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.

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.

Estratégias de oferta em leilões simétricos no âmbito dos mercados liberalizados de electricidade

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Influence of long-term wearing of unstable shoes on compensatory control of posture: An electromyography-based analysis

Purpose: This study investigated the influence of long-term wearing of unstable shoes (WUS) on compensatory postural adjustments (CPA) to an external perturbation. Methods: Participants were divided into two groups: one wore unstable shoes while the other wore conventional shoes for 8 weeks. The ground reaction force signal was used to calculate the anterior– posterior (AP) displacement of the centre of pressure (CoP) and the electromyographic signal of gastrocnemius medialis (GM), tibialis anterior (TA), rectus femoris (RF) and biceps femoris (BF) muscles was used to assess individual muscle activity, antagonist co-activation and reciprocal activation at the joint (TA/GM and RF/(BF + GM) pairs) and muscle group levels (ventral (TA + RF)/dorsal (GM + BF) pair) within time intervals typical for CPA. The electromyographic signal was also used to assess muscle latency. The variables described were evaluated before and after the 8-week period while wearing the unstable shoes and barefoot. Results: Long-term WUS led to: an increase of BF activity in both conditions (barefoot and wearing the unstable shoes); a decrease of GM activity; an increase of antagonist co-activation and a decrease of reciprocal activation level at the TA/GM and ventral/dorsal pairs in the unstable shoe condition. Additionally, WUS led to a decrease in CoP displacement. However, no differences were observed in muscle onset and offset. Conclusion: Results suggest that the prolonged use of unstable shoes leads to increased ankle and muscle groups’ antagonist co-activation levels and higher performance by the postural control system.

Short- and medium-term effects of manual therapy on cervical active range of motion and pressure pain sensitivity in latent myofascial pain of the upper trapezius muscle: a randomized controlled trial

Objective: The purpose of this study was to investigate effects of different manual techniques on cervical ranges of 17 motion and pressure pain sensitivity in subjects with latent trigger point of the upper trapezius muscle. 18 Methods: One hundred seventeen volunteers, with a unilateral latent trigger point on upper trapezius due to computer 19 work, were randomly divided into 5 groups: ischemic compression (IC) group (n = 24); passive stretching group (n = 20 23); muscle energy technique group (n = 23); and 2 control groups, wait-and-see group (n = 25) and placebo group 21 (n = 22). Cervical spine range of movement was measured using a cervical range of motion instrument as well as 22 pressure pain sensitivity by means of an algometer and a visual analog scale. Outcomes were assessed pretreatment, 23 immediately, and 24 hours after the intervention and 1 week later by a blind researcher. A 4 × 5 mixed repeated- 24 measures analysis of variance was used to examine the effects of the intervention and Cohen d coefficient was used. 25 Results: A group-by-time interaction was detected in all variables (P b .01), except contralateral rotation. The 26 immediate effect sizes of the contralateral flexion, ipsilateral rotation, and pressure pain threshold were large for 3 27 experimental groups. Nevertheless, after 24 hours and 1 week, only IC group maintained the effect size. 28 Conclusions: Manual techniques on upper trapezius with latent trigger point seemed to improve the cervical range of 29 motion and the pressure pain sensitivity. These effects persist after 1 week in the IC group. (J Manipulative Physiol 301 Ther 2013;xx:1-10)

Stochastic short-term maintenance scheduling of GENCOs in an oligopolistic electricity market

In the proposed model, the independent system operator (ISO) provides the opportunity for maintenance outage rescheduling of generating units before each short-term (ST) time interval. Long-term (LT) scheduling for 1 or 2 years in advance is essential for the ISO and the generation companies (GENCOs) to decide their LT strategies; however, it is not possible to be exactly followed and requires slight adjustments. The Cournot-Nash equilibrium is used to characterize the decision-making procedure of an individual GENCO for ST intervals considering the effective coordination with LT plans. Random inputs, such as parameters of the demand function of loads, hourly demand during the following ST time interval and the expected generation pattern of the rivals, are included as scenarios in the stochastic mixed integer program defined to model the payoff-maximizing objective of a GENCO. Scenario reduction algorithms are used to deal with the computational burden. Two reliability test systems were chosen to illustrate the effectiveness of the proposed model for the ST decision-making process for future planned outages from the point of view of a GENCO.

Long-term dependence in financial prices: evidence from the Belgian stock market returns

This article aims to contribute to the discussion of long-term dependence, focusing on the behavior of the main Belgian stock index. Non-parametric analyzes of the general characteristics of temporal frequency show that daily returns are non-ergodic and non-stationary. Therefore, we use the rescaled-range analysis (R/S) and the detrended fluctuation analysis (DFA), under the fractional Brownian motion approach, and we found slight evidence of long-term dependence. These results refute the random walk hypothesis with i.i.d. increments, which is the basis of the EMH in its weak form, and call into question some theoretical modeling of asset pricing. Other more localized complementary study, to identify the evolution of the degree of dependence over time windows, showed that the index has become less persistent from 2010. This may mean a maturing market by the extension of the effects of current financial crisis.

Long-term memory in financial prices: evidence from the Dutch stock market returns

Prepared for presentation at the Portuguese Finance Network International Conference 2014, Vilamoura, Portugal, June 18-20

How to feel "in love" with Math - a MOOC experience

In the past few years we have witnessed the fast development of distance learning tools such as Open Educational Resources (OER) and Massive Open Online Courses (MOOCs). This paper presents the “Mathematics without STRESS” MOOC Project, which is a cooperation between four schools from the Polytechnic Institute of Oporto (IPP). The concepts of MOOC and their quickly growing popularity are presented and complemented by a discussion of some MOOC definitions. The process of the project development is demonstrated by focusing on used MOOC structure, as well as the several types of course materials produced. At last, is presented a short discussion about problems and challenges met throughout the project. It is also our goal to contribute for a change in the way as teaching and learning Mathematics is seen and practiced nowadays.

Motivations to participate in international trade fairs: the Portuguese experience

Motivations/barriers to participate in ITF

Forest soil short term response to prescribed fire: an approach by Principal Components Analysis

In the current context of serious climate changes, where the increase of the frequency of some extreme events occurrence can enhance the rate of periods prone to high intensity forest fires, the National Forest Authority often implements, in several Portuguese forest areas, a regular set of measures in order to control the amount of fuel mass availability (PNDFCI, 2008). In the present work we’ll present a preliminary analysis concerning the assessment of the consequences given by the implementation of prescribed fire measures to control the amount of fuel mass in soil recovery, in particular in terms of its water retention capacity, its organic matter content, pH and content of iron. This work is included in a larger study (Meira-Castro, 2009(a); Meira-Castro, 2009(b)). According to the established praxis on the data collection, embodied in multidimensional matrices of n columns (variables in analysis) by p lines (sampled areas at different depths), and also considering the quantitative data nature present in this study, we’ve chosen a methodological approach that considers the multivariate statistical analysis, in particular, the Principal Component Analysis (PCA ) (Góis, 2004). The experiments were carried out in a soil cover over a natural site of Andaluzitic schist, in Gramelas, Caminha, NW Portugal, who was able to maintain itself intact from prescribed burnings from four years and was submit to prescribed fire in March 2008. The soils samples were collected from five different plots at six different time periods. The methodological option that was adopted have allowed us to identify the most relevant relational structures inside the n variables, the p samples and in two sets at the same time (Garcia-Pereira, 1990). Consequently, and in addition to the traditional outputs produced from the PCA, we have analyzed the influence of both sampling depths and geomorphological environments in the behavior of all variables involved.