replacement of Internal Combustion Engine Vehicles (ICEV) by Plug-in-Electric Vehicles (PEV) in many countries. However, in countries where these policies are still not implemented (for example those with no significant PEV subsidies like Spain), technical and economic criteria can also be relevant to assess the future PEV penetration. This work develops a new long-term expansion model that computes the share of PEV and ICEV based on economic criteria, including the impact of PEV on the electricity price and generation mix. The model minimizes the power and transport system costs (investment, operation and maintenance costs, etc.) considering electricity and private transportation needs. Results provide insight on the combined evolution of the renewable generation and of the PEV and ICEV future fleets in Spain, considering environmental constraints such as those imposed by the European Commission.

Abstract
Capacity generation expansion problems have traditionally been represented with low time resolution models due to their high computational cost, very often using blocks of hours with similar demand. However, the current transformation of the power system with the new generation and consumption technologies, the flexibility and reserve requirements, and the expected new behavioral consumption patterns, requires more complex and detailed models with higher time resolution to provide accurate investment decisions and allow for closer analyses. In particular, these challenges require chronological hourly models with constraints linking all the years of the planning horizon, compromising in most cases the computational feasibility. This paper presents a new approach to synthetize a reduced representative time period for capacity expansion problems, for being used in detailed chronological hourly models, while keeping them computationally feasible. The representative period is synthetized by selecting, with a genetic algorithm, those real days that minimizes the distance between the duration curves of a set of relevant variables (such as demand, renewable generation, ramps, etc.) computed for the original and for the representative periods. Results show that investments decisions with the representative period are very similar to those obtained with the full planning horizon, while computational times are strongly reduced.

Abstract
The European Union (EU) is adopting proactive strategies toward global decarbonization, proposing ambitious climate objectives to the international community, and adopting by itself ambitious energy and climate change objectives, as can be checked in its strategic packages for 2020, 2030 and 2050. As can be seen in these packages and in global climate and energy agreements, renewable generation is a key aspect to reach the global decarbonizing objectives. This chapter starts with a review of the very basic concepts of greenhouse gases emissions and its impact on climate change and summarizes the main objectives of the strategic EU energy packages and of the Paris agreement. It then focuses on methodologies for estimating the impact of renewable energies on greenhouse gases emissions reduction and reviews the reported EU related achievements. It also proposes a classification of EU countries in terms of Tapio decoupling states by analyzing and classifying the countries emissions intensities and its variation for a considered time period and analyzes the impact renewable energies had in that greenhouse gases emissions variations, in relation with other possibly relevant factors. The chapter ends with a summary of the expected evolution of renewable energies in the EU, and with the final conclusions.