Abstract

Abstract

Abstract
Fuzzy modelling of power systems is proposed, to take in account the qualitative aspects and vagueness or uncertainty that have not, in fact, a random nature and therefore cannot be modelled by a probabilistic approach. An operative procedure to derive fuzzy load diagrams associated with different types of energy consumption is presented. The feasibility of the development of fuzzy linear programming models for power system planning is demonstrated. A DC and an AC fuzzy load flow formulations are developed and the quality and usefulness of the results obtained with them is made evident with the help of an example.

Abstract
The authors present a novel automatic transient stability classification approach, based on a two-stage hierarchical classifier obtained through the combination of two different pattern recognition structures. The first-level classifier uses low-cost computational variables evaluated at the fault occurrence moment. The classification structure used in this first level is a linear one and is obtained through the combination of a Fisher discriminant transformation and a Bayesian probabilistic approach for the independent term determination. The second-level classifier uses a new set of transient variables, directly related to kinetic and potential energies at the fault clearance moment. The classification structure in this second level is based on a weighted K nearest-neighbor rule, using a Euclidian metric defined in an optimum discriminant plane, where all data have been previously projected. Results obtained in the CIGRE test system are presented, showing that this method provides an efficient tool for online transient stability assessment of electric power systems.

Abstract
The versatility of Bewley's method for the calculation of transient currents and voltages using personal computers is shown. The computer time and storage required are relatively small. SOBBE program is shown to be an efficient program for the study of transient phenomena of medium-size power system networks. Numerical results are presented.

Abstract
This paper presents a new candidate method for on-line transient security assessment and enhancement based on pattern recognition techniques. Transient state variables are used as primary features and the classifier is obtained in two phases, through the combination of an optimum discriminant transformation together with a probabilistic procedure. The proposed security functions can be further refined by means of a second level classifier based on an optimal discrimination plane and using a weighted K nearest neighbor rule. It is shown that this method provides also an efficient and simple tool for on-line preventive control. Results obtained for several contingencies in the CIGRE test system are discussed.