Design and assessment of a large commercial Photovoltaic System in Barbados

One of the main aims of this thesis is to design an optimized commercial Photovoltaic (PV) system in Barbados from several variables such as racking type, module type and inverter type based on practicality, technical performance as well as financial returns to the client. Detailed simulations are done in PVSYST and financial models are used to compare different systems and their viability. Once the preeminent system is determined from a financial and performance perspective a detailed design is done using PVSYST and AutoCAD to design the most optimal PV system for the customer. In doing so, suitable engineering drawings are generated which are detailed enough for construction of the system. Detailed cost with quotes from relevant manufacturers, suppliers and estimators become instrumental in determining Balance of System Costs in addition to total project cost. The final simulated system is suggested with a PV capacity of 425kW and an inverter output of 300kW resulting in an array oversizing of 1.42. The PV system has a weighted Performance Ratio of 77 %, a specific yield of 1467 kWh/kWp and a projected annual production of 624 MWh/yr. This system is estimated to offset approximately 28 % of Carlton’s electrical load annually. Over the course of 20 years the PV system is projected to produce electricity at a cost of $0.201USD/kWh which is significantly lower than the $0.35 USD/kWh paid to the utility at the time of writing this thesis. Due to the high cost of electricity on the island, an attractive Feed-In-Tariff is not necessary to warrant the installation of a commercial System which over a lifetime which produces electricity at less than 60% of the cost to the user purchasing electricity from the utility. A simple payback period of 5.4 years, a return on investment of 17 % without incentives, in addition to an estimated diversion of 6840 barrels of oil or 2168 tonnes of CO2 further provides compelling justification for the installation of a commercial Photovoltaic System not only on Carlton A-1 Supermarket, but also island wide as well as regionally where most electricity supplies are from imported fossil fuels.

Experimental and computational investigation of the roll forming process

One of the first questions to consider when designing a new roll forming line is the number of forming steps required to produce a profile. The number depends on material properties, the cross-section geometry and tolerance requirements, but the tool designer also wants to minimize the number of forming steps in order to reduce the investment costs for the customer. There are several computer aided engineering systems on the market that can assist the tool designing process. These include more or less simple formulas to predict deformation during forming as well as the number of forming steps. In recent years it has also become possible to use finite element analysis for the design of roll forming processes. The objective of the work presented in this thesis was to answer the following question: How should the roll forming process be designed for complex geometries and/or high strength steels? The work approach included both literature studies as well as experimental and modelling work. The experimental part gave direct insight into the process and was also used to develop and validate models of the process. Starting with simple geometries and standard steels the work progressed to more complex profiles of variable depth and width, made of high strength steels. The results obtained are published in seven papers appended to this thesis. In the first study (see paper 1) a finite element model for investigating the roll forming of a U-profile was built. It was used to investigate the effect on longitudinal peak membrane strain and deformation length when yield strength increases, see paper 2 and 3. The simulations showed that the peak strain decreases whereas the deformation length increases when the yield strength increases. The studies described in paper 4 and 5 measured roll load, roll torque, springback and strain history during the U-profile forming process. The measurement results were used to validate the finite element model in paper 1. The results presented in paper 6 shows that the formability of stainless steel (e.g. AISI 301), that in the cold rolled condition has a large martensite fraction, can be substantially increased by heating the bending zone. The heated area will then become austenitic and ductile before the roll forming. Thanks to the phenomenon of strain induced martensite formation, the steel will regain the martensite content and its strength during the subsequent plastic straining. Finally, a new tooling concept for profiles with variable cross-sections is presented in paper 7. The overall conclusions of the present work are that today, it is possible to successfully develop profiles of complex geometries (3D roll forming) in high strength steels and that finite element simulation can be a useful tool in the design of the roll forming process.

Modeling and forecasting long-term natural gas (NG) consumption in Iran, using particle swarm optimization (PSO)

The gradual changes in the world development have brought energy issues back into high profile. An ongoing challenge for countries around the world is to balance the development gains against its effects on the environment. The energy management is the key factor of any sustainable development program. All the aspects of development in agriculture, power generation, social welfare and industry in Iran are crucially related to the energy and its revenue. Forecasting end-use natural gas consumption is an important Factor for efficient system operation and a basis for planning decisions. In this thesis, particle swarm optimization (PSO) used to forecast long run natural gas consumption in Iran. Gas consumption data in Iran for the previous 34 years is used to predict the consumption for the coming years. Four linear and nonlinear models proposed and six factors such as Gross Domestic Product (GDP), Population, National Income (NI), Temperature, Consumer Price Index (CPI) and yearly Natural Gas (NG) demand investigated.

