Investigation of the Impacts of Large-Scale Wind Power Penetration on the Angle and Voltage Stability of Power Systems

The complexity of power systems has increased in recent years due to the operation of existing transmission lines closer to their limits, using flexible AC transmission system (FACTS) devices, and also due to the increased penetration of new types of generators that have more intermittent characteristics and lower inertial response, such as wind generators. This changing nature of a power system has considerable effect on its dynamic behaviors resulting in power swings, dynamic interactions between different power system devices, and less synchronized coupling. This paper presents some analyses of this changing nature of power systems and their dynamic behaviors to identify critical issues that limit the large-scale integration of wind generators and FACTS devices. In addition, this paper addresses some general concerns toward high compensations in different grid topologies. The studies in this paper are conducted on the New England and New York power system model under both small and large disturbances. From the analyses, it can be concluded that high compensation can reduce the security limits under certain operating conditions, and the modes related to operating slip and shaft stiffness are critical as they may limit the large-scale integration of wind generation.

Does Brazil need new nuclear power plants?

In October 2008, the Brazilian Government announced plans to invest US$212 billion in the construction of nuclear power plants, totaling a joint capacity of 60,000 MW. Apart from this program, officials had already announced the completion of the construction of the nuclear plant Angra III; the construction of large-scale hydroelectric plans in the Amazon and the implantation of natural gas, biomass and coal thermoelectric plants in other regions throughout the country. Each of these projects has its proponents and its opponents, who bring forth concerns and create heated debates in the specialized forums. In this article, some of these concerns are explained, especially under the perspective of the comparative analysis of costs involved. Under such merit figures, the nuclear option, when compared to hydro plants, combined with conventional thermal and biomass-fueled plants, and even wind, to expand Brazilian power-generation capacity, does not appear as a priority. (C) 2009 Elsevier Ltd. All rights reserved.

Manipulation effects of prior exercise intensity feedback by the Borg scale during open-loop cycling

Objective To verify the effects of exercise intensity deception by the Borg scale on the ratings of perceived exertion (RPE), heart rate (HR) and performance responses during a constant power output open-loop exercise. Methods Eight healthy men underwent a maximal incremental test on a cycle ergometer to identify the peak power output (PPO) and heart rate deflection point (HRDP). Subsequently, they performed a constant power output trial to exhaustion set at the HRDP intensity, in deception (DEC) and informed (INF) conditions: DEC-subjects were told that they would be cycling at an intensity corresponding to two categories below the RPE quantified at the HRDP; INF-subjects were told that they would cycle at the exact intensity corresponding to the RPE quantified at the HRDP. Results The PPO and power output at the HRDP obtained in maximal incremental tests were 247.5 +/- 32.1 W and 208.1 +/- 27.1 W, respectively. No significant difference in the time to exhaustion was found between DEC (525 +/- 244 s) or INF (499 +/- 224 s) trials. The slope and the first and second measurements of the RPE and HR parameters showed no significant difference between trials. Conclusions Psychophysiological variables such as RPE and HR as well as performance were not affected when exercise intensity was deceptively manipulated via RPE scores. This may suggest that unaltered RPE during exercise is a regulator of performance in this open-loop exercise.

Differential aberrant sprouting in temporal lobe epilepsy with psychiatric co-morbidities

Psychiatric co-morbidities in epilepsy are common in patients with temporal lobe epilepsy (TLE). Pathological alterations in TLE are well characterised; however, neuropathologic data are relatively scale regarding the association between psychiatric diseases and epilepsy. Our objective was to evaluate the clinical data of 46 adult TLE patients with and without psychiatric co-morbidities and to correlate the data with hippocampal neuronal density and mossy fiber sprouting. Accordingly, patients were grouped as follows: TLE patients without history of psychiatric disorder (TLE, n = 16), TLE patients with interictal psychosis (TLE + P, n = 14), and TLE patients with major depression (TLE + D, n = 16). Hippocampi from autopsies served as non-epileptic controls (n = 10). TLE + P exhibited significantly diminished mossy fiber sprouting and decreased neuronal density in the entorhinal cortex when compared with TLE. TLE + P showed significantly poorer results in verbal memory tasks. TLE + D exhibited significantly increased mossy fiber sprouting length when compared with TLE and TLE + P. Further, a higher proportion of TLE + D and TLE + P presented secondarily generalised seizures than did TLE. Our results indicate that TLE patients with psychiatric disorders have distinct features when compared with TLE patients without psychiatric co-morbidities and that these changes may be involved in either the manifestation or the maintenance of psychiatric co-morbidities in epilepsy. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

