Stochastic Framework for Strategic Decision-making of Load-serving Entities for Day-ahead Market

The deregulation of electricity markets has diversified the range of financial transaction modes between independent system operator (ISO), generation companies (GENCO) and load-serving entities (LSE) as the main interacting players of a day-ahead market (DAM). LSEs sell electricity to end-users and retail customers. The LSE that owns distributed generation (DG) or energy storage units can supply part of its serving loads when the nodal price of electricity rises. This opportunity stimulates them to have storage or generation facilities at the buses with higher locational marginal prices (LMP). The short-term advantage of this model is reducing the risk of financial losses for LSEs in DAMs and its long-term benefit for the LSEs and the whole system is market power mitigation by virtually increasing the price elasticity of demand. This model also enables the LSEs to manage the financial risks with a stochastic programming framework.

Short-term Load Forecasting Based on Load Profiling

Load forecasting has gradually becoming a major field of research in electricity industry. Therefore, Load forecasting is extremely important for the electric sector under deregulated environment as it provides a useful support to the power system management. Accurate power load forecasting models are required to the operation and planning of a utility company, and they have received increasing attention from researches of this field study. Many mathematical methods have been developed for load forecasting. This work aims to develop and implement a load forecasting method for short-term load forecasting (STLF), based on Holt-Winters exponential smoothing and an artificial neural network (ANN). One of the main contributions of this paper is the application of Holt-Winters exponential smoothing approach to the forecasting problem and, as an evaluation of the past forecasting work, data mining techniques are also applied to short-term Load forecasting. Both ANN and Holt-Winters exponential smoothing approaches are compared and evaluated.

Stochastic Short-term Incentive-based Demand Response Scheduling of Load-serving Entities

In competitive electricity markets it is necessary for a profit-seeking load-serving entity (LSE) to optimally adjust the financial incentives offering the end users that buy electricity at regulated rates to reduce the consumption during high market prices. The LSE in this model manages the demand response (DR) by offering financial incentives to retail customers, in order to maximize its expected profit and reduce the risk of market power experience. The stochastic formulation is implemented into a test system where a number of loads are supplied through LSEs.

Multiagent System Architecture for Short-term Operation of Integrated Microgrids

The forthcoming smart grids are comprised of integrated microgrids operating in grid-connected and isolated mode with local generation, storage and demand response (DR) programs. The proposed model is based on three successive complementary steps for power transaction in the market environment. The first step is characterized as a microgrid’s internal market; the second concerns negotiations between distinct interconnected microgrids; and finally, the third refers to the actual electricity market. The proposed approach is modeled and tested using a MAS framework directed to the study of the smart grids environment, including the simulation of electricity markets. This is achieved through the integration of the proposed approach with the MASGriP (Multi-Agent Smart Grid Platform) system.

Using Typical Consumption Profiles to Stablish the Consumption Level for Short Time Periods

The current practices in the consumption metering by electricity utilities is currently largely based on monthly consumption reading. The consumption metering device is always calculating the cumulative consumption. Then, it is possible to calculate the difference between the actual and the previous consumption evaluation in order to estimate the monthly consumption. The power systems planning needs in many aspects to handle consumption data obtained for shorter periods, namely in the Demand Response programs planning. The work presented in this paper is based on the application of typical consumption profiles that are previously defined for a certain power system area. Such profiles are then used in order to estimate the 15 minutes consumption for a certain consumer or consumer type.

Short-term Wind Speed Forecasting using Support Vector Machines

Wind speed forecasting has been becoming an important field of research to support the electricity industry mainly due to the increasing use of distributed energy sources, largely based on renewable sources. This type of electricity generation is highly dependent on the weather conditions variability, particularly the variability of the wind speed. Therefore, accurate wind power forecasting models are required to the operation and planning of wind plants and power systems. A Support Vector Machines (SVM) model for short-term wind speed is proposed and its performance is evaluated and compared with several artificial neural network (ANN) based approaches. A case study based on a real database regarding 3 years for predicting wind speed at 5 minutes intervals is presented.

