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Abstract In the last years, electric vehicles (EVs) are getting significant consideration as an environmental-sustainable and cost-effective alternative over conventional vehicles with internal combustion engines (ICEs), for the mitigation of the dependence from fossil fuels and for reduction of Green-House Gasses (GHGs) emission. However, many challenges are still ongoing to their large scale implementation. Among them, the negative impact on the electrical grid operation in case of an uncoordinated contemporary charging of a huge number of EVs. In the recent literature different solutions are proposed for handling the peak demand of EVs and the related problems. One answer is offered by the implementation of EV charging strategies, through aggregation agents, for containing the impact on the grid, guaranteeing the quality of the service. The implementation of a real charging strategy is strictly related to a deployment of smart-grid technologies, such as smart meters, Information and Communication Technologies (ICTs) and energy storage systems (ESSs). In particular ESSs are playing a fundamental role in the general smart grid paradigm, and can become fundamental for the integration in the new power systems of EV fast charging stations of the last generation: in this case the storage can have peak shaving and power quality functions and also to make the charge time shorter. In the present paper, an overview on the different types of EVs charging stations, in reference to the present international European standards, and on the storage technologies for the integration of EV charging stations in smart grid is reported. Then a real implementation of EVs fast charging station equipped with an ESS is deeply described. The system is a prototype, designed, implemented and now available at ENEA (Italian National Agency for New Technologies, Energy and Sustainable Economic Development) labs. A wide experimental activity has been performed on the prototype system in order to test its functionalities in the integration in a smart grid available at the same ENEA lab, including a smart metering system. The integration has been possible thanks to the use of a customized communication protocol, developed by the researchers and here described. The results of the experimental tests show that the system has a good performance in the implementation of peak shaving functions, in respect of the main distribution grid, making the prototype like a network nearly zero-impact system.

Capítulos en libros This paper assesses the scalability and replicability of smart grid projects, by means of the identification of limitations and barriers faced by these projects. Factors have been identified that impact a project s scalability and replicability by means of a review of demonstration projects. The factors are of technical, economic, regulatory and social acceptance nature, and they describe requirements for scalability and replicability. Data was collected from ongoing European smart grid demonstration projects through the use of an elaborated questionnaire on the identified factors. Which allowed to quantify the status quo to what extent projects have taken these factors into account. Dew to their nature the derived factors can be categorized in technical, economic and regulatory & stakeholder related factor areas The obtained results allowed the identification of barriers, i.e. limitations regarding the scalability and replicability of smart grid projects. In particular projects face barriers regarding the absence of standards, the physical limits of the existing infrastructure, the absence of cost-benefit analyses, the neglect of varying macro-economic factors, stakeholder involvement and from the dependency of projects on regional or national regulatory frameworks and market designs. info:eu-repo/semantics/publishedVersion

This paper focuses on the planning of electricity resources in the developing electricity infrastructure. First we model the existing infrastructure and extend this model to a smart grid infrastructure, where we focus on the large scale introduction of small electricity generators, leading to generation possibilities at both ends of the electricity network. Then the traditional Unit Commitment Problem (UCP) is given. We extend this formulation to the Multilevel Unit Commitment Problem (MUCP), where we describe and include the possibilities that arise in the developing smart grid, in a general way. Based on the characteristics of the problem with its subdivision into different levels, a planning method for the MUCP is described. Finally we solve and analyze a scenario, where a fleet of 5000 houses is added to a small collection of power plants.

In this paper, the implementation of a simulation model for studying the effect of cross-bonding of metallic sheaths and/or non-magnetic armor of single-core medium voltage cables in the same circuit is discussed. With the use of single-core cables, the resistive losses due to the induced circulating currents in cable sheaths or armors causes an increase of cable temperature that reduces its ampacity. In addition, the risk of electric shock due to induced voltages may be present if a person is exposed to the armor/sheath at the unbounded end. For this reason, special bonding techniques are used to significantly reduce these currents. The authors have implemented a model that could be used to help optimize the cross-bonding configuration for single-core cables employed in high-current industrial applications. The model has been experimentally validated thanks to actual data from a medium-voltage underground line.

