Catenary-Powered Electric Traction Network Modeling: A Data-Driven Analysis for Trolleybus System Simulation

In the context of smart cities, direct current overhead contact lines, usually adopted to power urban transportation systems such as trolleybuses, tramways, metros, and railways, can serve as a backbone to connect different modern emerging technologies. Among these, in-motion charging (IMC) trolleybuses with on-board batteries are expected to be very impactful on the DC network’s power flow and may require specific voltage and current control. These factors motivate the development of a simulation tool able to emulate these devices’ absorption and their effect on the supply infrastructure. The main innovative value of the work is to improve a simulation model of a trolleybus grid through a data-driven approach by using measurements of voltage and current output from a traction substation. The measurements are essential for understanding the behavior of vehicle weight variation throughout the day. Thanks to this information, a characterization of the current draw by conventional trolleybuses and IMC trolleybuses is then provided for each trolleybus route in a specific power section of the Bologna trolleybus system. By integrating the variation in vehicle weight within the model, a simulation of a possible daily operation of a trolleybus feeding section has been performed, obtaining a 7% error between the daily energy calculated from the simulation and that obtained through measurements. This analysis demonstrates the feasibility of the adopted simulation tool, which can also be used to evaluate additional hypothetical trolleybus operation scenarios. One of these possible scenarios considers IMC vehicles, and it is also evaluated in this paper

Novel Multi‐Vehicle Motion‐Based Model of Trolleybus Grids towards Smarter Urban Mobility

Trolleybus systems are resurfacing as a steppingstone to carbon-neutral urban transport. With an eye on smart city evolution, the study and simulation of a proper monitoring system for trolleybus infrastructures will be essential. This paper merges the authors’ engineering knowledge and sources available in the literature on designing and modeling catenary-based electric traction networks and performs a critical review of them to lay the foundations for proposing possible optimal alternatives. A novel multi-vehicle motion-based model of the DC catenary system is then devised and simulated in Matlab-Simulink, which could prove useful in predicting possible technical obstacles arising from the next-future introduction of smart electric traction grids, inevitably featuring greater morphological intricacy. The modularity property characterizing the created model allows an accurate, detailed, and flexible simulation of sophisticated catenary systems. By means of graphical and numerical results illustrating the behavior of the main electrical line parameters, the presented approach demonstrates today’s obsolescence of conventional design methods used so far. The trolleybus network of the city of Bologna was chosen as a case study

High-Precision Model for Accurate Simulation of Trolleybus Grids: Case Study of Bologna

The integration of renewable sources to catenary-powered electric traction systems is a paramount step to satisfy sustainability and smart city objectives, albeit necessitating accurate simulations of the infrastructure. This paper presents an innovative trolleybus network simulator, characterised by the modularity of the catenary model and built on an intuitive graphical user interface that offers significant topological change flexibility. The model is distinguished by high precision and moderate processing effort, bridging the gaps of existing block-based simulation tools. A graphical analysis of the voltage distribution evaluated in a section of Bologna's trolleybus network shows the advances in precision of the proposed model

Inventário nacional de emissões e remoções antrópicas de gases de efeito estufa.

O Brasil apresenta periodicamente seu inventário nacional de emissões antrópicas por fontes e remoções antrópicas por sumidouros de todos os gases de efeito estufa (GEE) não controlados pelo Protocolo de Montreal (doravante referenciado como Inventário), na medida que permitem as suas capacidades, conforme seu compromisso de atualização dessas estimativas e relato junto à Convenção-Quadro das Nações Unidas sobre Mudança do Clima (UNFCCC, no acrônimo em inglês). Além do Inventário pertinente às Comunicações Nacionais, o Brasil disponibiliza relato atualizado de suas emissões e remoções nos Relatórios de Atualização Bienal (BUR, no acrônimo em inglês). Os GEE estimados no presente Inventário foram o dióxido de carbono (CO2), o metano (CH4), o óxido nitroso (N2O), os hidrofluorcarbonos (HFC), os perfluorcarbonos (PFCs) e o hexafluoreto de enxofre (SF6). Outros gases, como monóxido de carbono (CO), óxidos de nitrogênio (NOx) e outros compostos orgânicos voláteis não metano (NMVOC), são GEE indireto, cujas emissões antrópicas foram incluídas sempre que possível, conforme encorajado pela UNFCCC. Este Inventário apresenta as emissões de 1990 a 2016, com atualização do Terceiro Inventário, que apresentou as emissões de 1990 a 2010 (BRASIL, 2016). A metodologia utilizada no presente Inventário reflete os avanços técnico-científicos consolidados nas "Diretrizes de 2006 do Painel Intergovernamental sobre Mudança do Clima (IPCC, no acrônimo em inglês) para Inventários Nacionais de Emissões de Gases de Efeito Estufa" (2006 IPCC Guidelines for National Greenhouse Gas Inventories - IPCC 2006) (IPCC, 2006). Em virtude das diversas fontes de emissões antrópicas de GEE, o Inventário está organizado segundo as atividades contempladas nos setores: Energia; Processos Industriais e Uso de Produtos (IPPU, no acrônimo em inglês); Agropecuária; Uso da Terra, Mudança do Uso da Terra e Florestas (LULUCF, no acrônimo em inglês); e Resíduos (conforme Figura 2.1). Já as remoções de GEE são contabilizadas apenas no setor LULUCF, como resultado do aumento do estoque de carbono, por meio, por exemplo, do crescimento de vegetação

Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine

Brazil has a monitoring system to track annual forest conversion in the Amazon and most recently to monitor the Cerrado biome. However, there is still a gap of annual land use and land cover (LULC) information in all Brazilian biomes in the country. Existing countrywide efforts to map land use and land cover lack regularly updates and high spatial resolution time-series data to better understand historical land use and land cover dynamics, and the subsequent impacts in the country biomes. In this study, we described a novel approach and the results achieved by a multi-disciplinary network called MapBiomas to reconstruct annual land use and land cover information between 1985 and 2017 for Brazil, based on random forest applied to Landsat archive using Google Earth Engine. We mapped five major classes: forest, non-forest natural formation, farming, non-vegetated areas, and water. These classes were broken into two sub-classification levels leading to the most comprehensive and detailed mapping for the country at a 30 m pixel resolution. The average overall accuracy of the land use and land cover time-series, based on a stratified random sample of 75,000 pixel locations, was 89% ranging from 73 to 95% in the biomes. The 33 years of LULC change data series revealed that Brazil lost 71 Mha of natural vegetation, mostly to cattle ranching and agriculture activities. Pasture expanded by 46% from 1985 to 2017, and agriculture by 172%, mostly replacing old pasture fields. We also identified that 86 Mha of the converted native vegetation was undergoing some level of regrowth. Several applications of the MapBiomas dataset are underway, suggesting that reconstructing historical land use and land cover change maps is useful for advancing the science and to guide social, economic and environmental policy decision-making processes in Brazil