Toxicity screening of Diclofenac, Propranolol, Sertraline and Simvastatin using Danio rerio and Paracentrotus lividus embryo bioassays

Early life-stage bioassays have been used as an alternative to short-term adult toxicity tests since they are cost-effective. A single couple can produce hundreds or thousands of embryos and hence can be used as a simple high-throughput approach in toxicity studies. In the present study, zebrafish and sea urchin embryo bioassays were used to test the toxicity of four pharmaceuticals belonging to different therapeutic classes: diclofenac, propranolol, simvastatin and sertraline. Simvastatin was the most toxic tested compound for zebrafish embryo, followed by diclofenac. Sertraline was the most toxic drug to sea urchin embryos, inducing development abnormalities at the ng/L range. Overall, our results highlight the potential of sea urchin embryo bioassay as a promising and sensitive approach for the high-throughput methods to test the toxicity of new chemicals, including pharmaceuticals, and identify several drugs that should go through more detailed toxicity assays.

Estudo do óxido de cálcio como catalisador para a transesterificação de óleos alimentares usados

O instável mas tendencialmente crescente preço dos combustíveis associado a preocupações ambientais cada vez mais enraizadas nas sociedades, têm vindo a despoletar uma maior atenção à procura de combustíveis alternativos. Por outro lado, várias projecções indicam um aumento muito acentuado do consumo energético global no curto prazo, fruto do aumento da população e do nível de industrialização das sociedades. Neste contexto, o biodiesel (ésteres de ácidos gordos) obtido através da transesterificação de triglicerídeos de origem vegetal ou animal, surge como a alternativa “verde” mais viável para utilização em equipamentos de combustão. A reacção de transesterificação é catalisada, por norma com recurso a catalisadores homogéneos alcalinos (NaOH ou KOH). Este tipo de processo, o único actualmente com expressão a nível industrial, apresenta algumas desvantagens que, para além de aumentarem o custo do produto final, contribuem para reduzir a benignidade do mesmo: a impossibilidade de reutilização do catalisador, o aumento do número e complexidade das etapas de separação e a produção de efluentes resultantes das referidas etapas. Com o intuito de minimizar ou eliminar estes problemas, vários catalisadores heterogéneos têm vindo a ser estudados para esta reacção. Apesar de muitos apresentarem resultados promissores, a grande maioria não tem viabilidade para aplicação industrial seja devido ao seu próprio custo, seja devido aos pré-tratamentos necessários à sua utilização. Entre estes catalisadores, o óxido de cálcio é talvez o que apresenta resultados mais promissores. O crescente número de estudos envolvendo este catalisador em detrimento de outros, é por si mesmo prova do potencial do CaO. A realização deste trabalho pretendia atingir os seguintes objectivos principais: • Avaliar a elegibilidade do óxido de cálcio enquanto catalisador da reacção de transesterificação de óleos alimentares usados com metanol; • Avaliar qual a sua influência nas características dos produtos finais; • Avaliar as diferenças de performance entre o óxido de cálcio activado em atmosfera inerte (N2) e em ar, enquanto catalisadores da reacção de transesterificação de óleos alimentares usados com metanol; • Optimizar as condições da reacção com recurso às ferramentas matemáticas disponibilizadas pelo planeamento factorial, através da variação