Prediction Of Hydrological Models’ Uncertainty By A Committee Of Machine Learning-Models

This study presents an approach to combine uncertainties of the hydrological model outputs predicted from a number of machine learning models. The machine learning based uncertainty prediction approach is very useful for estimation of hydrological models' uncertainty in particular hydro-metrological situation in real-time application [1]. In this approach the hydrological model realizations from Monte Carlo simulations are used to build different machine learning uncertainty models to predict uncertainty (quantiles of pdf) of the a deterministic output from hydrological model . Uncertainty models are trained using antecedent precipitation and streamflows as inputs. The trained models are then employed to predict the model output uncertainty which is specific for the new input data. We used three machine learning models namely artificial neural networks, model tree, locally weighted regression to predict output uncertainties. These three models produce similar verification results, which can be improved by merging their outputs dynamically. We propose an approach to form a committee of the three models to combine their outputs. The approach is applied to estimate uncertainty of streamflows simulation from a conceptual hydrological model in the Brue catchment in UK and the Bagmati catchment in Nepal. The verification results show that merged output is better than an individual model output. [1] D. L. Shrestha, N. Kayastha, and D. P. Solomatine, and R. Price. Encapsulation of parameteric uncertainty statistics by various predictive machine learning models: MLUE method, Journal of Hydroinformatic, in press, 2013.

Model Configuration And Data Management In The Short-Term Water Information Forecasting Tools

The Short-term Water Information and Forecasting Tools (SWIFT) is a suite of tools for flood and short-term streamflow forecasting, consisting of a collection of hydrologic model components and utilities. Catchments are modeled using conceptual subareas and a node-link structure for channel routing. The tools comprise modules for calibration, model state updating, output error correction, ensemble runs and data assimilation. Given the combinatorial nature of the modelling experiments and the sub-daily time steps typically used for simulations, the volume of model configurations and time series data is substantial and its management is not trivial. SWIFT is currently used mostly for research purposes but has also been used operationally, with intersecting but significantly different requirements. Early versions of SWIFT used mostly ad-hoc text files handled via Fortran code, with limited use of netCDF for time series data. The configuration and data handling modules have since been redesigned. The model configuration now follows a design where the data model is decoupled from the on-disk persistence mechanism. For research purposes the preferred on-disk format is JSON, to leverage numerous software libraries in a variety of languages, while retaining the legacy option of custom tab-separated text formats when it is a preferred access arrangement for the researcher. By decoupling data model and data persistence, it is much easier to interchangeably use for instance relational databases to provide stricter provenance and audit trail capabilities in an operational flood forecasting context. For the time series data, given the volume and required throughput, text based formats are usually inadequate. A schema derived from CF conventions has been designed to efficiently handle time series for SWIFT.

Optimized Water Demand Management Through Intelligent Sensing And Analytics: The WISDOM Approach

New business and technology platforms are required to sustainably manage urban water resources [1,2]. However, any proposed solutions must be cognisant of security, privacy and other factors that may inhibit adoption and hence impact. The FP7 WISDOM project (funded by the European Commission - GA 619795) aims to achieve a step change in water and energy savings via the integration of innovative Information and Communication Technologies (ICT) frameworks to optimize water distribution networks and to enable change in consumer behavior through innovative demand management and adaptive pricing schemes [1,2,3]. The WISDOM concept centres on the integration of water distribution, sensor monitoring and communication systems coupled with semantic modelling (using ontologies, potentially connected to BIM, to serve as intelligent linkages throughout the entire framework) and control capabilities to provide for near real-time management of urban water resources. Fundamental to this framework are the needs and operational requirements of users and stakeholders at domestic, corporate and city levels and this requires the interoperability of a number of demand and operational models, fed with data from diverse sources such as sensor networks and crowsourced information. This has implications regarding the provenance and trustworthiness of such data and how it can be used in not only the understanding of system and user behaviours, but more importantly in the real-time control of such systems. Adaptive and intelligent analytics will be used to produce decision support systems that will drive the ability to increase the variability of both supply and consumption [3]. This in turn paves the way for adaptive pricing incentives and a greater understanding of the water-energy nexus. This integration is complex and uncertain yet being typical of a cyber-physical system, and its relevance transcends the water resource management domain. The WISDOM framework will be modeled and simulated with initial testing at an experimental facility in France (AQUASIM – a full-scale test-bed facility to study sustainable water management), then deployed and evaluated in in two pilots in Cardiff (UK) and La Spezia (Italy). These demonstrators will evaluate the integrated concept providing insight for wider adoption.

