Showing papers in "Electric Power Systems Research in 1994"

TL;DR: In this article, a modified simulated annealing technique is applied to network reconfiguration for loss reduction in distribution systems, where a set of simplified line flow equations is first presented for approximate loss calculation, and the loss profile of the whole system can be computed in a straightforward single-pass manner.

TL;DR: Using existing tie and sectionalizing switches, reconfiguration of the distribution system represents an attractive method of loss reduction as it can be implemented at minimal cost to the utility.

TL;DR: New fault location algorithms based on synchronized sampling based on a time domain model of a transmission line are introduced, which show high accuracy while the computational burden is moderate.

TL;DR: It is shown that, with careful network design, the back-propagation learning procedure is an effective way of training neural networks for electrical load prediction.

TL;DR: An economics based model of sectionalizer allocation in single radial feeder distribution systems is presented and a genetic algorithm based procedure is developed to solve the problem of optimal sectionalizers allocation.

TL;DR: This paper will present an explanation of the genetic algorithm, the implementation of this algorithm and the results for a six-generator 24-hour commitment schedule.

TL;DR: In this article, the minimum total load interruption cost by taking into account the current, voltage and system operating and structural constraints is provided for large-scale urban distribution systems after heavy disturbances.

TL;DR: A new method for optimal network decomposition based on genetic algorithms (GAs) is presented and the genetic algorithm approach is found to produce significantly better solutions.

TL;DR: In this article, the least-square and least-absolute-value techniques are applied to the voltage harmonic estimation of a three-phase six-pulse converter, and compared with respect to the signal/no noise ratio, number of samples, sampling frequency, computation time and missing data.

TL;DR: This paper presents short-term load forecasting using a genetic algorithm to optimize the weights of an artificial neural network and presents a technique that allows a genetic algorithms to consistently find a good set of weights for an artificial neutral network.

TL;DR: In this paper, the authors present the results of an investigation of the economic dispatch problem in view of the Clean Air Act Amendment (CAAA) of 1990 and propose two, easy-to-implement, strategies to solve the problem subject to environmental constraints that reflect the requirements of the CAAA.

TL;DR: In this article, an artificial neural network is proposed to provide an energy measure which is an indication of the power system's proximity to voltage collapse and test results are presented on a sample power system.

TL;DR: A comparison of Scott and Leblanc transformers for supplying unbalanced electric railway demands mainly from the point of view of voltage imbalance is presented in this paper, where the equivalent loads and formulas for estimating the voltage imbalance for these two connections are derived and compared.

TL;DR: In this paper, the authors present the fundamental concepts of voltage stability, gives a short recall of the classical voltage theory and different criteria currently available for predicting voltage collapse problems in power systems, which have been associated with multiple power flow solutions, bifurcation, dynamics of tap changers, stochastic loads, singular values etc.

TL;DR: In this article, the main flux saturation of an induction motor is considered in the process of switching off and reclosing transients of a single-and double-cage induction motor with capacitor reactive power compensation.

TL;DR: In this paper, a computer-rated transmission expansion planning approach using the network simplex technique is proposed, which uses variable load structure and generator cost curves for economic generation, assuming an increased load demand, an optimum network configuration is designed.

TL;DR: In this paper, the damping of electromechanical oscillations of synchronous generators using an output feedback static var controller is investigated, and an eigenstructure assignment technique is applied to design this controller.

TL;DR: In this paper, an improved sensitivity model is developed for predicting the proximity of the power system steady state to the voltage stability boundaries, which can predict voltage collapse and suggest corrective action, thus providing valuable information in both the planning and operating environments.

TL;DR: A digital fault location algorithm for calculating the fault distance on a power transmission line can be designed using any of three approaches: the steady-state phasor approach, the differential equation approach and the travelling-wave approach as mentioned in this paper.

TL;DR: In the present paper not only are the power generations and loads in the power systems described by fuzzy sets, but the availability of each generating unit is also presented in fuzzy terms.

TL;DR: In this paper, a voltage angle or magnitude update solution after every set of FDLF adjustments is introduced to circumvent the problem of oscillations, or even divergence of the power flow solution.

TL;DR: A restoration system for maximizing the restorable loads in a distribution network using three different restoration schemes, a network state knowledge base (NSK) and a restoration knowledgebase (RKB) is described.

TL;DR: In this article, the relationship between distribution system reliability and restoration analysis is explored and it is demonstrated that sets which may be used in describing power restoration are subsets of those developed during reliability calculations.

TL;DR: In this article, a neuro-fuzzy hybrid power system stabilizer (PSS) design for damping electromechanical modes of oscillation and enhancing power system synchronous stability is presented.

TL;DR: A supervised learning procedure is adopted and the familiar back-propagation technique is used in training the network and the performance of the neural network is evaluated with the aid of a benchmark case.

TL;DR: In this article, a two-stage searching approach to the switching operation is proposed, where the evaluation function of each tie switch is estimated and a depth-first search is used to find all possible switching operations.

TL;DR: In this article, an analysis of the dynamic performance of a closed-loop hysteresis current controlled voltage source inverter (VSI) fed cage induction motor drive is presented.

TL;DR: An evaluative study of three real-time artificial intelligence toolkits: Muse, Kappa and Nexpert Object is presented, based on the knowledge representation and reasoning paradigm, the user's interface, integration with external programs and real- time databases, portability, price and execution speed, and the capabilities of such toolKits to recognize the power system conditions responsible for causing alarms.

TL;DR: In this article, a Monte Carlo approach to radial distribution feeder reliability assessment is described, and the results of a series of simulations studying the distributional variation associated with reliability indices for distribution feeders are presented.