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.

Programmable logic design of a compact Genetic Algorithm for phasor estimation in real-time

The main objective of this work is to present an efficient method for phasor estimation based on a compact Genetic Algorithm (cGA) implemented in Field Programmable Gate Array (FPGA). To validate the proposed method, an Electrical Power System (EPS) simulated by the Alternative Transients Program (ATP) provides data to be used by the cGA. This data is as close as possible to the actual data provided by the EPS. Real life situations such as islanding, sudden load increase and permanent faults were considered. The implementation aims to take advantage of the inherent parallelism in Genetic Algorithms in a compact and optimized way, making them an attractive option for practical applications in real-time estimations concerning Phasor Measurement Units (PMUs).

Implementing the Objective Structured Clinical Examination in a Geriatrics Fellowship Program-A 3-Year Experience

The Objective Structured Clinical Examination (OSCE) appears to be an effective alternative for assessing not only medical knowledge, but also clinical skills, including effective communication and physical examination skills. The purpose of the current study was to implement an OSCE model in a geriatrics fellowship program and to compare the instrument with traditional essay examination. Seventy first- and second-year geriatric fellows were initially submitted to a traditional essay examination and scored from 0 to 10 by a faculty member. The same fellows subsequently underwent an OSCE with eight 10-minute stations covering a wide range of essential aspects of geriatric knowledge. Each OSCE station had an examiner responsible for its evaluation according to a predefined checklist. Checklist items were classified for analysis purposes as clinical knowledge items (CKI) and communication skills items (CSI); fellow responses were scored from 0 to 10.Although essay examinations took from 30 to 45 minutes to complete, 180200 minutes were required to evaluate fellows using the proposed OSCE method. Fellows scored an average of 6.2 +/- 1.2 on the traditional essay examination and 6.6 +/- 1.0 on the OSCE (P < .001). Subanalyses of OSCE scores indicated that average performance on CKI was lower than the average on CSI (6.4 +/- 1.1 vs. 8.4 +/- 1.1; P < .001). Fellow performance on the essay examination was similar to their performance on CKI (P = .13). Second-year fellows performed better than first-year fellows on the essay examination (P < .001) and CKI (P = .05), but not on CSI (P = .25).The OSCE was successfully implemented as an educational strategy during a geriatrics fellowship program. Combining different testing modalities may provide the best assessment of competence for various domains of knowledge, skills, and behavior.