Effects of flooding of the River Paraná on the temporal activity of Anopheles (Nyssorhynchus) darlingi Root (Diptera: Culicidae), at the border state of Mato Grosso do Sul and São Paulo, Brazil

INTRODUCTION: Study of the temporal activity of malaria vectors during the implantation of a hydroelectric power station on the River Paraná, intended to generate electrical energy. The river separates the States of São Paulo and Mato Grosso do Sul, in Brazil. The objective was to verify whether alterations occurred in the wealth and diversity indices of Anopheles, following two successive floods, extended to the temporal activity and nycthemeral rhythm followed over a five year period. METHODS: Mosquito capture was performed monthly using the Human Attraction Technique and Shannon Traps. The first, executed for 24h, provided the nycthemeral rhythm and the second, lasting 15h, permitted the tracking of Anopheles during the two floods. RESULTS: The bimodal pattern of Anopheles darlingi defined before these floods was modified throughout the environment interventions. The same effect had repercussions on the populations of An albitarsis s.l., An triannulatus and An galvaoi. Activity prior to twilight was less affected by the environment alterations. CONCLUSIONS: The dam construction provoked changes in Anopheles temporal activity patterns, permitting classification of the area as an ecologically steady and unstable situation. Differences observed in Anopheles behavior due to the capture methods revealed the influence of solo and multiple attractiveness inside the populations studied.

Functional characterization and directed engineering of redox proteins for a rational improvement of Bioelectrochemical systems

In recent years, new methods of clean and environmentally friendly energy production have been the focus of intense research efforts. Microbial fuel cells (MFCs) are devices that utilize naturally occurring microorganisms that feed on organic matter, like waste water, while producing electrical energy. The natural habitats of bacteria thriving in microbial fuel cells are usually marine and freshwater sediments. These microorganisms are called dissimilatory metal reducing bacteria (DMRB), but in addition to metals like iron and manganese, they can use organic compounds like DMSO or TMAO, radionuclides and electrodes as terminal electron acceptors in their metabolic pathways.(...)

Prospective system analysis of stationary battery systems under the frame of Constructive Technology Assessment

Based on the report for the unit “Project IV” of the PhD programme on Technology Assessment under the supervision of Dr.-Ing. Marcel Weil and Prof. Dr. António Brandão Moniz. The report was presented and discussed at the Doctorate Conference on Technologogy Assessment in July 2013 at the University Nova Lisboa, Caparica campus.

Experimental and modeling studies on reverse electrodialysis for sustainable power generation

A potentially renewable and sustainable source of energy is the chemical energy associated with solvation of salts. Mixing of two aqueous streams with different saline concentrations is spontaneous and releases energy. The global theoretically obtainable power from salinity gradient energy due to World’s rivers discharge into the oceans has been estimated to be within the range of 1.4-2.6 TW. Reverse electrodialysis (RED) is one of the emerging, membrane-based, technologies for harvesting the salinity gradient energy. A common RED stack is composed by alternately-arranged cation- and anion-exchange membranes, stacked between two electrodes. The compartments between the membranes are alternately fed with concentrated (e.g., sea water) and dilute (e.g., river water) saline solutions. Migration of the respective counter-ions through the membranes leads to ionic current between the electrodes, where an appropriate redox pair converts the chemical salinity gradient energy into electrical energy. Given the importance of the need for new sources of energy for power generation, the present study aims at better understanding and solving current challenges, associated with the RED stack design, fluid dynamics, ionic mass transfer and long-term RED stack performance with natural saline solutions as feedwaters. Chronopotentiometry was used to determinate diffusion boundary layer (DBL) thickness from diffusion relaxation data and the flow entrance effects on mass transfer were found to avail a power generation increase in RED stacks. Increasing the linear flow velocity also leads to a decrease of DBL thickness but on the cost of a higher pressure drop. Pressure drop inside RED stacks was successfully simulated by the developed mathematical model, in which contribution of several pressure drops, that until now have not been considered, was included. The effect of each pressure drop on the RED stack performance was identified and rationalized and guidelines for planning and/or optimization of RED stacks were derived. The design of new profiled membranes, with a chevron corrugation structure, was proposed using computational fluid dynamics (CFD) modeling. The performance of the suggested corrugation geometry was compared with the already existing ones, as well as with the use of conductive and non-conductive spacers. According to the estimations, use of chevron structures grants the highest net power density values, at the best compromise between the mass transfer coefficient and the pressure drop values. Finally, long-term experiments with natural waters were performed, during which fouling was experienced. For the first time, 2D fluorescence spectroscopy was used to monitor RED stack performance, with a dedicated focus on following fouling on ion-exchange membrane surfaces. To extract relevant information from fluorescence spectra, parallel factor analysis (PARAFAC) was performed. Moreover, the information obtained was then used to predict net power density, stack electric resistance and pressure drop by multivariate statistical models based on projection to latent structures (PLS) modeling. The use in such models of 2D fluorescence data, containing hidden, but extractable by PARAFAC, information about fouling on membrane surfaces, considerably improved the models fitting to the experimental data.