On scale-mixture Birnbaum-Saunders distributions

We present for the first time a justification on the basis of central limit theorems for the family of life distributions generated from scale-mixture of normals. This family was proposed by Balakrishnan et al. (2009) and can be used to accommodate unexpected observations for the usual Birnbaum-Saunders distribution generated from the normal one. The class of scale-mixture of normals includes normal, slash, Student-t, logistic, double-exponential, exponential power and many other distributions. We present a model for the crack extensions where the limiting distribution of total crack extensions is in the class of scale-mixture of normals. (C) 2012 Elsevier B.V. All rights reserved.

New approach for power transformer protection based on intelligent hybrid systems

A power transformer needs continuous monitoring and fast protection as it is a very expensive piece of equipment and an essential element in an electrical power system. The most common protection technique used is the percentage differential logic, which provides discrimination between an internal fault and different operating conditions. Unfortunately, there are some operating conditions of power transformers that can mislead the conventional protection affecting the power system stability negatively. This study proposes the development of a new algorithm to improve the protection performance by using fuzzy logic, artificial neural networks and genetic algorithms. An electrical power system was modelled using Alternative Transients Program software to obtain the operational conditions and fault situations needed to test the algorithm developed, as well as a commercial differential relay. Results show improved reliability, as well as a fast response of the proposed technique when compared with conventional ones.

Optimization of Large-Scale Hydrothermal System Operation

This paper presents the development of a mathematical model to optimize the management and operation of the Brazilian hydrothermal system. The system consists of a large set of individual hydropower plants and a set of aggregated thermal plants. The energy generated in the system is interconnected by a transmission network so it can be transmitted to centers of consumption throughout the country. The optimization model offered is capable of handling different types of constraints, such as interbasin water transfers, water supply for various purposes, and environmental requirements. Its overall objective is to produce energy to meet the country's demand at a minimum cost. Called HIDROTERM, the model integrates a database with basic hydrological and technical information to run the optimization model, and provides an interface to manage the input and output data. The optimization model uses the General Algebraic Modeling System (GAMS) package and can invoke different linear as well as nonlinear programming solvers. The optimization model was applied to the Brazilian hydrothermal system, one of the largest in the world. The system is divided into four subsystems with 127 active hydropower plants. Preliminary results under different scenarios of inflow, demand, and installed capacity demonstrate the efficiency and utility of the model. From this and other case studies in Brazil, the results indicate that the methodology developed is suitable to different applications, such as planning operation, capacity expansion, and operational rule studies, and trade-off analysis among multiple water users. DOI: 10.1061/(ASCE)WR.1943-5452.0000149. (C) 2012 American Society of Civil Engineers.

Plasma cortisol in first episode drug-naive mania: Differential levels in euphoric versus irritable mood

Background: Dysregulation of HPA axis has been widely described in subjects with bipolar disorder (BD), including changes in cortisol levels during mood episodes and euthymia. However, most of the studies were done with medicated BD patients with variable length of illness, which was shown to interfere on peripheral cortisol levels. Therefore, the present study aims to evaluate plasma cortisol levels in drug-naive BD subjects during the first manic episode, as well as investigate the relationship between plasma cortisol levels and manic symptomatology. Methods: Twenty-six drug-naive patients were enrolled meeting criteria for a first manic episode in bipolar I disorder. Severity of mania was assessed using the Young Mania Rating Scale (YMRS). The control group included 27 healthy subjects matched by age and gender. Cortisol was quantified using a direct radioimmunoassay. Results: Plasma cortisol levels were decreased during first manic episode compared to healthy controls. Higher cortisol levels were positively associated with the presence of irritability (dysphoria), while elated mania showed lower cortisol levels compared to controls. Limitation: Data including larger samples are lacking. Conclusion: Higher cortisol in dysphoric mania compared to predominantly elated/euphoric mania may indicate a clinical and neurobiological polymorphic phenomenon, potentially involving a higher biological sensitivity to stress in the presence of irritable mood. The present findings highlight the importance to add a dimensional approach to the traditional categorical diagnosis for future neurobiological studies in BD. (C) 2011 Elsevier B.V. All rights reserved.

