Electrical load forecasting formulation by a fast neural network

The objective of this work is to develop a methodology for electric load forecasting based on a neural network. Here, backpropagation algorithm is used with an adaptive process that based on fuzzy logic and using a decaying exponential function to avoid instability in the convergence process. This methodology results in fast training, when compared to the conventional formulation of backpropagation algorithm. The results are presented using data from a Brazilian Electric Company, and shows a very good performance for the proposal objective.

An effortless hybrid method to solve economic load dispatch problem in power systems

This paper proposes a new approach and coding scheme for solving economic dispatch problems (ED) in power systems through an effortless hybrid method (EHM). This novel coding scheme can effectively prevent futile searching and also prevents obtaining infeasible solutions through the application of stochastic search methods, consequently dramatically improves search efficiency and solution quality. The dominant constraint of an economic dispatch problem is power balance. The operational constraints, such as generation limitations, ramp rate limits, prohibited operating zones (POZ), network loss are considered for practical operation. Firstly, in the EHM procedure, the output of generator is obtained with a lambda iteration method and without considering POZ and later in a genetic based algorithm this constraint is satisfied. To demonstrate its efficiency, feasibility and fastness, the EHM algorithm was applied to solve constrained ED problems of power systems with 6 and 15 units. The simulation results obtained from the EHM were compared to those achieved from previous literature in terms of solution quality and computational efficiency. Results reveal that the superiority of this method in both aspects of financial and CPU time. (C) 2011 Elsevier Ltd. All rights reserved.

Foraging Behavior of the Swarm-Founding Wasp, Polybia (Trichothorax) sericea (Hymenoptera, Vespidae): Prey Capture and Load Capacity

The main component of the protein diet of P. sericea was larvae of Lepidoptera (75.38%), with predominance of the following Families: Noctuidae (30.99%), Hesperiidae (19.01%); Pyralidae (19.01%) and Nymphalidae (11.98%). The average weight of the prey captured was 14.2 mg, a value equivalent to 24.7% of the average wasp weight. The average glucidic food load was 28.61 mg, corresponding to approximately half the wasp weight (49.64%). The weight of the load transported in the crop varied according to the food density, which, in turn, influenced the time spent in its collection (Pearson: n=64; r=0.64;p<0.05). Polybia sericea showed predatory interactions against Lepidopteran caterpillars, who are known to be agricultural pests. P. sericea has potential to be used in Integrated Pest Management.

Urban Traffic Control and Monitoring - An Approach for the Brazilian Intelligent Cities Project

This paper describes an urban traffic control system which aims at contributing to a more efficient traffic management system in the cities of Brazil. It uses fuzzy sets, case-based reasoning, and genetic algorithms to handle dynamic and unpredictable traffic scenarios, as well as uncertain, incomplete, and inconsistent information. The system is composed by one supervisor and several controller agents, which cooperate with each other to improve the system's results through Artificial Intelligence Techniques.

Spatial electric load forecasting using a local movement approach

An agent based model for spatial electric load forecasting using a local movement approach for the spatiotemporal allocation of the new loads in the service zone is presented. The density of electrical load for each of the major consumer classes in each sub-zone is used as the current state of the agents. The spatial growth is simulated with a walking agent who starts his path in one of the activity centers of the city and goes to the limits of the city following a radial path depending on the different load levels. A series of update rules are established to simulate the S growth behavior and the complementarity between classes. The results are presented in future load density maps. The tests in a real system from a mid-size city show a high rate of success when compared with other techniques. The most important features of this methodology are the need for few data and the simplicity of the algorithm, allowing for future scalability. © 2009 IEEE.

Spatial load forecasting using a demand propagation approach

A method for spatial electric load forecasting using multi-agent systems, especially suited to simulate the local effect of special loads in distribution systems is presented. The method based on multi-agent systems uses two kinds of agents: reactive and proactive. The reactive agents represent each sub-zone in the service zone, characterizing each one with their corresponding load level, represented in a real number, and their relationships with other sub-zones represented in development probabilities. The proactive agent carry the new load expected to be allocated because of the new special load, this agent distribute the new load in a propagation pattern. The results are presented with maps of future expected load levels in the service zone. The method is tested with data from a mid-size city real distribution system, simulating the effect of a load with attraction and repulsion attributes. The method presents good results and performance. © 2011 IEEE.

Short-term multinodal load forecasting in distribution systems using general regression neural networks

Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, trustable and has a short-time processing. This paper proposes two methodologies based on general regression neural networks for short-term multinodal load forecasting. The first individually forecast the local loads and the second forecast the global load and individually forecast the load participation factors to estimate the local loads. To design the forecasters it wasn't necessary the previous study of the local loads. Tests were made using a New Zealand distribution subsystem and the results obtained are compatible with the ones founded in the specialized literature. © 2011 IEEE.

Characterization of the temperature, load and damage effects using piezoelectric transducer patches based on fuzzy clustering

Structural Health Monitoring (SHM) denotes a system with the ability to detect and interpret adverse changes in a structure. One of the critical challenges for practical implementation of SHM system is the ability to detect damage under changing environmental conditions. This paper aims to characterize the temperature, load and damage effects in the sensor measurements obtained with piezoelectric transducer (PZT) patches. Data sets are collected on thin aluminum specimens under different environmental conditions and artificially induced damage states. The fuzzy clustering algorithm is used to organize the sensor measurements into a set of clusters, which can attribute the variation in sensor data due to temperature, load or any induced damage.

