Micro-inverter for integrated grid-tie photovoltaic module using resonant controller

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Uma investigação do minos e sua aplicação ao problema de fluxo de potência ótimo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Alocação ótima de chaves de interconexão nas redes de distribuição de energia elétrica

Pós-graduação em Engenharia Elétrica - FEIS

Aplicação de técnicas metaheurísticas para resolver o problema de coordenação de carregamento de veículos elétricos em sistemas de distribuição

Pós-graduação em Engenharia Elétrica - FEIS

Desenvolvimento de uma rede neuro-fuzzy para a previsão da carga

Pós-graduação em Engenharia Elétrica - FEIS

Inclusão das representações de gary e de skilling-umoto em modelos de linhas de transmissão trifásicas: Aplicação em simulações de transitórios eletromagnéticos em sistemas de energia elétrica

Pós-graduação em Engenharia Elétrica - FEIS

Análise espacial do potencial fotovoltaico em telhados de residências usando modelagem hierárquica bayesiana

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fluxo de potência continuado baseado em equações de injeção de corrente expressas em coordenadas polares

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

La sostenibilità ambientale dal Progetto Edilizio al Piano Urbano: L'integrazione della variabile energetica nella pianificazione del territorio

La questione energetica ha assunto, negli ultimi anni, un ruolo centrale nel dibattito mondiale in relazione a quattro fattori principali: la non riproducibilità delle risorse naturali, l’aumento esponenziale dei consumi, gli interessi economici e la salvaguardia dell'equilibrio ambientale e climatico del nostro Pianeta. E’ necessario, dunque, cambiare il modello di produzione e consumo dell’energia soprattutto nelle città, dove si ha la massima concentrazione dei consumi energetici. Per queste ragioni, il ricorso alle Fonti Energetiche Rinnovabili (FER) si configura ormai come una misura necessaria, opportuna ed urgente anche nella pianificazione urbanistica. Per migliorare la prestazione energetica complessiva del sistema città bisogna implementare politiche di governo delle trasformazioni che escano da una logica operativa “edificio-centrica” e ricomprendano, oltre al singolo manufatto, le aggregazioni di manufatti e le loro relazioni/ interazioni in termini di input e output materico-energetiche. La sostituzione generalizzata del patrimonio edilizio esistente con nuovi edifici iper-tecnologici, è improponibile. In che modo quindi, è possibile ridefinire la normativa e la prassi urbanistica per generare tessuti edilizi energeticamente efficienti? La presente ricerca propone l’integrazione tra la nascente pianificazione energetica del territorio e le più consolidate norme urbanistiche, nella generazione di tessuti urbani “energy saving” che aggiungano alle prestazioni energetico-ambientali dei singoli manufatti quelle del contesto, in un bilancio energetico complessivo. Questo studio, dopo aver descritto e confrontato le principali FER oggi disponibili, suggerisce una metodologia per una valutazione preliminare del mix di tecnologie e di FER più adatto per ciascun sito configurato come “distretto energetico”. I risultati di tale processo forniscono gli elementi basilari per predisporre le azioni necessarie all’integrazione della materia energetica nei Piani Urbanistici attraverso l’applicazione dei principi della perequazione nella definizione di requisiti prestazionali alla scala insediativa, indispensabili per un corretto passaggio alla progettazione degli “oggetti” e dei “sistemi” urbani.

Decomposition Methods and Network Design Problems

Decomposition based approaches are recalled from primal and dual point of view. The possibility of building partially disaggregated reduced master problems is investigated. This extends the idea of aggregated-versus-disaggregated formulation to a gradual choice of alternative level of aggregation. Partial aggregation is applied to the linear multicommodity minimum cost flow problem. The possibility of having only partially aggregated bundles opens a wide range of alternatives with different trade-offs between the number of iterations and the required computation for solving it. This trade-off is explored for several sets of instances and the results are compared with the ones obtained by directly solving the natural node-arc formulation. An iterative solution process to the route assignment problem is proposed, based on the well-known Frank Wolfe algorithm. In order to provide a first feasible solution to the Frank Wolfe algorithm, a linear multicommodity min-cost flow problem is solved to optimality by using the decomposition techniques mentioned above. Solutions of this problem are useful for network orientation and design, especially in relation with public transportation systems as the Personal Rapid Transit. A single-commodity robust network design problem is addressed. In this, an undirected graph with edge costs is given together with a discrete set of balance matrices, representing different supply/demand scenarios. The goal is to determine the minimum cost installation of capacities on the edges such that the flow exchange is feasible for every scenario. A set of new instances that are computationally hard for the natural flow formulation are solved by means of a new heuristic algorithm. Finally, an efficient decomposition-based heuristic approach for a large scale stochastic unit commitment problem is presented. The addressed real-world stochastic problem employs at its core a deterministic unit commitment planning model developed by the California Independent System Operator (ISO).