de quatro factores chave de influência: temperatura, tempo, relação metanol / óleo e massa de catalisador utilizado. O CaO utlizado foi obtido a partir de carbonato de cálcio calcinado numa mufla a 750 °C durante 3 h. Foi posteriormente activado a 900 °C durante 2h, em atmosferas diferentes: azoto (CaO-N2) e ar (CaO-Ar). Avaliaram-se algumas propriedades dos catalisadores assim preparados, força básica, concentração de centros activos e áreas específicas, tendo-se obtido uma força básica situada entre 12 e 14 para ambos os catalisadores, uma concentração de centros activos de 0,0698 mmol/g e 0,0629 mmol/g e áreas específicas de 10 m2/g e 11 m2/g respectivamente para o CaO-N2 e CaO-Ar. Efectuou-se a transesterificação, com catálise homogénea, da mistura de óleos usados utilizada neste trabalho com o objectivo de determinar os limites para o teor de FAME’s (abreviatura do Inglês de Fatty Acid Methyl Esters’) que se poderiam obter. Foi este o parâmetro avaliado em cada uma das amostras obtidas por catálise heterogénea. Os planos factoriais realizados tiveram como objectivo maximizar a sua quantidade recorrendo à relação ideal entre tempo de reacção, temperatura, massa de catalisador e quantidade de metanol. Verificou-se que o valor máximo de FAME’s obtidos a partir deste óleo estava situado ligeiramente acima dos 95 % (m/m). Realizaram-se três planos factoriais com cada um dos catalisadores de CaO até à obtenção das condições óptimas para a reacção. Não se verificou influência significativa da relação entre a quantidade de metanol e a massa de óleo na gama de valores estudada, pelo que se fixou o valor deste factor em 35 ml de metanol / 85g de óleo (relação molar aproximada de 8:1). Verificou-se a elegibilidade do CaO enquanto catalisador para a reacção estudada, não se tendo observado diferenças significativas entre a performance do CaO-N2 e do CaO-Ar. Identificaram-se as condições óptimas para a reacção como sendo os valores de 59 °C para a temperatura, 3h para o tempo e 1,4 % de massa de catalisador relativamente à massa de óleo. Nas referidas condições, obtiveram-se produtos com um teor de FAME’s de 95,7 % na catálise com CaO-N2 e 95,3 % na catálise com CaO-Ar. Alguns autores de estudos consultados no desenvolvimento do presente trabalho, referiam como principal problema da utilização do CaO, a lixiviação de cálcio para os produtos obtidos. Este facto foi confirmado no presente trabalho e na tentativa de o contornar, tentou-se promover a carbonatação do cálcio com a passagem de ar comprimido através dos produtos e subsequente filtração. Após a realização deste tratamento, não mais se observaram alterações nas suas propriedades (aparecimento de turvação ou precipitados), no entanto, nos produtos obtidos nas condições óptimas, a concentração de cálcio determinada foi de 527 mg/kg no produto da reacção catalisada com CaO-N2 e 475 mg/kg com CaO-A. O óxido de cálcio apresentou-se como um excelente catalisador na transesterificação da mistura de óleos alimentares usados utilizada no presente trabalho, apresentando uma performance ao nível da obtida por catálise homogénea básica. Não se observaram diferenças significativas de performance entre o CaO-N2 e o CaO-Ar, sendo possível obter nas mesmas condições reaccionais produtos com teores de FAME’s superiores a 95 % utilizando qualquer um deles como catalisador. O elevado teor de cálcio lixiviado observado nos produtos, apresenta-se como o principal obstáculo à aplicação a nível industrial do óxido de cálcio como catalisador para a transesterificação de óleos.