EDP - A new estimation algorithm

The aim of this work project is to analyze the current algorithm used by EDP to estimate their clients’ electrical energy consumptions, create a new algorithm and compare the advantages and disadvantages of both. This new algorithm is different from the current one as it incorporates some effects from temperature variations. The results of the comparison show that this new algorithm with temperature variables performed better than the same algorithm without temperature variables, although there is still potential for further improvements of the current algorithm, if the prediction model is estimated using a sample of daily data, which is the case of the current EDP algorithm.

Control in distribution networks with demand side management

The way in which electricity networks operate is going through a period of significant change. Renewable generation technologies are having a growing presence and increasing penetrations of generation that are being connected at distribution level. Unfortunately, a renewable energy source is most of the time intermittent and needs to be forecasted. Current trends in Smart grids foresee the accommodation of a variety of distributed generation sources including intermittent renewable sources. It is also expected that smart grids will include demand management resources, widespread communications and control technologies required to use demand response are needed to help the maintenance in supply-demand balance in electricity systems. Consequently, smart household appliances with controllable loads will be likely a common presence in our homes. Thus, new control techniques are requested to manage the loads and achieve all the potential energy present in intermittent energy sources. This thesis is focused on the development of a demand side management control method in a distributed network, aiming the creation of greater flexibility in demand and better ease the integration of renewable technologies. In particular, this work presents a novel multi-agent model-based predictive control method to manage distributed energy systems from the demand side, in presence of limited energy sources with fluctuating output and with energy storage in house-hold or car batteries. Specifically, here is presented a solution for thermal comfort which manages a limited shared energy resource via a demand side management perspective, using an integrated approach which also involves a power price auction and an appliance loads allocation scheme. The control is applied individually to a set of Thermal Control Areas, demand units, where the objective is to minimize the energy usage and not exceed the limited and shared energy resource, while simultaneously indoor temperatures are maintained within a comfort frame. Thermal Control Areas are overall thermodynamically connected in the distributed environment and also coupled by energy related constraints. The energy split is performed based on a fixed sequential order established from a previous completed auction wherein the bids are made by each Thermal Control Area, acting as demand side management agents, based on the daily energy price. The developed solutions are explained with algorithms and are applied to different scenarios, being the results explanatory of the benefits of the proposed approaches.

Coupling organic substrate removal to methane production in a fully biological microbial electrolysis cell

Microbial electrolysis cells (MECs) are an innovative and emerging technique based on the use of solid-state electrodes to stimulate microbial metabolism for wastewater treatment and simultaneous production of value-added compounds (such as methane). This research studied the performance of a two-chamber MEC in terms of organic matter oxidation (at the anode) and methane production (at the cathode). MEC‟s anode had been previously inoculated with an activated sludge, whereas the cathode chamber inoculum was an anaerobic sludge (containing methanogenic microorganisms). During the experimentation, the bioanode was continuously fed with synthetic solutions in anaerobic basal medium, at an organic load rate (OLR) of around 1 g L-1 d-1, referred to the chemical oxygen demand (COD). At the beginning (Run I), the feeding solution contained acetate and subsequently (Run II) it was replaced with a more complex solution containing soluble organic compounds other than acetate. For both conditions, the anode potential was controlled at -0.1 V vs. standard hydrogen electrode, by means of a potentiostat. During Run I, over 80% of the influent acetate was anaerobically oxidized at the anode, and the resulting electric current was recovered as methane at the cathode (with a cathode capture efficiency, CCE, accounting around 115 %). The average energy efficiency of the system (i.e., the energy captured into methane relative to the electrical energy input) under these conditions was over 170%. However, reactor‟s performance decreased over time during this run. Throughout Run II, a substrate oxidation over 60% (on COD basis) was observed. The electric current produced (57% of coulombic efficiency) was also recovered as methane, with a CCE of 90%. For this run the MEC‟s average energy efficiency accounted for almost 170 %. During all the experimentation, a very low biomass growth was observed at the anode whereas ammonium was transferred through the cationic membrane and concentrated at the cathode. Tracer experiments and scanning electron microscopy analyses were also carried out to gain a deeper insight into the reactor performance and also to investigate the possible reasons for partial loss of performance. In conclusion, this research suggests the great potential of MEC to successfully treat low-strength wastewaters, with high energy efficiency and very low sludge production.