A study on time-varying quantile and its applications

This Thesis is the result of my Master Degree studies at the Graduate School of Economics, Getúlio Vargas Foundation, from January 2004 to August 2006. am indebted to my Thesis Advisor, Professor Luiz Renato Lima, who introduced me to the Econometrics' world. In this Thesis, we study time-varying quantile process and we develop two applications, which are presented here as Part and Part II. Each of these parts was transformed in paper. Both papers were submitted. Part shows that asymmetric persistence induces ARCH effects, but the LMARCH test has power against it. On the other hand, the test for asymmetric dynamics proposed by Koenker and Xiao (2004) has correct size under the presence of ARCH errors. These results suggest that the LM-ARCH and the Koenker-Xiao tests may be used in applied research as complementary tools. In the Part II, we compare four different Value-at-Risk (VaR) methodologies through Monte Cario experiments. Our results indicate that the method based on quantile regression with ARCH effect dominates other methods that require distributional assumption. In particular, we show that the non-robust method ologies have higher probability to predict VaRs with too many violations. We illustrate our findings with an empirical exercise in which we estimate VaR for returns of São Paulo stock exchange index, IBOVESPA, during periods of market turmoil. Our results indicate that the robust method based on quantile regression presents the least number of violations.

Tests of conditional asset pricing models in the brazilian stock market

In this paper, we test a version of the conditional CAPM with respect to a local market portfolio, proxied by the Brazilian stock index during the period 1976-1992. We also test a conditional APT modeI by using the difference between the 3-day rate (Cdb) and the overnight rate as a second factor in addition to the market portfolio in order to capture the large inflation risk present during this period. The conditional CAPM and APT models are estimated by the Generalized Method of Moments (GMM) and tested on a set of size portfolios created from individual securities exchanged on the Brazilian markets. The inclusion of this second factor proves to be important for the appropriate pricing of the portfolios.

Trade and infrastructure: evidences from the Andean Community

This paper presents evidence on the key role of infrastructure in the Andean Community trade patterns. Three distinct but related gravity models of bilateral trade are used. The first model aims at identifying the importance of the Preferential Trade Agreement and adjacency on intra-regional trade, while also checking the traditional roles of economic size and distance. The second and third models also assess the evolution of the Trade Agreement and the importance of sharing a common border, but their main goal is to analyze the relevance of including infrastructure in the augmented gravity equation, testing the theoretical assumption that infrastructure endowments, by reducing trade and transport costs, reduce “distance” between bilateral partners. Indeed, if one accepts distance as a proxy for transportation costs, infrastructure development and improvement drastically modify it. Trade liberalization eliminates most of the distortions that a protectionist tariff system imposes on international business; hence transportation costs represent nowadays a considerably larger barrier to trade than in past decades. As new trade pacts are being negotiated in the Americas, borders and old agreements will lose significance; trade among countries will be nearly without restrictions, and bilateral flows will be defined in terms of costs and competitiveness. Competitiveness, however, will only be achieved by an improvement in infrastructure services at all points in the production-distribution chain.

Past and future of the bankruptcy law in Brazil and Latin America

This paper studies the Bankruptcy Law in Latin America, focusing on the Brazilian reform. We start with a review of the international literature and its evolution on this subject. Next, we examine the economic incentives associated with several aspects of bankruptcy laws and insolvency procedures in general, as well as the trade-offs involved. After this theoretical discussion, we evaluate empirically the current stage of the quality of insolvency procedures in Latin America using data from Doing Business and World Development Indicators, both from World Bank and International Financial Statistics from IMF. We find that the region is governed by an inefficient law, even when compared with regions of lower per capita income. As theoretical and econometric models predict, this inefficiency has severe consequences for credit markets and the cost of capital. Next, we focus on the recent Brazilian bankruptcy reform, analyzing its main changes and possible effects over the economic environment. The appendix describes difficulties of this process of reform in Brazil, and what other Latin American countries can possibly learn from it.

Verificação da existência de assimetria de informação no processo de emissão de ações no mercado brasileiro

O presente estudo busca realizar uma revisão bibliográfica sobre Assimetria de Informação, de forma a permitir sua análise no mercado brasileiro de capitais. A análise será conduzida com base no modelo de equilíbrio da decisão de emissão-investimento desenvolvido por Myers e Majluf. Este trabalho procurará discutir novas formas de medir Assimetria de Informação através da utilização de modelos estatísticos que permitam, posteriormente, utilizar modelos tais como ARCH e GARCH que consideram a heterocedasticidade da série de dados, desta forma, ampliando o conceito de medida correta sugerido por Nathalie Dierkens.

