Reactive power optimisation using an analytic hierarchical process and a nonlinear optimisation neural network approach

A new idea using an analytic hierarchical process (AHP) is proposed for VAr placement compensation. AHP uses parallel analytical criteria for selecting and ranking placement of VAr compensation. Due to their independent nature these criteria are not necessarily the same although both aim to identify weak nodes in maintaining system voltages. AHP also considers quantitative criteria. It is especially suitable for problems that are difficult to analyse. AHP provides a simple, convenient and comprehensive means of selection and ranking. The proposed algorithms have been tested on the IEEE 14-bus and 30-bus systems with satisfactory results. The paper also proposes a new nonlinear optimisation neural network approach to study the reactive power problem. The approach is applied to VAr control optimisation, in which the objective is to minimise the system voltage profile. The approach is a penalty-minimisation method with weights based on optimisation theory and neural optimisation methods. It is used to solve the nonlinear programming problem with equality and inequality constraints. The paper demonstrates that the energy function used is a Lyapunov function, and the equilibrium point of the proposed neural network corresponds to the optimal solution of a constrained optimisation problem