An integrated approach for distributed energy resource short term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .

A short-term risk management tool applied to OMEL electricity market using particle swarm optimization

Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, are presented and discussed in detail.

Optimization model for medium term natural gas commitment

In this paper we study the optimal natural gas commitment for a known demand scenario. This study implies the best location of GSUs to supply all demands and the optimal allocation from sources to gas loads, through an appropriate transportation mode, in order to minimize total system costs. Our emphasis is on the formulation and use of a suitable optimization model, reflecting real-world operations and the constraints of natural gas systems. The mathematical model is based on a Lagrangean heuristic, using the Lagrangean relaxation, an efficient approach to solve the problem. Computational results are presented for Iberian and American natural gas systems, geographically organized in 65 and 88 load nodes, respectively. The location model results, supported by the computational application GasView, show the optimal location and allocation solution, system total costs and suggest a suitable gas transportation mode, presented in both numerical and graphic supports.

Distribution network short term scheduling in Smart Grid context

The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and “green” operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a Mixed Integer Non-Linear Programming (MINLP) approach.

Tratamento de cor em pós-produção televisiva: o caso da produtora de conteúdos SP Televisão

Dissertação apresentada à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Audiovisual e Multimédia.

A long-term swarm intelligence hedging tool applied to electricity markets

This paper proposes a swarm intelligence long-term hedging tool to support electricity producers in competitive electricity markets. This tool investigates the long-term hedging opportunities available to electric power producers through the use of contracts with physical (spot and forward) and financial (options) settlement. To find the optimal portfolio the producer risk preference is stated by a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance estimation and the expected return are based on a forecasted scenario interval determined by a long-term price range forecast model, developed by the authors, whose explanation is outside the scope of this paper. The proposed tool makes use of Particle Swarm Optimization (PSO) and its performance has been evaluated by comparing it with a Genetic Algorithm (GA) based approach. To validate the risk management tool a case study, using real price historical data for mainland Spanish market, is presented to demonstrate the effectiveness of the proposed methodology.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.

Pre-operative tractography of the facial nerve in vestibular schwannomas: inter-observer agreement with surgical findings

Pre-operative diffusion tensor (DT) tractography is currently employed in our institutions. We use it to predict the course of the facial nerve (FN) in the vicinity of vestibular schwannomas (VS) of the cerebellopontine angle (CPA). In this study we were interested to assess the inter-observer reproducibility of this method. Two Neuroradiologists (PMGP and TT) determined independently the location of the FN by tractography and compared the results with in-vivo findings of microsurgery of VS.

Surgical proven location of the facial nerve in the vicinity of cerebellopontine angle tumours depicted pre-operatively by tractography

Purpose/Introduction: To determine the clinical utility of pre-operative diffusion tensor (DT) tractography of the facial nerve in the vicinity of cerebellopontine angle (CPA) tumours. The location of the facial nerve was established pre-operatively by tractography and compared with in-vivo electrode stimulation during microsurgery of vestibular schwannomas and rare CPA masses (meningiomas and arachnoid cysts).

Evidence of long-term changes in the distribution of key intertidal species

World Congress of Malacology, Ponta Delgada, July 22-28, 2013.

Influence of the pre-treatments on the properties of biodegradable films from bovine hair

The replacement of conventional synthetic films and coatings by biodegradable alternatives reduces the use of non-renewable resources and waste disposal problems. Considering that Portugal is a major producer of leather, and consequently a large producer of related wastes, in this research, bovine hair was tested for the production of biodegradable films directly by thermo-compression, allowing waste valorisation and reduction of environmental pollution. The aim of this study was to determine the influence of the different pre-treatments performed by two processes (removal by mechanical action and removal by chemical process), applied to bovine hair, in order to obtain a biodegradable film with appropriate properties. Mechanical properties for these films were evaluated, namely strain at break, stress at break and Young modulus. Additionally colour, solubility and swelling in water were also studied. The mechanical removal hair only produced films with Na2S treatment. Chemical removed hair (immunization) depends of the pre-treatment and the degreasing with petroleum ether or sodium sulphide pre-treatment leads better mechanical properties. The results obtained indicated that the pre-treatments have an important role in the final properties of biodegradable films.

Perfil de citocinas no colostro em função da idade gestacional e do crescimento fetal

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

The adjusted effect of maternal body mass index, energy and macronutrient intakes during pregnancy, and gestational weight gain on body composition of full-term neonates

Objective - To evaluate the effect of prepregnancy body mass index (BMI), energy and macronutrient intakes during pregnancy, and gestational weight gain (GWG) on the body composition of full-term appropriate-for-gestational age neonates. Study Design - This is a cross-sectional study of a systematically recruited convenience sample of mother-infant pairs. Food intake during pregnancy was assessed by food frequency questionnaire and its nutritional value by the Food Processor Plus (ESHA Research Inc, Salem, OR). Neonatal body composition was assessed both by anthropometry and air displacement plethysmography. Explanatory models for neonatal body composition were tested by multiple linear regression analysis. Results - A total of 100 mother-infant pairs were included. Prepregnancy overweight was positively associated with offspring weight, weight/length, BMI, and fat-free mass in the whole sample; in males, it was also positively associated with midarm circumference, ponderal index, and fat mass. Higher energy intake from carbohydrate was positively associated with midarm circumference and weight/length in the whole sample. Higher GWG was positively associated with weight, length, and midarm circumference in females. Conclusion - Positive adjusted associations were found between both prepregnancy BMI and energy intake from carbohydrate and offspring body size in the whole sample. Positive adjusted associations were also found between prepregnancy overweight and adiposity in males, and between GWG and body size in females.

Long-term monitoring across elevational gradients to assess ecological hypothesis : a description of standardized sampling methods in oceanic islands and first results

We are launching a long-term study to characterize the biodiversity at different elevations in several Azorean Islands. Our aim is to use the Azores as a model archipelago to answer the fundamental question of what generates and maintains the global spatial heterogeneity of diversity in islands and to be able to understand the dynamics of change across time. An extensive, standardized sampling protocol was applied in most of the remnant forest fragments of five Azorean Islands. Fieldwork followed BRYOLAT methodology for the collection of bryophytes, ferns and other vascular plant species. A modified version of the BALA protocol was used for arthropods. A total of 70 plots (10 m x 10 m) are already established in five islands (Flores, Pico, São Jorge, Terceira and São Miguel), all respecting an elevation step of 200 m, resulting in 24 stations examined in Pico, 12 in Terceira, 10 in Flores, 12 in São Miguel and 12 in São Jorge. The first results regarding the vascular plants inventory include 138 vascular species including taxa from Lycopodiophyta (N=2), Pteridophyta (N=27), Pinophyta (N=2) and Magnoliophyta (N=107). In this contribution we also present the main research question for the next six years within the 2020 Horizon.