Minimizing residential distribution system operating costs through intelligently scheduled plug-in hybrid electric vehicle charging

Rising fuel prices and environmental concerns are threatening the stability of current electrical grid systems. These factors are pushing the automobile industry towards more effcient, hybrid vehicles. Current trends show petroleum is being edged out in favor of electricity as the main vehicular motive force. The proposed methods create an optimized charging control schedule for all participating Plug-in Hybrid Electric Vehicles in a distribution grid. The optimization will minimize daily operating costs, reduce system losses, and improve power quality. This requires participation from Vehicle-to-Grid capable vehicles, load forecasting, and Locational Marginal Pricing market predictions. Vehicles equipped with bidirectional chargers further improve the optimization results by lowering peak demand and improving power quality.

Estimating greenhouse gas emissions of highway construction and rehabilitation to support pavement life cycle assessment

Highway infrastructure plays a significant role in society. The building and upkeep of America’s highways provide society the necessary means of transportation for goods and services needed to develop as a nation. However, as a result of economic and social development, vast amounts of greenhouse gas emissions (GHG) are emitted into the atmosphere contributing to global climate change. In recognizing this, future policies may mandate the monitoring of GHG emissions from public agencies and private industries in order to reduce the effects of global climate change. To effectively reduce these emissions, there must be methods that agencies can use to quantify the GHG emissions associated with constructing and maintaining the nation’s highway infrastructure. Current methods for assessing the impacts of highway infrastructure include methodologies that look at the economic impacts (costs) of constructing and maintaining highway infrastructure over its life cycle. This is known as Life Cycle Cost Analysis (LCCA). With the recognition of global climate change, transportation agencies and contractors are also investigating the environmental impacts that are associated with highway infrastructure construction and rehabilitation. A common tool in doing so is the use of Life Cycle Assessment (LCA). Traditionally, LCA is used to assess the environmental impacts of products or processes. LCA is an emerging concept in highway infrastructure assessment and is now being implemented and applied to transportation systems. This research focuses on life cycle GHG emissions associated with the construction and rehabilitation of highway infrastructure using a LCA approach. Life cycle phases of the highway section include; the material acquisition and extraction, construction and rehabilitation, and service phases. Departing from traditional approaches that tend to use LCA as a way to compare alternative pavement materials or designs based on estimated inventories, this research proposes a shift to a context sensitive process-based approach that uses actual observed construction and performance data to calculate greenhouse gas emissions associated with highway construction and rehabilitation. The goal is to support strategies that reduce long-term environmental impacts. Ultimately, this thesis outlines techniques that can be used to assess GHG emissions associated with construction and rehabilitation operations to support the overall pavement LCA.

民族系物流企業の勃興

現在中国において物流サービスを提供している企業は約１万社あるとされる。筆者の見るところ、これら企業には大きく分けて三つのタイプがある。第一は外資系企業で、改革・開放の初期にはフォワーダー（貨物運送代理業者）が参入し、やがて各種の物流合弁企業が設立された。第二は旧来の運輸・倉庫企業、卸売り企業から発展したもので、既存設備や顧客を基礎に本格的物流企業への脱皮を図っている。第三が新しいビジネスモデルで参入したベンチャー系企業である。本稿では、第三の企業を紹介しつつ、激化する市場競争の中で進む業界再編の行方について展望を試みる。

Detection and Tracking of Traffic Signs Using a Recursive Bayesian Decision Framework

In this paper we propose a new method for the automatic detection and tracking of road traffic signs using an on-board single camera. This method aims to increase the reliability of the detections such that it can boost the performance of any traffic sign recognition scheme. The proposed approach exploits a combination of different features, such as color, appearance, and tracking information. This information is introduced into a recursive Bayesian decision framework, in which prior probabilities are dynamically adapted to tracking results. This decision scheme obtains a number of candidate regions in the image, according to their HS (Hue-Saturation). Finally, a Kalman filter with an adaptive noise tuning provides the required time and spatial coherence to the estimates. Results have shown that the proposed method achieves high detection rates in challenging scenarios, including illumination changes, rapid motion and significant perspective distortion

Floating car data augmentation based on infrastructure sensors and neural networks

The development of new-generation intelligent vehicle technologies will lead to a better level of road safety and CO2 emission reductions. However, the weak point of all these systems is their need for comprehensive and reliable data. For traffic data acquisition, two sources are currently available: 1) infrastructure sensors and 2) floating vehicles. The former consists of a set of fixed point detectors installed in the roads, and the latter consists of the use of mobile probe vehicles as mobile sensors. However, both systems still have some deficiencies. The infrastructure sensors retrieve information fromstatic points of the road, which are spaced, in some cases, kilometers apart. This means that the picture of the actual traffic situation is not a real one. This deficiency is corrected by floating cars, which retrieve dynamic information on the traffic situation. Unfortunately, the number of floating data vehicles currently available is too small and insufficient to give a complete picture of the road traffic. In this paper, we present a floating car data (FCD) augmentation system that combines information fromfloating data vehicles and infrastructure sensors, and that, by using neural networks, is capable of incrementing the amount of FCD with virtual information. This system has been implemented and tested on actual roads, and the results show little difference between the data supplied by the floating vehicles and the virtual vehicles.