Algebraic-graph method for identification of islanding in power system grids

In this paper, a new algebraic-graph method for identification of islanding in power system grids is proposed. The proposed method identifies all the possible cases of islanding, due to the loss of a equipment, by means of a factorization of the bus-branch incidence matrix. The main features of this new method include: (i) simple implementation, (ii) high speed, (iii) real-time adaptability, (iv) identification of all islanding cases and (v) identification of the buses that compose each island in case of island formation. The method was successfully tested on large-scale systems such as the reduced south Brazilian system (45 buses/72 branches) and the south-southeast Brazilian system (810 buses/1340 branches). (C) 2011 Elsevier Ltd. All rights reserved.

A modified Primal-Dual Logarithmic-Barrier Method for solving the Optimal Power Flow problem with discrete and continuous control variables

The aim of solving the Optimal Power Flow problem is to determine the optimal state of an electric power transmission system, that is, the voltage magnitude and phase angles and the tap ratios of the transformers that optimize the performance of a given system, while satisfying its physical and operating constraints. The Optimal Power Flow problem is modeled as a large-scale mixed-discrete nonlinear programming problem. This paper proposes a method for handling the discrete variables of the Optimal Power Flow problem. A penalty function is presented. Due to the inclusion of the penalty function into the objective function, a sequence of nonlinear programming problems with only continuous variables is obtained and the solutions of these problems converge to a solution of the mixed problem. The obtained nonlinear programming problems are solved by a Primal-Dual Logarithmic-Barrier Method. Numerical tests using the IEEE 14, 30, 118 and 300-Bus test systems indicate that the method is efficient. (C) 2012 Elsevier B.V. All rights reserved.

Likelihood-based inference for power distributions

This paper considers likelihood-based inference for the family of power distributions. Widely applicable results are presented which can be used to conduct inference for all three parameters of the general location-scale extension of the family. More specific results are given for the special case of the power normal model. The analysis of a large data set, formed from density measurements for a certain type of pollen, illustrates the application of the family and the results for likelihood-based inference. Throughout, comparisons are made with analogous results for the direct parametrisation of the skew-normal distribution.

Multi-objective evolutionary algorithm for single and multiple fault service restoration in large-scale distribution systems

Network reconfiguration for service restoration (SR) in distribution systems is a complex optimization problem. For large-scale distribution systems, it is computationally hard to find adequate SR plans in real time since the problem is combinatorial and non-linear, involving several constraints and objectives. Two Multi-Objective Evolutionary Algorithms that use Node-Depth Encoding (NDE) have proved able to efficiently generate adequate SR plans for large distribution systems: (i) one of them is the hybridization of the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) with NDE, named NSGA-N; (ii) the other is a Multi-Objective Evolutionary Algorithm based on subpopulation tables that uses NDE, named MEAN. Further challenges are faced now, i.e. the design of SR plans for larger systems as good as those for relatively smaller ones and for multiple faults as good as those for one fault (single fault). In order to tackle both challenges, this paper proposes a method that results from the combination of NSGA-N, MEAN and a new heuristic. Such a heuristic focuses on the application of NDE operators to alarming network zones according to technical constraints. The method generates similar quality SR plans in distribution systems of significantly different sizes (from 3860 to 30,880 buses). Moreover, the number of switching operations required to implement the SR plans generated by the proposed method increases in a moderate way with the number of faults.