Urban environments provide opportunities for greater resource efficiency and the fostering of urban ecosystems. Brownfield areas are a typical example of underused land resources. Brownfield redevelopment projects that include green infrastructure allow for further ecosystems to be accommodated in urban environments. Green infrastructure also deliver important urban ecosystem services (UES) to local residents, which can greatly contribute to improving quality of life in cities. In this case study, we quantify and assess the economic value of five UES for a brownfield redevelopment project in Antwerp, Belgium. The assessment is carried out using the “Nature Value Explorer” modelling tool. The case includes three types of green infrastructure (green corridor,infiltration gullies and green roofs) primarily intended to connect nature reserves on the urban periphery and to avoid surface runoff. The green infrastructure also provides air filtration, climate regulation, carbon sequestration and recreation ecosystem services. The value of recreation far exceeds other values, including the value of avoided runoff. The case study raises crucial questions as to whether existing UES valuation approaches adequately account for the range of UES provided and whether such approaches can be improved to achieve more accurate and reliable value estimates in future analyses.

Advanced smart grids have several power sources that contribute with their own irregular dynamic to the power production, while load nodes have another dynamic. Several factors have to be considered when using the owned power sources for satisfying the demand, i.e., production rate, battery charge and status, variable cost of externally bought energy, and so on. The objective of this paper is to develop appropriate neural network architectures that automatically and continuously govern power production and dispatch, in order to maximize the overall benefit over a long time. Such a control will improve the fundamental work of a smart grid. For this, status data of several components have to be gathered, and then an estimate of future power production and demand is needed. Hence, the neural network-driven forecasts are apt in this paper for renewable nonprogrammable energy sources. Then, the produced energy as well as the stored one can be supplied to consumers inside a smart grid, by means of digital technology. Among the sought benefits, reduced costs and increasing reliability and transparency are paramount.

Questions of justice in the transition to a green economy have been raised by various social forces. Very few proposals, however, have been as focused and developed as the “just transition” strategy proposed by global labour unions. Yet, labour unions are remarkably absent from discussions of the transition towards a green economy. This is surprising as labour unions are arguably the largest organizations in the world fighting for basic rights and more just social relations. This paper tries to advance the potential contribution of labour unions in this arena by asking: what is the full scope of “just transition” today and how have labour unions developed and refined it over the years to render the move towards a green economy both environmentally and socially sustainable? The concept of just transition is hotly debated within labour unions and has different interpretations, and hence different strategies. The last section assesses these interpretations by means of a normative framework, which seeks to fuse political economy and political ecology. Empirically, we add to the growing literature on labour environmentalism, as well as transitions more generally. Analytically, our goal is to place the various approaches to a “just transition” within a heuristic framework of environmental justice that is explicit about power relations when demanding justice, two themes central to this special issue.

A smart grid features can be referred to as a two-way communication with all active network elements and decentralized resources such as under-load tap-changer (ULTC), capacitor, and distributed generation (DG) units. In the smart grid systems, the mentioned units are required to be well coordinated to keep the voltage within the standard range. Therefore, in this paper, a multi-agent controller based on type-2 fuzzy logic system (T2FLS) is utilized to coordinate the DG, ULTC, and load to regulate the voltage of the smart grid in the presence of noise and uncertainty. The proposed fuzzy system identifies the different parts of the smart grid as an agent (i.e. ULTC, DG, and load) and regulates the voltage by managing them. A 16-bus power system has been utilized to demonstrate the effectiveness of the proposed method. It has been shown that the proposed T2FLS controller outperforms the type-1 fuzzy controller and regulates the voltage in an appropriate way even in the presence of the different levels of measurement noise and uncertainty.