PV inverters for module level applications

Dissertação para obtenção do Grau de Mestre em Energias Renováveis – Conversão Eléctrica e Utilização Sustentáveis

Environmental impact assessment of energy crops cultivation in the Mediterranean Europe

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa Para a obtenção do Grau de Mestre em Energia e Bioenergia

Structural and functional studies of a high activity NiFeSe Hydrogenase

Theawareness that fossil fuels exist in limited quantities has stimulated research into energy production from renewable sources. Future energy sources! should! be! plentiful! with! negligible! impact! on! the! environment.! Hydrogen!has!the!potential!to!satisfy!these!requirements.!Nevertheless,!current! methods! of! H2! production! rely! on! nonOrenewable! resources.! Biological! H2! production! from! sunlight! or! biomass! is! an! appealing! alternative! to! current! production!methods.!!(...)

SDAR: a package for plotting and analyzing stratigraphy data in R

Stratigraphic Columns (SC) are the most useful and common ways to represent the eld descriptions (e.g., grain size, thickness of rock packages, and fossil and lithological components) of rock sequences and well logs. In these representations the width of SC vary according to the grain size (i.e., the wider the strata, the coarser the rocks (Miall 1990; Tucker 2011)), and the thickness of each layer is represented at the vertical axis of the diagram. Typically these representations are drawn 'manually' using vector graphic editors (e.g., Adobe Illustrator®, CorelDRAW®, Inskape). Nowadays there are various software which automatically plot SCs, but there are not versatile open-source tools and it is very di cult to both store and analyse stratigraphic information. This document presents Stratigraphic Data Analysis in R (SDAR), an analytical package1 designed for both plotting and facilitate the analysis of Stratigraphic Data in R (R Core Team 2014). SDAR, uses simple stratigraphic data and takes advantage of the exible plotting tools available in R to produce detailed SCs. The main bene ts of SDAR are: (i) used to generate accurate and complete SC plot including multiple features (e.g., sedimentary structures, samples, fossil content, color, structural data, contacts between beds), (ii) developed in a free software environment for statistical computing and graphics, (iii) run on a wide variety of platforms (i.e., UNIX, Windows, and MacOS), (iv) both plotting and analysing functions can be executed directly on R's command-line interface (CLI), consequently this feature enables users to integrate SDAR's functions with several others add-on packages available for R from The Comprehensive R Archive Network (CRAN).

Post-merger innovative performance in the renewable energy sector

Due to global warming and shrinking fossil fuel resources, politics as well as society urge for a reduction of green house gas (GHG) emissions. This leads to a re-orientation towards a renewable energy sector. In this context, innovation and new technologies are key success factors. Moreover, the renewable energy sector has entered a consolidation stage, where corporate investors and mergers and acquisitions (M&A) gain in importance. Although both M&A and innovation in the renewable energy sector are important corporate strategies, the link between those two aspects has not been examined before. The present thesis examines the research question how M&A influence the acquirer’s post-merger innovative performance in the renewable energy sector. Based on a framework of relevant literature, three hypotheses are defined. First, the relation between non-technology oriented M&A and post-merger innovative performance is discussed. Second, the impact of absolute acquired knowledge on postmerger innovativeness is examined. Third, the target-acquirer relatedness is discussed. A panel data set of 117 firms collected over a period of six years has been analyzed via a random effects negative binomial regression model and a time lag of one year. The results support a non-significant, negative impact of non-technology M&A on postmerger innovative performance. The applied model did not support a positive and significant impact of absolute acquired knowledge on post-merger innovative performance. Lastly, the results suggest a reverse relation than postulated by Hypothesis 3. Targets from the same industry significantly and negatively influence the acquirers’ innovativeness.