Psychometric Properties of the Portuguese Version of the Posttraumatic Growth Inventory Short Form Among Divorced Adults

The aim of this study was to develop and validate a Portuguese version of the Short Form of the Posttraumatic Growth Inventory (PTGI-SF). Using an online convenience sample of Portuguese divorced adults (N = 482), we confirmed the oblique five-factor structure of the PTGI-SF by confirmatory factor analysis. The results demonstrated the measurement invariance across divorce initiator status groups. Total score and factors of PTGI-SF showed good internal consistency, with the exception of the New Possibilities factor, which revealed an acceptable reliability. The Portuguese PTGI-SF showed a satisfactory convergent validity. In terms of discriminant validity, posttraumatic growth assessed by the Portuguese PTGI-SF was a distinct factor from posttraumatic psychological adjustment. These preliminary findings suggest the cultural adaptation and also psychometric properties of the present Portuguese PTGI-SF to measure posttraumatic growth after personal crisis.

Electrospun Polyaniline-Reduced Graphene Oxide Composite Nanofibers Based High Sensitive Ammonia Gas Sensor

Ammonia is an important gas in many power plants and industrial processes so its detection is of extreme importance in environmental monitoring and process control due to its high toxicity. Ammonia’s threshold limit is 25 ppm and the exposure time limit is 8 h, however exposure to 35 ppm is only secure for 10 min. In this work a brief introduction to ammonia aspects are presented, like its physical and chemical properties, the dangers in its manipulation, its ways of production and its sources. The application areas in which ammonia gas detection is important and needed are also referred: environmental gas analysis (e.g. intense farming), automotive-, chemical- and medical industries. In order to monitor ammonia gas in these different areas there are some requirements that must be attended. These requirements determine the choice of sensor and, therefore, several types of sensors with different characteristics were developed, like metal oxides, surface acoustic wave-, catalytic-, and optical sensors, indirect gas analyzers, and conducting polymers. All the sensors types are described, but more attention will be given to polyaniline (PANI), particularly to its characteristics, syntheses, chemical doping processes, deposition methods, transduction modes, and its adhesion to inorganic materials. Besides this, short descriptions of PANI nanostructures, the use of electrospinning in the formation of nanofibers/microfibers, and graphene and its characteristics are included. The created sensor is an instrument that tries to achieve a goal of the medical community in the control of the breath’s ammonia levels being an easy and non-invasive method for diagnostic of kidney malfunction and/or gastric ulcers. For that the device should be capable to detect different levels of ammonia gas concentrations. So, in the present work an ammonia gas sensor was developed using a conductive polymer composite which was immobilized on a carbon transducer surface. The experiments were targeted to ammonia measurements at ppb level. Ammonia gas measurements were carried out in the concentration range from 1 ppb to 500 ppb. A commercial substrate was used; screen-printed carbon electrodes. After adequate surface pre-treatment of the substrate, its electrodes were covered by a nanofibrous polymeric composite. The conducting polyaniline doped with sulfuric acid (H2SO4) was blended with reduced graphene oxide (RGO) obtained by wet chemical synthesis. This composite formed the basis for the formation of nanofibers by electrospinning. Nanofibers will increase the sensitivity of the sensing material. The electrospun PANI-RGO fibers were placed on the substrate and then dried at ambient temperature. Amperometric measurements were performed at different ammonia gas concentrations (1 to 500 ppb). The I-V characteristics were registered and some interfering gases were studied (NO2, ethanol, and acetone). The gas samples were prepared in a custom setup and were diluted with dry nitrogen gas. Electrospun nanofibers of PANI-RGO composite demonstrated an enhancement in NH3 gas detection when comparing with only electrospun PANI nanofibers. Was visible higher range of resistance at concentrations from 1 to 500 ppb. It was also observed that the sensor had stable, reproducible and recoverable properties. Moreover, it had better response and recovery times. The new sensing material of the developed sensor demonstrated to be a good candidate for ammonia gas determination.

Frailty as a predictor of short-term adverse outcomes

The objectives of this study were to compare how different frailty measures (Frailty Phenotype/FP, Groningen Frailty Indicator/GFI and Tilburg Frailty Indicator/TFI) predict short-term adverse outcomes. Secondarily, adopting a multidimensional approach to frailty (integral conceptual model–TFI), this study aims to compare how physical, psychological and social frailty predict the outcomes. A longitudinal study was carried out with 95 community-dwelling elderly. Participants were assessed at baseline for frailty, determinants of frailty, and adverse outcomes (healthcare utilization, quality of life, disability in basic and instrumental activities of daily living/ADL and IADL). Ten months later the outcomes were assessed again. Frailty was associated with specific healthcare utilization indicators: the FP with a greater utilization of informal care; GFI with an increased contact with healthcare professionals; and TFI with a higher amount of contacts with a general practitioner. After controlling for the effect of life-course determinants, comorbidity and adverse outcome at baseline, GFI predicted IADL disability and TFI predicted quality of life. The effect of the FP on the outcomes was not significant, when compared with the other measures. However, when comparing TFI’s domains, the physical domain was the most significant predictor of the outcomes, even explaining part of the variance of ADL disability. Frailty at baseline was associated with adverse outcomes at follow-up. However, the relationship of each frailty measure (FP, GFI and TFI) with the outcomes was different. In spite of the role of psychological frailty, TFI’s physical domain was the determinant factor for predicting disability and most of the quality of life.

