Fast fault section estimation in distribution control centers using adaptive genetic algorithm

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A simple and effective inverse projection scheme for void distribution control in topology optimization

The ability to control both the minimum size of holes and the minimum size of structural members are essential requirements in the topology optimization design process for manufacturing. This paper addresses both requirements by means of a unified approach involving mesh-independent projection techniques. An inverse projection is developed to control the minimum hole size while a standard direct projection scheme is used to control the minimum length of structural members. In addition, a heuristic scheme combining both contrasting requirements simultaneously is discussed. Two topology optimization implementations are contributed: one in which the projection (either inverse or direct) is used at each iteration; and the other in which a two-phase scheme is explored. In the first phase, the compliance minimization is carried out without any projection until convergence. In the second phase, the chosen projection scheme is applied iteratively until a solution is obtained while satisfying either the minimum member size or minimum hole size. Examples demonstrate the various features of the projection-based techniques presented.

Intelligent behavior in a Cyber-Ambient training system for control center operators

This paper deals with the application of an intelligent tutoring approach to delivery training in diagnosis procedures of a Power System. In particular, the mechanisms implemented by the training tool to support the trainees are detailed. This tool is part of an architecture conceived to integrate Power Systems tools in a Power System Control Centre, based on an Ambient Intelligent paradigm. The present work is integrated in the CITOPSY project which main goal is to achieve a better integration between operators and control room applications, considering the needs of people, customizing requirements and forecasting behaviors.

Fault section estimation in automated distribution substations

In this paper, a methodology based on Unconstrained Binary Programming (UBP) model and Genetic Algorithms (GAs) is proposed for estimating fault sections in automated distribution substations. The UBP model, established by using the parsimonious set covering theory, looks for the match between the relays' protective alarms informed by the SCADA system and their expected states. The GA is developed to minimize the UBP model and estimate the fault sections in a swift and reliable manner. The proposed methodology is tested by utilizing a real-life automated distribution substation. Control parameters of the GA are tuned to achieve maximum computational efficiency and reduction of processing time. Results show the potential and efficiency of the methodology for estimating fault section in real-time at Distribution Control Centers. ©2009 IEEE.

Connecticut Poison Control Center. 2002 and 2003 Annual Report and Poison Exposure Statistics

The Connecticut Poison Control Center (CPCC) at the University of Connecticut Health Center (UCHC) was established in 1957 under Connecticut General Statute 10a- 132. The CPCC’s main responsibility is to provide 24-hour emergency toxicology management consultations for victims of poisoning, and serve as a source for pharmacology and toxicology-related information. The center monitors the epidemiology of human poisoning and provides surveillance for environmental and occupational chemical exposures, drug abuse, and pharmaceutical interactions and adverse effects. The CPCC performs toxicological research, and provides formal toxicology instruction for allied health professionals, as well as professional and consumer poison prevention education. The CPCC is one of 63 nationwide centers certified by the American Association of Poison Control Centers (AAPCC), and the only poison center in the state of Connecticut. The AAPCC establishes standards of care for poisoning and administers the Toxic Exposure Surveillance System (TESS), a national database of poisoning statistics, to which the CPCC is a contributor.

Connecticut Poison Control Center . 2004 and 2005 Bi-Annual Report on Poisoning in Connecticut

For the past 49 years, the Connecticut Poison Control Center (CTPCC) based at the University of Connecticut Health Center (UCHC), has managed human exposures and poisonings throughout the state and continues to serve as a toxicologic center of excellence. A human exposure may be defined as contact by skin, eye, mouth or inhalation to any substance: animal, mineral or vegetable, including: bites, commercial products, chemicals, drugs, natural remedies and plants among others. A poisoning is any injury to the body resulting from an exposure. Toxicology is the scientific study of the adverse effects of any substance on the body.

Boston Air Route Traffic Control Center (ARTCC) lighting study /

Prepared by Raytheon Company, Equipment Division, Air Traffic Control Directorate, under contract DOT-FA 76WA-3738.

Operation rain-check at the Chicago Air Route Traffic Control Center, Aurora, Illinois.

Mode of access: Internet.

Welcome to Denver Air Route Traffic Control Center, Longmont, Colorado.

Mode of access: Internet.

Operator's, organizational, direct support, and general support maintenance manual for communications technical control center AN/TSQ-84 (NSN 5895-01-007-4788).

"April 1977."

Distribution, control, and measurement of irrigation water on the farm /

"Issued July 1963."

Online distribution management framework by incorporating wind generation

In distribution system operations, dispatchers at control center closely monitor system operating limits to ensure system reliability and adequacy. This reliability is partly due to the provision of remote controllable tie and sectionalizing switches. While the stochastic nature of wind generation can impact the level of wind energy penetration in the network, an estimate of the output from wind on hourly basis can be extremely useful. Under any operating conditions, the switching actions require human intervention and can be an extremely stressful task. Currently, handling a set of switching combinations with the uncertainty of distributed wind generation as part of the decision variables has been nonexistent. This thesis proposes a three-fold online management framework: (1) prediction of wind speed, (2) estimation of wind generation capacity, and (3) enumeration of feasible switching combinations. The proposed methodology is evaluated on 29-node test system with 8 remote controllable switches and two wind farms of 18MW and 9MW nameplate capacities respectively for generating the sequence of system reconfiguration states during normal and emergency conditions.

Center for Disease Control family planning services: annual summary.

Mode of access: Internet.

Extended Fault-Location Formulation for Power Distribution Systems

In this paper, an extended impedance-based fault-location formulation for generalized distribution systems is presented. The majority of distribution feeders are characterized by having several laterals, nonsymmetrical lines, highly unbalanced operation, and time-varying loads. These characteristics compromise traditional fault-location methods performance. The proposed method uses only local voltages and currents as input data. The current load profile is obtained through these measurements. The formulation considers load variation effects and different fault types. Results are obtained from numerical simulations by using a real distribution system from the Electrical Energy Distribution State Company of Rio Grande do Sul (CEEE-D), Southern Brazil. Comparative results show the technique robustness with respect to fault type and traditional fault-location problems, such as fault distance, resistance, inception angle, and load variation. The formulation was implemented as embedded software and is currently used at CEEE-D`s distribution operation center.

Hybrid fault diagnosis scheme implementation for power distribution systems automation

Power distribution automation and control are import-ant tools in the current restructured electricity markets. Unfortunately, due to its stochastic nature, distribution systems faults are hardly avoidable. This paper proposes a novel fault diagnosis scheme for power distribution systems, composed by three different processes: fault detection and classification, fault location, and fault section determination. The fault detection and classification technique is wavelet based. The fault-location technique is impedance based and uses local voltage and current fundamental phasors. The fault section determination method is artificial neural network based and uses the local current and voltage signals to estimate the faulted section. The proposed hybrid scheme was validated through Alternate Transient Program/Electromagentic Transients Program simulations and was implemented as embedded software. It is currently used as a fault diagnosis tool in a Southern Brazilian power distribution company.