REACTIVE POWER OPTIMIZATION USING AN ANALYTIC HIERARCHICAL PROCESS AND A NONLINEAR OPTIMIZATION NEURAL-NETWORK APPROACH

A new idea using an analytic hierarchical process (AHP) is proposed fo r Var placement compensation. AHP uses parallel analytical criteria fo r selecting and ranking placement of Var compensation. Due to their in dependent nature these criteria are not necessarily the same although both aim to identify weak nodes in maintaining system voltages. AHP al so considers quantitative criteria. It is especially suitable for prob lems that are difficult to analyse. AHP provides a simple, convenient and comprehensive means of selection and ranking, The proposed algorit hms have been tested on the IEEE 14-bus and 30-bus systems with satisf actory results. The paper also proposes a new nonlinear optimisation n eural network approach to study the reactive power problem, The approa ch is applied to Var control optimisation, in which the objective is t o minimise the system voltage profile. The approach is a penalty-minim isation method with weights based on optimisation theory and neural op timisation methods. It is used to solve the nonlinear programming prob lem with equality and inequality constraints. The paper demonstrates t hat the energy function used is a Lyapunov function, and the equilibri um point of the proposed neural network corresponds to the optimal sol ution of a constrained optimisation problem.