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Many potential benefits related to the integrations of various corporate information systems in a utility have been recognized. In order to evaluate an integrated distribution system SCADA and AM/FM system, in this paper, a discrete time simulation method is used. Distributed architectures of SCADA and AM/FM systems and their integration are simulated by using an off the shelf simulation package. The changes in the response times of SCADA functions due to the integration are investigated. Test results have indicated that a simple SCADA-AM/FM integration using data file transfer scheme could enhance distribution system dispatchers' performance in day-to-day work without giving up much in the response times of SCADA functions.

A method that uses uncertain network data, load distribution information and telemetered data for feeder voltage profile calculation is proposed in this paper. In the proposed method, data involved in the calculation are represented by using fuzzy numbers. All possible feeder voltage solutions within bounds obtained from fuzzy arithmetic are considered. The mean values of the obtained intervals are useful for system operation planning, and lower and upper bounds can be used to alert dispatchers for possible system deterioration. Measurements are included in the calculation to reduce the uncertainty of the obtained results. The voltage calculation method is used to evaluate the measurement configuration and a meter placement scheme is proposed to select the locations of new meters from the standpoint of minimizing the uncertainties of the calculated voltage profile. Keywords: Distribution System Analysis, Distribution Automation, Fuzzy Arithmetic.

A new external network modeling approach is proposed in this paper. This approach is based on load flow solutions and a fuzzy linear programming formulation. The idea of the proposed method is to find an acceptable solution that matches most closely to the knowledge we have for the external network. Uncertainties of the external network data are modeled by using fuzzy set theory. Test results have shown that the proposed method provides a stable and flexible tool for finding an estimated real-time external network solution. Contingency analysis performed on the obtained models has indicated that the external network solutions are acceptable.

The use of trouble call information for handling service interruption events that exist between primary feeders and customers is discussed in this paper. Artificial neural networks are used for fast pattern recognition and classification of trouble calls such that the time and effort required for service restoration can be reduced. Back propagation network is chosen as our neural network model. This proposed trouble call analysis system is embedded in an integrated Automated Mapping, Facilities Management and Geographic Information System environment.

The W-matrix method has been proposed in many literatures to exploit parallelism in the solution of many power system problems. This paper presents a storage scheme for storing the sparse W-matrix in solving linear equations on vector computers. Based on the proposed storage scheme, several efficient algorithms have been developed to perform the W-matrix vector multiplication for finding linear system solution. In this paper, attention is given to the issues of vector length, data movement between vector registers and memory, and the vector stride. The proposed storage scheme and algorithms are tested on Convex 3840 and Alliant FX/80 vector machines. It is shown that a speedup of two to four times is obtainable as compared to traditional scalar operation. The proposed storage scheme and algorithms can be applied to power system problems that require repeat solutions of linear system, such as load flow, contingency analysis, fast decoupled state estimation and short circuit calculations.

Karmarkar's interior point method, said to perform much faster than the simplex method in solving large scale linear programming problems, has attracted a great deal of attention in recent years. In this paper we present a preliminary implementation of the interior point algorithm and test results on the network constrained security control problem. Test results indicate that when solving various sizes of network constrained security control linear programming problems with increasing numbers of controls and constraints, both the total number of iterations and the overall execution time grow at a slower rate in the interior point method than in the simplex method. The number of iterations required by the interior point method is relatively insensitive to problem size and composition, while iteration counts for the simplex method tend to be much higher in the presence of large numbers of control variables and/or constraints.

The artificial neural network (ANN) technique for short term load forecasting (STLF) has been proposed by several authors, and gained a lot of attention recently. In order to evaluate ANN as a viable technique for STLF, one has to evaluate the performance of ANN methodology for practical considerations of STLF problems. This paper makes an attempt to address these issues. The paper presents the results of a study to investigate whether the ANN model is system dependent, and/or case dependent. Data from two utilities were used in modeling and forecasting. In addition, the effectiveness of a next 24 hour ANN model in predicting 24 hour load profile at one time was compared with the traditional next one hour ANN model.

This letter presents a systematic approach that composes network congestion warning indices and lights of given power service areas. Based on typical power system analysis methods and engineering judgments, a set of indices and congestion severity measures were developed. The composite indices include the normal condition margin index and the contingency margin index, and each includes three measures with corresponding weightings to address the current and future transmission margins, single worst transmission element, and system average loading. The weighting factors are adjusted according to system characteristics and specific planning principles adopted by stakeholders. The congestion warning lights are then defined on a two-dimension plot based on the indices computed. The resultant indicating lights can be used as simple media for conveying possible network congestion problems. Index Terms--Network congestion, system planning, warning index.

Abstract: Excellent ultra-shallow p+n junctions have been formed by thermally treating the BF2 +-implanted Si samples by excimer laser annealing (ELA) at 300–400mJcm−2 with post low-temperature long-time furnace annealing (FA) at 600°C. A junction with a leakage current density lower than 20nAcm−2 and a sheet resistance smaller than 200Ω□−1 can be well achieved. No considerable dopant diffusion is observed by using this low-thermal-budget annealing process. However, by simply using the ELA treatment at 300–400mJcm−2, the resultant junction shows a leakage current density as high as 104 nAcm−2 and a peripheral leakage current density of 103 nAcm−1. The large junction leakage is primarily due to the leakage current generated within the junction region near the local-oxidation-of-silicon (LOCOS) edge, and which is substantially caused by the ELA treatment. The large peripheral junction leakage current density can be significantly reduced to be about 0.2nAcm−1 after a post low-temperature FA treatment at 600°C. As a result, the scheme that employs ELA treatment with post low-temperature FA treatment would be efficient for forming excellent ultra-shallow p+n junctions at low thermal budget. [Copyright &y& Elsevier]