PARAMETRISATION TECHNIQUES AND INTELLIGENT SYSTEMS APPLIED TO CONTINUATION POWER FLOW IN ORDER TO IMPROVING THE ELECTRICAL POWER SYSTEMS

Abstract

Currently, the continuing trend of increasing load demands coupled with economic and environmental constraints for the construction of new power plants and transmission lines, has led energy systems to operate closer to their limits, increasing the probability of occurrence of stability problems. The studies related to static voltage stability require the qualitative evaluation of several operating conditions of the system under different loading conditions and contingencies. The continuation method is one of the main tools used in these studies due to their robustness and versatility, and has been used among others: in the evaluation of the effects of variations of parameters of transmission lines on the power system, in the observation of the behavior of the tensions of the bus system and in the comparison of planning strategies aiming at the adequate proposition of enlargements and reinforcements of the network with the intention of avoiding the cut of load. The publications show an increasing interest on the part of the companies of the electrical sector even in small improvements of this method aiming at the improvement of its performance in the several studies. In the continuation method, the Jacobian matrix singularity is removed by adding parameterized equations in the load flow equations. From the previous studies, created a great expectation that it is possible to be used several global variables, such as the real or reactive power of the slack bus, total losses of active power among others, to compose the equation of the line or the equation quadratic. Another very attractive idea is to use various plans for the complete design of the P-V curve, an example is the plane formed by the magnitudes versus the angles of the node voltages, resulting in a trajectory of solutions with a linear aspect and thus, enabling the removal of singularity during the tracing of all P-V curve. The use of these variables also has the advantage of requiring only small changes in the existing conventional Load Flow programs and practically, does not affect the degree of sparsity of the Jacobian matrix. Another important factor to be investigated is the use of artificial neural networks (ANNs) to analyze the load margin and consequently to obtain the point of maximum loading of the electrical systems. Thus, this project aims to continue the analysis of these techniques of geometric parameterization and also, through the RNAs improve their efficiency in obtaining the load margin and in the reduction of computational time spent by the geometric parameterization techniques. It is also intended to investigate the feasibility of the use of Newton's decoupled methods and of XB and BX versions of the fast decoupled continuation power flow, as well as some new methods recently presented in the literature. (AU)