An agent-based simulator to estimate domestic energy use

Throughout recent years, there has been an increase in the population size, as well as a fast economic growth, which has led to an increase of the energy demand that comes mainly from fossil fuels. In order to reduce the ecological footprint, governments have implemented sustainable measures and it is expected that by 2035 the energy produced from renewable energy sources, such as wind and solar would be responsible for one-third of the energy produced globally. However, since the energy produced from renewable sources is governed by the availability of the respective primary energy source there is often a mismatch between production and demand, which could be solved by adding flexibility on the demand side through demand response (DR). DR programs influence the end-user electricity usage by changing its cost along the time. Under this scenario the user needs to estimate the energy demand and on-site production in advance to plan its energy demand according to the energy price. This work focuses on the development of an agent-based electrical simulator, capable of: (a) estimating the energy demand and on-site generation with a 1-min time resolution for a 24-h period, (b) calculating the energy price for a given scenario, (c) making suggestions on how to maximize the usage of renewable energy produced on-site and to lower the electricity costs by rescheduling the use of certain appliances. The results show that this simulator allows reducing the energy bill by 11% and almost doubling the use of renewable energy produced on-site.

Bioproduction of succinic acid from renewable feedstocks by Actinobacillus succinogenes 130Z

Succinic acid (SA) is a highly versatile building block that is used in a wide range of industrial applications. The biological production of succinic acid has emerged in the last years as an efficient alternative to the chemical production based on fossil fuels. However, in order to fully replace the competing petro-based chemical process from which it has been produced so far, some challenges remain to be surpassed. In particular, one main obstacle would be to reduce its production costs, mostly associated to the use of refined sugars. The present work is focused on the development of a sustainable and cost-e↵ective microbial production process based on cheap and renewable resources, such as agroindustrial wastes. Hence, glycerol and carob pods were identified as promising feedstocks and used as inexpensive carbon sources for the bioproduction of succinic acid by Actinobacillus succinogenes 130Z, one of the best naturally producing strains. Even though glycerol is a highly available carbon source, as by-product of biodiesel production, its consumption by A. succinogenes is impaired due to a redox imbalance during cell growth. However, the use of an external electron acceptor such as dimethylsulfoxide (DMSO) may improve glycerol metabolism and succinic acid production by this strain. As such, DMSO was tested as a co-substrate for glycerol consumption and concentrations of DMSO between 1 and 4% (v/v) greatly promoted glycerol consumption and SA production by this biocatalyst. Aiming at obtaining higher succinic acid yield and production rate, batch and fed-batch experiments were performed under controlled cultivation conditions. Batch experiments resulted in a succinic acid yield on glycerol of 0.95 g SA/g GLY and a production rate of 2.13 g/L.h, with residual production of acetic and formic acids. In fed-batch experiment, the SA production rate reached 2.31 g/L.h, the highest value reported in the literature for A. succinogenes using glycerol as carbon source. DMSO dramatically improved the conversion of glycerol by A. succinogenes and may be used as a co-substrate, opening new perspectives for the use of glycerol by this biocatalyst. Carob pods, highly available in Portugal as a residue from the locust bean gum industry, contain a significant amount of fermentable sugars such as sucrose, glucose and fructose and were also used as substrate for succinic acid production. Sugar extraction from raw and roasted carobs was optimized varying solid/water ratio and extraction time, maximizing sugar recovery while minimizing the extraction of polyphenols. Kinetic studies of glucose, fructose and sucrose consumption by A. succinogenes as individual carbon sources till 30 g/L were first determined to assess possible metabolic diferences. Results showed no significant diferences related to sugar consumption and SA production between the diferent sugars. Carob pods water extracts were then used as carbon source during controlled batch cultivations. (...)

Has the time for renewables finally arrived? – An event study on EPA’s Clean Power Plan

The recent proposals presented by EPA aimed to reduce the dependency of fossil fuels and to lower current emissions levels, hoping to gradually shift electric generation units to renewable energy sources. Actually, the Final Rule Proposal announcement day exhibited a negative Abnormal Return on Fossil Fuels but the following days had positive Abnormal Returns, mostly due to legislative change perceived by financial markets which eased up implementation periods of the proposed measures in the Final Rule when compared to the Draft Rule. Oppositely, Renewables and Solar Portfolios exhibited negative Cumulative Abnormal Returns over the period surrounding the Final Rule.