Abstract
In this paper, a weighted least square (WLS) state estimation algorithm with equality constraints is proposed for smart distribution networks embedded with microgrids. Since only a limited number of real-time measurements are available at the primary or secondary substations and distributed generation sites, load estimates at unmeasured buses remote from the substations are needed to execute state estimation. The load information can be obtained by forecasted and historical data or smart real-time meters. The proposed algorithms can be applied in either grid-connected or islanded operation mode and can efficiently identify breaker status errors at the main substations and feeders, where sufficient measurement redundancy exists. The impact of the accuracy of real and pseudo-measurements on the estimated bus voltages is tested with a 55-bus distribution network including distributed generation.
Highlights
State estimation (SE) will be a key element function in smart distribution automation to provide inputs to various functions, such as optimal feeder reconfiguration, capacitor switching, and demand-side management
The proposed state estimation algorithms are implemented in a MATLAB (Mathworks, Inc., Natick, MA, USA) environment
Bus 60 is the main high voltage (HV) supply point through a 150/15 kV, HV/MV transformer
Summary
State estimation (SE) will be a key element function in smart distribution automation to provide inputs to various functions, such as optimal feeder reconfiguration, capacitor switching, and demand-side management This function has already become popular to transmission-level power systems for their control and supervision, enabling a large variety of measurements and adopting techniques to detect and identify faulted measurements. In [2], the usage of real-time measurements with forecasted loads or pseudo-measurements to increase the accuracy of estimated states is suggested, and how power flow and current measurements affect bad-data detection and identification is demonstrated. Like the accurate solution for multi-area state estimation in distribution grids based on a modified WLS formulation [23] and the inclusion of any type of measurement regardless of their statistical model through a Bayesian approach [24], have been included to the SE problem.
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