Smart platform towards batteries analysis based on internet-of-things

This paper presents a new approach of pre-defined profiles, based in different voltage and current values, to control the charging and discharging processes of batteries in order to assess their performance. This new approach was implemented in a prototype that was specially developed for such purpose. This prototype is a smart power electronics platform that allows to perform batteries analysis and to control the charging and discharging processes through a web application using pre-defined profiles. This platform was developed aiming to test different batteries technologies. Considering the relevance of the energy storage area based in batteries, especially for the batteries applied to electric mobility systems, this platform allows to perform controlled tests to the batteries, in order to analyze the batteries performance under different scenarios of operation. Besides the results obtained with the batteries, this work also intends to produce results that can contribute to an involvement in the strengthening of the Internet-of-Things.

Dynamic range prediction for an electric vehicle

Electric Vehicles (EVs) have limited energy storage capacity and the maximum autonomy range is strongly dependent of the driver's behaviour. Due to the fact of that batteries cannot be recharged quickly during a journey, it is essential that a precise range prediction is available to the driver of the EV. With this information, it is possible to check if the desirable destination is achievable without a stop to charge the batteries, or even, if to reach the destination it is necessary to perform an optimized driving (e.g., cutting the air-conditioning, among others EV parameters). The outcome of this research work is the development of an Electric Vehicle Assistant (EVA). This is an application for mobile devices that will help users to take efficient decisions about route planning, charging management and energy efficiency. Therefore, it will contribute to foster EVs adoption as a new paradigm in the transportation sector.

Predictive control of a current-source inverter for solar photovoltaic grid interface

Solar photovoltaic systems are an increasing option for electricity production, since they produce electrical energy from a clean renewable energy resource, and over the years, as a result of the research, their efficiency has been increasing. For the interface between the dc photovoltaic solar array and the ac electrical grid is necessary the use of an inverter (dc-ac converter), which should be optimized to extract the maximum power from the photovoltaic solar array. In this paper is presented a solution based on a current-source inverter (CSI) using continuous control set model predictive control (CCS-MPC). All the power circuits and respective control systems are described in detail along the paper and were tested and validated performing computer simulations. The paper shows the simulation results and are drawn several conclusions.

Advances and future challenges in printed batteries

There is an increasing interest in thin and flexible energy storage devices to meet modern society needs for applications such as, radio frequency sensing, interactive packaging and other consumer products. Printed batteries comply these requirements and are an excellent alternative to conventional batteries for many applications. Flexible and micro-batteries are also included in the area of printed batteries whenever fabricated by printing technologies. The main characteristics, advantages, disadvantages, developments, and printing techniques of printed batteries are presented and discussed in this review. The state-of-art takes into account both the research and industrial levels. In the academic one, the research progress of printed batteries is summarized divided in lithium-ion battery (Li-ion), zinc-manganese dioxide (Zn-MnO2), and other battery types with emphasis on the different materials for anode, cathode and separator as well as in the battery design. With respect to the industrial state-of-art, materials, device formulations and manufacturing techniques are presented. Finally, the prospects and challenges of printed batteries are discussed.

Desenvolvimento de um concentrador solar com sistema de seguimento

Dissertação de mestrado em Engenharia Mecânica

Desenvolvimento de um Posto de Carregamento Lento com BMS e Interface com o Cockpit para o CEPIUM

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e de Computadores

Desenvolvimento de um Range Extender para Veículo Elétrico

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e de Computadores