A. Bernieri et al., NEURAL NETWORKS AND PSEUDO-MEASUREMENTS FOR REAL-TIME MONITORING OF DISTRIBUTION-SYSTEMS, IEEE transactions on instrumentation and measurement, 45(2), 1996, pp. 645-650
A state estimation scheme for power distribution systems, based on Art
ificial Neural Networks (ANN's), is proposed, Despite the influence of
measurement uncertainties, it allows quantities describing the distri
bution system operation to be identified on-line, thereby constituting
neural ''pseudo-instruments''. Details of the design and optimization
of such a neural scheme are discussed, underlining the importance of
ANN tuning to achieve greater levels of accuracy, The performance obta
ined in a study case, for different types of operating conditions, was
analyzed and confirmed the feasibility and the robustness of the prop
osed approach, This neural estimation scheme proves to be preferable t
o traditional mathematical approaches whenever there are online requir
ements, due, of course, to the typically high operating speed of ANN's
.