Análise da volatilidade de preço do mercado da borracha natural

O foco central deste estudo foi desenvolver uma análise da trajetória dos prsços da borracha natural bensflciada ao longo do século XX, através da utilização dos testes econométricos da dasse - ARCH: GARCH, E-GARCH e TARCH para o da Malásia, principal entidade de formação do preço intemacional da commodity. Como resultado dos testes estatísticos dos dados disponíveis no mercado, observouse uma forte incidência de ciclos de sazonalidade no preço intemacional da borracha impactando diretamente na produção mundial. Observa se ainda a baixa capacidade de resposta da produção a choques de demanda devido ao longo prazo de maturação das pfantações

A study of behavioral finance: background, theories and application

Behavioral finance, or behavioral economics, consists of a theoretical field of research stating that consequent psychological and behavioral variables are involved in financial activities such as corporate finance and investment decisions (i.e. asset allocation, portfolio management and so on). This field has known an increasing interest from scholar and financial professionals since episodes of multiple speculative bubbles and financial crises. Indeed, practical incoherencies between economic events and traditional neoclassical financial theories had pushed more and more researchers to look for new and broader models and theories. The purpose of this work is to present the field of research, still ill-known by a vast majority. This work is thus a survey that introduces its origins and its main theories, while contrasting them with traditional finance theories still predominant nowadays. The main question guiding this work would be to see if this area of inquiry is able to provide better explanations for real life market phenomenon. For that purpose, the study will present some market anomalies unsolved by traditional theories, which have been recently addressed by behavioral finance researchers. In addition, it presents a practical application of portfolio management, comparing asset allocation under the traditional Markowitz’s approach to the Black-Litterman model, which incorporates some features of behavioral finance.

Prevendo a volatilidade realizada de ações brasileiras : evidências empíricas

Este estudo compara previsões de volatilidade de sete ações negociadas na Bovespa usando 02 diferentes modelos de volatilidade realizada e 03 de volatilidade condicional. A intenção é encontrar evidências empíricas quanto à diferença de resultados que são alcançados quando se usa modelos de volatilidade realizada e de volatilidade condicional para prever a volatilidade de ações no Brasil. O período analisado vai de 01 de Novembro de 2007 a 30 de Março de 2011. A amostra inclui dados intradiários de 5 minutos. Os estimadores de volatilidade realizada que serão considerados neste estudo são o Bi-Power Variation (BPVar), desenvolvido por Barndorff-Nielsen e Shephard (2004b), e o Realized Outlyingness Weighted Variation (ROWVar), proposto por Boudt, Croux e Laurent (2008a). Ambos são estimadores não paramétricos, e são robustos a jumps. As previsões de volatilidade realizada foram feitas através de modelos autoregressivos estimados para cada ação sobre as séries de volatilidade estimadas. Os modelos de variância condicional considerados aqui serão o GARCH(1,1), o GJR (1,1), que tem assimetrias em sua construção, e o FIGARCH-CHUNG (1,d,1), que tem memória longa. A amostra foi divida em duas; uma para o período de estimação de 01 de Novembro de 2007 a 30 de Dezembro de 2010 (779 dias de negociação) e uma para o período de validação de 03 de Janeiro de 2011 a 31 de Março de 2011 (61 dias de negociação). As previsões fora da amostra foram feitas para 1 dia a frente, e os modelos foram reestimados a cada passo, incluindo uma variável a mais na amostra depois de cada previsão. As previsões serão comparadas através do teste Diebold-Mariano e através de regressões da variância ex-post contra uma constante e a previsão. Além disto, o estudo também apresentará algumas estatísticas descritivas sobre as séries de volatilidade estimadas e sobre os erros de previsão.

Risky business: social media metrics and political risk analysis

A quantificação do risco país – e do risco político em particular – levanta várias dificuldades às empresas, instituições, e investidores. Como os indicadores econômicos são atualizados com muito menos freqüência do que o Facebook, compreender, e mais precisamente, medir – o que está ocorrendo no terreno em tempo real pode constituir um desafio para os analistas de risco político. No entanto, com a crescente disponibilidade de “big data” de ferramentas sociais como o Twitter, agora é o momento oportuno para examinar os tipos de métricas das ferramentas sociais que estão disponíveis e as limitações da sua aplicação para a análise de risco país, especialmente durante episódios de violência política. Utilizando o método qualitativo de pesquisa bibliográfica, este estudo identifica a paisagem atual de dados disponíveis a partir do Twitter, analisa os métodos atuais e potenciais de análise, e discute a sua possível aplicação no campo da análise de risco político. Depois de uma revisão completa do campo até hoje, e tendo em conta os avanços tecnológicos esperados a curto e médio prazo, este estudo conclui que, apesar de obstáculos como o custo de armazenamento de informação, as limitações da análise em tempo real, e o potencial para a manipulação de dados, os benefícios potenciais da aplicação de métricas de ferramentas sociais para o campo da análise de risco político, particularmente para os modelos qualitativos-estruturados e quantitativos, claramente superam os desafios.