Short sea como alternativa ao transporte terrestre

O Short Sea Shipping (SSS) é um conceito de transporte marítimo de difícil definição. No entanto, considera-se neste trabalho, que corresponde ao movimento de carga e passageiros por mar entre portos situados geográficamente na Europa ou entre outros portos que não estejam situados na Europa, mas que partilham costa com mares que banham a Europa. Esta definição é sem dúvida aquela que melhor se adequa à inclusão do Short SSS como elo de uma cadeia multimodal de transporte de mercadorias no espaço Europeu, e como alternativa ao transporte de mercadorias apenas por estrada. Este trabalho aborda alguns conceitos importantes subjacentes ao transporte marítimo de forma a permitir uma contextualização que possibilite uma melhor compreensão da abordagem feita ao SSS. A sua promoção e implementação, como alternativa viável para o transporte de mercadorias dentro do espaço Europeu, são objetivos da política de transportes da União Europeia (UE). Este trabalho reflete sobre algumas das políticas estratégicas de promoção da UE para impulsionar o SSS como alternativa ao transporte rodoviário. O objetivo deste trabalho é analisar se o SSS é uma alternativa ao transporte terrestre, no contexto de uma distribuição no Reino Unido de produtos de uma Industria localizada nos arredores da cidade do Porto. Neste trabalho analisou-se as vantagens e desvantagens do SSS, foi efetuada uma descrição do Porto de Leixões como porto escolhido para as expedições, assim como uma análise descritiva dos serviços de Short Sea disponiveis neste porto para as zonas de distribuição desta empresa. Foram descritos os fatores chave da mudança de transporte terrestre para SSS, efectuada uma caracterização da distribuição desta empresa e da solução que esta adotou para distribuir os seus produtos no Reino Unido. A anállise económica da operação, dos tempos de trânsito são dois temas fundamentais para a viabilidade da solução como alternativa ao transporte terrestre.

Determination of Microcystin-LR in waters in the subnanomolar range by sol–gel imprinted polymers on solid contact electrodes

The present work reports new sensors for the direct determination of Microcystin-LR (MC-LR) in environmental waters. Both selective membrane and solid contact were optimized to ensure suitable analytical features in potentiometric transduction. The sensing layer consisted of Imprinted Sol–Gel (ISG) materials capable of establishing surface interactions with MC-LR. Non-Imprinted Sol–Gel (NISG) membranes were used as negative control. The effects of an ionic lipophilic additive, time of sol–gel polymerization, time of extraction of MC-LR from the sensitive layer, and pH were also studied. The solid contact was made of carbon, aluminium, titanium, copper or nickel/chromium alloys (80 : 20 or 90 : 10). The best ISG sensor had a carbon solid contact and displayed average slopes of 211.3 mV per decade, with detection limits of 7.3 1010 M, corresponding to 0.75 mg L1 . It showed linear responses in the range of 7.7 1010 to 1.9 109 M of MC-LR (corresponding to 0.77–2.00 mg L1 ), thus including the limiting value for MC-LR in waters (1.0 mg L1 ). The potentiometric-selectivity coefficients were assessed by the matched potential method for ionic species regularly found in waters up to their limiting levels. Chloride (Cl) showed limited interference while aluminium (Al3+), ammonium (NH4 + ), magnesium (Mg2+), manganese (Mn2+), sodium (Na+ ), and sulfate (SO4 2) were unable to cause the required potential change. Spiked solutions were tested with the proposed sensor. The relative errors and standard deviation obtained confirmed the accuracy and precision of the method. It also offered the advantages of low cost, portability, easy operation and suitability for adaptation to flow methods.

Using data mining with time series data in short-term stocks prediction

Data Mining (DM) methods are being increasingly used in prediction with time series data, in addition to traditional statistical approaches. This paper presents a literature review of the use of DM with time series data, focusing on short- time stocks prediction. This is an area that has been attracting a great deal of attention from researchers in the field. The main contribution of this paper is to provide an outline of the use of DM with time series data, using mainly examples related with short-term stocks prediction. This is important to a better understanding of the field. Some of the main trends and open issues will also be introduced.

A multi-objective model for scheduling of short-term incentive-based demand response programs offered by electricity retailers

In this paper, we formulate the electricity retailers’ short-term decision-making problem in a liberalized retail market as a multi-objective optimization model. Retailers with light physical assets, such as generation and storage units in the distribution network, are considered. Following advances in smart grid technologies, electricity retailers are becoming able to employ incentive-based demand response (DR) programs in addition to their physical assets to effectively manage the risks of market price and load variations. In this model, the DR scheduling is performed simultaneously with the dispatch of generation and storage units. The ultimate goal is to find the optimal values of the hourly financial incentives offered to the end-users. The proposed model considers the capacity obligations imposed on retailers by the grid operator. The profit seeking retailer also has the objective to minimize the peak demand to avoid the high capacity charges in form of grid tariffs or penalties. The non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the multi-objective problem. It is a fast and elitist multi-objective evolutionary algorithm. A case study is solved to illustrate the efficient performance of the proposed methodology. Simulation results show the effectiveness of the model for designing the incentive-based DR programs and indicate the efficiency of NSGA-II in solving the retailers’ multi-objective problem.