Interdisciplinary approach to the management of Ewing sarcoma: A case report

Ewing sarcoma is a common primary bone malignancy occurring in childhood and adolescence. This case report describes a 4-year-old female patient who had Ewing sarcoma in the left clavicular region. The patient underwent total excision of the left clavicle and subsequently developed periodontitis and multiple carious lesions after chemotherapy. Caries risk and salivary flow rate tests were performed, followed by periodontal treatment, topical fluoride application, restoration of caries, and oral hygiene instruction. The care of this patient demonstrates that an interdisciplinary approach is essential to eliminate all foci of infection, minimize morbidity, and improve the patient's general health before, during, and after oncological treatment. © 2012 Special Care Dentistry Association and Wiley Periodicals, Inc.

Knowledge-based risk management: Survey on Brazilian software development enterprises

A risks management, carried on in an effective way, leads the software development to success and may influence on the organization. The knowledge takes part of such a process as a way to help taking decisions. This research aimed to analyze the use of Knowledge Management techniques to the Risk Management in software projects development and the possible influence on the enterprise revenue. It had, as its main studying subject, Brazilian incubated and graduated software developing enterprises. The chosen research method was the Survey type. Multivariate statistical methods were used for the treatment and analysis of the obtained results, this way identifying the most significant factors, that is, enterprise's achievement constraining factors and those outcome achievement ones. Among the latter we highlight the knowledge methodology, the time of existence of the enterprise, the amount of employees and the knowledge externalization. The results encourage contributing actions to the increasing of financial revenue. © 2013 Springer-Verlag.

Failure of miniplate osteosynthesis for the management of atrophic mandibular fracture

Fractures of the severely atrophic (<10 mm) edentulous mandible are not common, and these fractures with a vertical height of 10 mm or less have long been recognized as being particularly problematic. Although there are advances in the treatment of the atrophic mandibular fracture, the treatment remains controversial. There are some options for treatment planning because of using small miniplates to large reconstruction plates. However, when the fixation method fails, it causes malunion, nonunion, and/or infection, and sometimes it has been associated with large bone defects. The authors describe a clinical report of a failed miniplate fixation for atrophic mandibular fracture management. The authors used a load-bearing reconstruction plate combined with autogenous bone graft from iliac crest for this retreatment. The authors show a follow-up of 6 months, with union of the fracture line and no complication postoperatively. © 2013 by Mutaz B. Habal, MD.

Energy Management and Control for Islanded Microgrid Using Multi-Agents

This paper presents a multi-agent system for real-time operation of simulated microgrid using the Smart-Grid Test Bed at Washington State University. The multi-agent system (MAS) was developed in JADE (Java Agent DEvelopment Framework) which is a Foundation for Intelligent Physical Agents (FIPA) compliant open source multi-agent platform. The proposed operational strategy is mainly focused on using an appropriate energy management and control strategies to improve the operation of an islanded microgrid, formed by photovoltaic (PV) solar energy, batteries and resistive and rotating machines loads. The focus is on resource management and to avoid impact on loads from abrupt variations or interruption that changes the operating conditions. The management and control of the PV system is performed in JADE, while the microgrid model is simulated in RSCAD/RTDS (Real-Time Digital Simulator). Finally, the outcome of simulation studies demonstrated the feasibility of the proposed multi-agent approach for real-time operation of a microgrid.

Desenvolvimento de um sistema de gerenciamento de energia (EMS - Energy Management System) para a rede elétrica inteligente (Smart Grid)

Pós-graduação em Engenharia Elétrica - FEIS

Centralized vs. Distributed Connection Management Schemes under Different Traffic Patterns in Wavelength-Convertible Optical Networks

Centralized and Distributed methods are two connection management schemes in wavelength convertible optical networks. In the earlier work, the centralized scheme is said to have lower network blocking probability than the distributed one. Hence, much of the previous work in connection management has focused on the comparison of different algorithms in only distributed scheme or in only centralized scheme. However, we believe that the network blocking probability of these two connection management schemes depends, to a great extent, on the network traffic patterns and reservation times. Our simulation results reveal that the performance improvement (in terms of blocking probability) of centralized method over distributed method is inversely proportional to the ratio of average connection interarrival time to reservation time. After that ratio increases beyond a threshold, those two connection management schemes yield almost the same blocking probability under the same network load. In this paper, we review the working procedure of distributed and centralized schemes, discuss the tradeoff between them, compare these two methods under different network traffic patterns via simulation and give our conclusion based on the simulation data.

Knowledge management in health: a systematic literature review

Knowledge has been used as a resource for intelligent and effective action planning in organizations. Interest in research on knowledge management processes has intensified in different areas. A systematic literature review was accomplished, based on the question: what are the contributions of Brazilian and international journal publications on knowledge management in health? The sample totaled 32 items that complied with the inclusion criteria. The results showed that 78% of journals that published on the theme are international, 77% of researchers work in higher education and 65% have a Ph.D. The texts gave rise to five thematic categories, mainly: development of knowledge management systems in health (37.5%), discussion of knowledge management application in health (28.1%) and nurses' function in knowledge management (18.7%).