Constrained state estimation with applications in water distribution network monitoring

This paper investigates the effects of imposing bounds on the measurements used in weighted least-square s (WLS) state estimation. The active limits f or such bounds are derived and algorithms based on linear and quadratic pro gramming kernels are presented. Using the lower limit for the bounds, the c onstrained WLS scheme becomes an adaptive maximally constrained scheme: M-W LS. For some networks, the poor prior knowledge of the global error charact eristic results in some measurements having less influence than would be ex pected from the local error characteristics of their transducers. By using M-WLS estimation, the influence of such measurements on state estimation ma y be improved. Analysis of the adaptive bounding of the scheme can also lea d to identification of critical measurement discrepancies. For the purpose of illustration, results are presented using simulated measurements; the he ad measurements (pressures) are consistent with nominal demands (nodal flow s) and the demand measurements are generated by superimposing random errors of 2.5 l s(-1) rms on the nominal demands.