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The effectiveness of harmonic state estimation (HSE) in identifying the location and magnitude of harmonic sources is largely dependent on the accuracy of the measurements. Measurement errors (or bad data) can be classified into two groups; measurement noise and gross error. This paper uses a statistical approach (cumulative probability density functions) obtained from five thousand Monte Carlos runs to investigate the impact of measurement noise and gross errors in harmonic state estimation. The Lower South Island of the New Zealand system is used as the test system and the results are probability curves containing the statistics of the estimation error. The effect of additional measurements on an over-determined system to filter noise is also discussed.